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Welcome, Hugging Face!

We are thrilled to announce our investment in Hugging Face, who has built the largest and most important open source community in AI in the world.

  • Founder: Clément Delangue, Julien Chaumond, Thomas Wolf
  • Sector: Artificial Intelligence
  • Location: Brooklyn, NY

At Salesforce Ventures, we strongly believe open source will shape the future of the artificial intelligence landscape. Open source enables collaboration, transparency, accountability, innovation, and trust. As AI becomes increasingly critical across industries, an open ecosystem will be key to ensuring AI technology develops responsibly and ethically.

That’s why today, we are excited to announce we are leading the Series D round in Hugging Face, the leading open source platform for data science and machine learning (ML). The company acts as the central hub connecting AI developers, researchers, and enthusiasts—like a GitHub for AI.

Founded by Clément Delangue,Julien Chaumond and Thomas Wolf in 2016, Hugging Face began as an AI chatbot. The founders soon realized the true potential was not the chatbot itself, but the natural language processing (NLP) models powering it. We decided to back this talented founding team because of their creative vision, technical expertise, and proven ability to build passionate communities around their products. In particular, Clem’s business acumen, Julien’s engineering skills, and Thomas’ research background form a powerful combination capable of advancing the field of AI.

In 2018 to 2019, Hugging Face quickly garnered fame and a burgeoning open source following as it built a Pytorch replica of the popular Transformer model which was widely adopted, and created the Transformers library that provides easy access to thousands of pretrained models, including state-of-the-art NLP models. Since then, Hugging Face has expanded into other categories beyond just NLP, such as computer vision and speech, and built the world’s largest open source community for AI, with over 2 million users interacting with its models, datasets, and other resources. 

Open source has been the driving force behind much of the rapid progress in AI over the past decade. Nearly all major ML frameworks like TensorFlow and PyTorch are open source. Similarly, breakthrough models like LLaMA, BERT, and Stable Diffusion are all open source. By transparently sharing ideas and innovations, researchers can build upon each other’s work to advance the field faster than any one organization could alone.Open source also promotes transparency and trust in AI systems and allows researchers worldwide to inspect, audit, and improve them. This transparency is critical as AI is deployed into sensitive domains like healthcare and finance. As we hear time and again from enterprises, they want to adopt a hybrid strategy (or approach) that combines the benefits of open and closed-source models.

We believe the future of AI will be driven by a thriving open ecosystem of researchers, developers, enterprises, and enthusiasts collaborating together. Hugging Face sits at the center of the open AI movement and has become the most important community for ML researchers and practitioners. 

The Hugging Face Hub brings together over 1 million repositories, including models, datasets and app demos, in one central platform. This makes it easy for anyone to find and access the latest innovations in AI, collaborate with others, and build on top of existing work. The Hub contains essentially all major open source AI models and is frequently the first destination for researchers to release their work – for instance, the much talked about LLaMA 2 model from Meta, Falcon, Vicuna and even Salesforce research team’s BLIP model – making Hugging Face a one-stop shop for the ML community. It promotes a virtuous cycle where the platform facilitates extremely rapid innovation cycles. This open ecosystem approach has been critical to the meteoric progress in AI over the past decade.

Beyond accelerating research, Hugging Face also provides the tools enterprises need to operationalize AI. This includes inference endpoints to deploy models into production, AutoTrain for scalable, low-code model training, Spaces to easily build and share demos and ML apps, and private Hugging Face Hubs for internal collaboration and model hosting. Hugging Face supports the entire ML workflow from research to deployment, enabling organizations to go from prototype to production seamlessly. This is another vital reason for our investment in Hugging Face – given this platform is already taking up so much of ML developers and researchers’ mindshare, it is the best place to capture the end-to-end ML workflow of its users.

The combination of its massive open community and enterprise-ready tools for deploying AI makes Hugging Face a fundamental part of any organization’s ML strategy. For both researchers and enterprises, Hugging Face is the gateway to the future of AI. This has led to fast-growing enterprise team adoption, an increasing number of whom have started to pay for the various ML tools on the company’s platform. We were deeply impressed by the speed of commercial growth (one of the fastest we have seen in recent history) and at the continuous amazing feedback we received through customer conversations. Many of these customers are not just the next AI native startup or big tech company who already has the ML engineering talent, but established enterprises from traditional industries such as healthcare, financial services and automotive. This speaks to how profoundly impactful the Hugging Face platform is to companies’ journey to AI adoption and the excitement from customers further solidified our belief that Hugging Face will become a generational company.

We believe open source AI, and Hugging Face’s role in catalyzing it, will fundamentally transform industries. We’re thrilled to partner with Clem, Julien, Thomas, and the entire Hugging Face team on their mission to democratize AI. Together, we’ll work to maximize the positive impacts of open AI across industries and society.

Welcome to the Salesforce Ventures family, Hugging Face!

Welcome, Protect AI!

  • Founder: Ian Swason, Daryan Dehghanpisheh, Badar Ahmed
  • Sector: Cybersecurity, Artificial Intelligence
  • Location: Seattle, WA

Building the Future of MLSecOps: Salesforce Ventures Invests in Protect AI

As the wave of AI startups began exploding in the early days of 2023, we started asking ourselves how to apply cybersecurity to this quickly emerging space. Security of ML systems and AI applications differs from typical software development, as the ML pipeline goes beyond code. The dynamic ML development life cycle includes data, unique machine learning artifacts, and a vast ecosystem of open-source libraries, packages, and frameworks. This leads to the need for new tools that provide full transparency and visibility across all elements of an ML pipeline. The tailwind has only strengthened as AI adoption reached a seminal point, with increasing consumer adoption and enterprises gearing up for more deployments of AI systems, driven by interest in generative applications. Regulators are also focusing on AI security. In May this year, White House officials hosted CEOs from leading AI companies and announced new US policies drafted to mitigate AI risks, shortly before the EU approved its AI Act on June 14th, classifying AI systems by risk and mandating development and usage requirements.

As artificial intelligence continues its rapid trajectory, a new startup has emerged to help secure AI systems across the machine learning lifecycle. Salesforce Ventures is excited to announce our investment in Protect AI, the pioneers of MLSecOps.

Founded in 2022 by serial entrepreneurs Ian Swanson, Daryan Dehghanpisheh, and Badar Ahmed, Protect AI recognizes that traditional cybersecurity solutions are insufficient for the unique risks and workflows of machine learning. Their mission is to shift security left by building specialized tools for ML developers and operators.

The Need for AI-Specific Security

Machine learning introduces new attack surfaces and vulnerabilities that legacy security vendors aren’t equipped to address. ML pipelines rely on diverse data sources, rapidly evolving open source libraries, and complex model architectures. Once deployed, models become black boxes that are difficult to monitor and test.

As enterprises accelerate their AI adoption, these security gaps become urgent priorities. Protect AI’s research has uncovered rising exploits of ML systems, foreshadowing potential vulnerabilities as adoption increases. Their solutions cover the entire machine learning lifecycle to provide end-to-end protection.

Enabling Secure and Trustworthy ML

Protect AI takes a developer-first approach to ML security. Their initial open source offering, NB Defense, integrates directly into Jupyter Notebooks to provide security scanning without disrupting workflows. It checks for exposed credentials, vulnerable dependencies, and other common risks.

Their upcoming flagship product, AI Radar, delivers robust capabilities for managing and securing ML pipelines. It provides visibility into the entire ML supply chain, an auditable record of ML development, and AI-aware security testing. Together, these solutions aim to help enterprises build trust and confidence in their machine learning applications.

Beyond its technology, Protect AI also leads important community building in this nascent field. Initiatives like provide education and bring together practitioners to advance ML security.

Why We’re Excited About Protect AI

Unsurprisingly, the top reason for our conviction is the amazing team leading Protect AI. Ian Swanson, Co-founder & CEO, is a serial entrepreneur who has assembled a talented team with rare experience in both AI/ML and security. Protect AI is Ian’s third startup, having sold his first company to American Express in 2011 and his second company,, to Oracle in 2018. Most recently, Ian was AWS Worldwide Leader for AI and ML, responsible for all go-to-market efforts across the AWS portfolio.

The other co-founders, Daryan (Global Leader for AI/ML Solution Architects at AWS) and Badar (Head of Engineering at, bring deep technical capabilities in ML. Their recent CISO hire, Diana Kelley, a former cybersecurity executive at Microsoft and IBM, complements the team’s expertise.

Second, the need for a new type of security player and the increasing importance of AI security for CISOs creates a large and opportune market for Protect AI. ML pipelines also incorporate new tools like PyTorch and MLFlow not covered by existing vendors. As a result, CISOs have moved ML Security to a top three budget priority in recent months, which we’ve consistently heard in market research and customer calls. Protect AI’s solutions address the distinct security challenges of ML systems missed by legacy vendors.

And lastly, Protect AI aims to lead the industry in MLSecOps, combining security practices with AI operations. Their end-to-end approach aligns with the need for comprehensive solutions expressed by organizations adopting AI. We believe they have the vision and experience to define leading practices in this emerging category.

Partnering to Define a New Category

As a pioneer in MLSecOps, Protect AI has an enormous opportunity to shape how enterprises secure their AI futures. We believe Ian, Daryan, and Badar have the experience and vision to define leading practices in this space. That’s why we’re excited to partner with them.

At Salesforce Ventures, we look to back companies inventing the future. By integrating security into ML operations, Protect AI unlocks the next generation of trustworthy and ethical AI applications. We can’t wait to see what they build!

Welcome, Runway!

  • Founder: Cristóbal Valenzuela, Anastasis Germanidis, Alejandro Matamala-Ortiz
  • Sector: Artificial Intelligence
  • Location: New York, NY

The Opportunity

When we first met Cris Valenzuela, the co-founder and CEO of Runway, we were immediately captivated by his vision to build a new kind of creative suite. Cris described Runway’s technology in a way that was similar to a new camera, something that could enable a new way of storytelling and creating digital content. We are proud and excited to be investing in a company developing foundational technology that has the potential for new category creation.

Runway was founded in 2018 by Cris, Anastasis, and Alejandro. The initial idea came out of Cris’ thesis project at the Interactive Telecommunications Program at NYU, where he met his co-founders while researching applications of machine learning models for image and video use in the creative domains. Informed by their own experiences as artists, the Runway co-founders set out to answer the question of how a well-built digital tool could simplify the approachability of complex ML models and circumvent the need for deep technical background to give better access to state of the art machine intelligence to artists and designers. The mission of Runway was to democratize access to machine learning so more people can start thinking of new and creative ways to use those models.

The Solution

Runway was first launched in 2019 as a model directory that enabled others to deploy and run open-source machine learning models for a variety of use cases. As the model directory and its user base grew, the team started seeing a usage pattern emerge that led Runway to commit to building more deeply around ML-enabled video editing tools. And staying true to the mission, Runway created tools that require no training to use, unlike many other professional tools in the video editing and visual effects space. Today, Runway is not only a developer of AI-powered editing tools but also text-to-image, video-to-video and text-to-video generation products powered by a set of proprietary state of the art generative models. It provides a full-stack platform from model research to end-user facing applications, which is one of our core theses in partnering with the Runway team.

Since 2020, Runway has invested heavily in foundational research that helps power these tools. Runway Research has co-published, together with LMU Munich, the foundational paper and model “High-Resolution Image Synthesis with Latent Diffusion Models” that gave birth to Latent Diffusion in December 2021 and Stable Diffusion in August 2022. The latest breakthrough by the Runway Research team are two video generation models, “Structure and Content-Guided Video Synthesis with Diffusion Models” also known as Gen-1 (video-to-video, released in March 2023) and Gen-2 (text-/image-/video-to-video, released in early June 2023) that builds on top of Gen-1. Gen-2 is the only commercially available multi-modal AI system that has text-to-video capability today: users can type in text prompts and generate synthesized videos in any style. Users can also use reference or input images and videos to tune the outputs. The videos are not of final production quality yet – as Cris would put it, this is equivalent to when cameras were still in the era of creating black and white photography – but the technology holds significant potential as it moves toward higher fidelity. Runway is continuously training these models in that direction as well. Overall, including these generative tools, Runway has 30+ “AI Magic Tools” that serve different aspects of the creative process.

As we talked with Runway customers, it became clear that Runway, and its users, are continuously innovating in the ways the platform can be used to solve business problems. The most immediate use case is around video editing and visual effects for the creative industries (e.g., film, animation, digital marketing) and marketing functions horizontally. For instance, visual effect editors for the award-winning movie Everything Everywhere All at Once and graphics designers for The Late Show with Stephen Colbert have used Runway to create and edit scenes and videos. Runway has done a great job of organically acquiring users at an incredible speed and converting them into paying customers, which speaks to the potential of its products. 

Why we’re backing Runway

As we look to invest across modalities at the model layer of the AI stack outside of text generation, Runway has the rare combination of a team and products that can completely reinvent the category in which they’re operating in. We have been big fans of Runway’s vision since day one and are impressed by their speed of innovation and shipping new products. Over the course of our meetings, it became clear that Cris, Anastasis and Alejandro are the right leaders to catalyze Runway into a generational company. 

Runway’s products create tangible outputs that demonstrate the creativity and ingenuity of the technology underlying them, which is the foremost reason for our investment. While the AI-powered editing tools can apply the necessary editorial steps in the matter of a couple clicks, the true piece of revolutionary technology is its video generation capability and Runway is likely the leading company in the world today in building this capability. Its Gen-1 and Gen-2 models can support high-quality artistic and stylized text-, image-, and video-to-video generation that can replace manual creative work. The company is also actively and quickly innovating to make the models more powerful and to move toward higher fidelity videos that can be more photorealistic or follow a certain style better if needed. As we saw with ChatGPT, a powerful and easy-to-use product can go viral quickly. We think Runway’s products are showing signs of that kind of virality. The speed of innovation and shipping products is also a key part of their success, which we are seeing with the cadence of product and research releases in recent months.

Runway has an amazing founding team that is product obsessed and understands the need to innovate and build quickly. Cris is highly focused on building great products. His vision is to continuously build better and better products that will sell themselves. Anastasis (co-founder and CTO) complements Cris’ product acumen with his technical background. He was a computer vision researcher at IBM Research and is one of the co-authors behind Gen-1 and Gen-2. Lastly, Alejandro (co-founder and Chief Design Officer) completes the founding team with his experience in design. He was previously a research resident at NYU and co-founded Material, a graphic design studio, and Ediciones DAGA, an independent art book publishing house. The team understands the need for speed and building on existing research to push the boundaries of what Runway’s products can do to really capture this market. They have already built so much with a relatively small team that is just getting to ~50 people today. Cris and his team have also referenced incredibly well among investors and other leading entrepreneurs within the Salesforce Ventures portfolio. 

Runway also services a large addressable market that will only expand as Runway’s products get better. Given the nascency of this new category of content creation and the breadth of use cases Runway touches and has the potential to address, the company’s addressable market is evolving. But we know that directionally and intuitively, the market is big. Runway sits at the intersection of content editing and visual effects, both of which are multi-billion dollar software markets. Given the large percentage of individual creators, the company has mostly attracted “prosumers” so far, but we are beginning to see enterprise traction and that is an area we are super excited about. 

What’s ahead?

The realm of human creativity is continuously evolving and adapting to new technology. When photography was invented, it gave voice to artists who didn’t have the upbringing to enroll in art schools. Similarly, video art in the 1960s allowed more female artists to become vanguards of artistic expression in America. In today’s world, the format of video is drastically becoming one of the most popular forms of digital content being consumed globally, and everyone can be a creator. As other modalities are seeing generative capabilities of artificial intelligence seeping through, video is due for an upgrade as well. Runway’s approach to make AI available in the hands of all creators is a very exciting mission, and one we are proud to support.

Welcome to Salesforce Ventures, Runway!

Welcome, Mnemonic!

  • Founders: Andrii Yasinetsky, Elena Ikonomovska, Ben Metcalfe
  • Sector: Web3, Data and Analytics
  • Location: San Francisco, CA

The Opportunity

Mnemonic is solving the unique and increasingly complex challenges of NFT data by building a data and analytics platform to enable developers and business users to derive insights from their data. They serve brands, builders, and enterprises creating experiences in Web3 with APIs that bring rich Web3 analytics, audience insights, and customizable audience segmentation abilities.

The Solution 

NFTs enable the tokenization of everything in both the physical and digital world with the opportunity to reflect provenance, ownership, valuation, and other characteristics. This data can then be used to enrich existing data sets – for example, by unifying Web3 and Web2 identities to build a full customer picture of an individual. However, the complexities of the web3 ecosystem require bespoke solutions that help enterprises of all sizes not only access relevant data but also turn it into actionable insights that fulfill their objectives and enable them to build personalized, memorable, and safe products and experiences in Web3. Mnemonic solves this by live indexing on-chain data to real-time product data to provide a highly available and reliable platform built for enterprises. Mnemonic’s B2B API platform provides instant access to NFT data, collection analytics and insights into billions of transactions. The platform enables developers to power Web3 experiences at scale, including Web3 wallets, social media, analytics tools, and Web3 marketing platforms. 

Why we’re backing Mnemonic 

At Salesforce Ventures, we have seen enterprises increasingly exploring and requesting services to facilitate Web 3.0 strategies. We see the business use cases around NFTs rapidly evolving. One example is brands exploring how a commerce site may distribute NFTs. The brand can then  target the community of NFT holders to create personalized, omnichannel experiences that drive greater customer engagement and long-term customer relationships. Mnemonic supports this by providing powerful audience insights and wallet segmentation capabilities to fully understand the performance of a collection, the behavior of its holders and identify new opportunities to reach and engage with new audiences. The platform also enables creators and brands to better analyze and understand their fans by gaining insight into the collection owners, with the opportunity to drive better engagement with fans. 

In supporting Mnemonic, we are also partnering with exceptional co-founders Andrii Yasinetsky and Elena Ikonomovska. The team has decades of experience building large-scale infrastructure, data science, machine learning, and big data applications. Andrii and Elena combine excellent technical backgrounds (from companies including Uber, Google, and Reddit) with a visionary understanding of the powerful potential of Web3. 

We see a huge opportunity for companies building the infrastructure and applications that will enable broader adoption of blockchain technology. Mnemonic’s data and analytics platform solves the complex challenges of NFT data and enables customers to quickly benefit from powerful analytics and intelligence capabilities across Web3. We are excited to invest in best-in-class companies building enterprise solutions in Web3, and playing a key role in supporting partners in the ecosystem. Indeed, Mnemonic was most recently announced as an official launch partner for Base, Coinbase’s L2 scaling solution, in addition to their existing partnerships with leading Web3 players including Polygon.

What’s Ahead 

This is just the start – we are only in the earliest innings of exploring the full utility of Web3 technology. Traditional enterprises and brands are increasingly engaging with NFT strategies and exploring use cases that include digital twins, metaverse commerce, supply chain inventory, provenance as well as advertising and marketing. Salesforce Ventures is excited about the potential for NFTs and wallet analytics to allow for unique engagement between enterprises and their customers with enriched customer profiles and real-time insights into new audiences. Mnemonic is building a platform that is playing a key role in enabling enterprises and brands to derive value from their Web3 strategy.

Welcome, Cohere!

  • Founders: Aidan Gomez, Nick Frosst, Ivan Zhang
  • Sector: Artificial Intelligence
  • Location: Toronto, Canada

The Cohere Vision

The invention of the Transformer models at Google Brain in 2017 was a revolutionary breakthrough that spread across Google’s product portfolio. The new model architecture was introduced in the paper, Attention is All You Need, which pioneered a new approach to neural network NLP that captured the context and meaning of words more accurately than previous NLP models, and serves as the underpinning of language models today. Aidan Gomez, the CEO and Co-Founder of Cohere, was a research intern at Google Brain at the time and one of the co-authors of the Transformer paper. Two years later, the impact and benefit of the Transformer model still hadn’t widely caught on outside of Google. As a result, Aidan, along with his co-founders Nick Frosst (who collaborated with Geoffrey Hinton, becoming Hinton’s first employee at Google Brain’s Toronto lab) and Ivan Zhang (who worked alongside Gomez at, an independent research group), founded Cohere in early 2019 to bring “Google-quality AI to the masses.” Fast forward to today, and they have successfully done that with a clear vision to build the leading AI platform for enterprises, offering data-secure deployment options in companies’ existing cloud environments, customization, and customer support.

Instead of focusing on artificial general intelligence (“AGI”) or creating large language models (“LLMs”) with the highest number of parameters, Cohere has chosen to focus on building a generative AI platform for enterprises that is easy to access, customizable, and secure. Cohere’s AI platform can be trained or finetuned for specific use cases that are most relevant to customers including writing content, building conversational chatbots, aggregating customer feedback and analyzing sentiments, and content moderation. Cohere has already found notable applications with leading companies including Jasper and Hyperwrite, for copywriting generation tasks such as creating marketing content, drafting emails, or developing product descriptions, and LivePerson, who Cohere is partnering with to deliver custom LLMs for customer engagement and turn conversations into live actions.

While its existing AI suite encompasses a significant amount of enterprise use cases today, Cohere continues to layer on more advanced capabilities. The company is working on retrieval-augmentation to ensure generation remains grounded in facts and action-based models that can interface with and drive external systems, allowing agents to take actions and drive processes. These models have the potential for higher quality automation and more complex workflows that customers can utilize.

The focus on being enterprise-facing has always been a part of Cohere’s DNA and instilled in the company a continuous desire to prioritize security and privacy. The platform is built to be available on every cloud provider — deployed inside a customers’ existing cloud environment, virtual private cloud (VPC), or even on-site — to meet companies where their data is. This is oftentimes a significant hurdle for customers and Cohere addresses it head-on. The company’s vision is always to push for better and safer models that customers can easily use while putting a premium on privacy and data protection.

Why we’re backing Cohere

We are eager to invest across the AI stack from the foundational AI layer, to tooling that helps companies train, finetune and deploy models, to applications that have unique data or distribution moats. The foundational layer is an area where we see significant value accruing and Cohere is one of the key players.

Many founders building at this foundational layer come from specific academic backgrounds given the deep technical know-how required for research and development, which often means they don’t have as much experience with GTM and business building. That was why when we first met Aidan and his co-founders, we were surprised to find how incredibly sophisticated and mature the team already is at speaking the language of their customers and having a clear vision for GTM. Over the course of our diligence, we further built conviction on the technical and commercial potential of the business, as well as a level of trust and confidence in Aidan and the leadership team he has gathered at Cohere’s helm. We believe Cohere is one of very few leading foundational model players that can capitalize on the generative AI paradigm shift. Cohere is one of the first few investments we made from the new $250 million Generative AI fund Salesforce Ventures launched in March 2023. Its distinctive enterprise-focused approach aligns with our own mission and values – we are excited to partner with Cohere and strengthen the relationship between our two companies.

Cohere is uniquely poised to capture the enterprise AI market: the company has industry-leading foundational AI, has remained independent and cloud agnostic, ensures data security for its customers, and is backed by a top-tier team that has both strong technical background and enterprise experience. Customers have consistently referred to Cohere as one of the most advanced AI providers in the world. Meanwhile, while academic benchmarks have their limitations, the Stanford HELM results (as of June 2023) indicate that Cohere is currently leading the pack in accuracy and fairness. Cohere also recently released the first-ever publicly available multilingual understanding model trained on authentic data from native speakers – it is equipped to read and understand over 100 of the world’s most commonly spoken languages. 

Cohere’s technical prowess comes from and is supported by a deep bench of great hires. Despite the intense competition for talent in AI/ML, Aidan and his founding team have successfully attracted well-known researchers in the NLP space, including Phil Blunsom (Chief Scientist at Cohere), who led DeepMind’s Natural Language team for 7 years (2014-2022) and has been a professor of computer science at Oxford since 2009, as well as Nils Reimers (Director of Machine Learning at Cohere), who built one of the most popular open source models (SBERT) and brings significant experience in embedding. Both the Chief Product Officer, Jaron Waldman, and SVP of Engineering, Saurabh Baji, have years of experience building products for enterprise use cases from their time at Apple and AWS, respectively. Jaron himself was a two-time founder who has built amazing products and successfully sold his startups to Apple and Rakuten.

On top of that, Cohere has demonstrated early GTM maturity with a laser focus on serving enterprise customers. Cohere has shown a clear and thorough understanding of how to drive GTM strategy in this space and create value for enterprise customers. The company is highly focused on building deep partnerships with a select group of enterprise businesses to drive the flywheel effect of selling to their downstream customers. Cohere can create custom models and provide custom re-training to really hone in on what these enterprise customers need. It built out capabilities for AWS Sagemaker and VPC or on-prem deployments early on, which is something that these customers look for right away. Additionally, the GTM team is led by a veteran experienced in selling into the enterprise market: Martin Kon, President & COO at Cohere, who was formerly Youtube’s CFO and a senior partner at BCG. As a result, Cohere’s keen focus on building customer-facing products has also allowed it to be more capital efficient with training and hosting models.

What’s ahead?

As we had mentioned in a previous investment blog, we believe we are at the beginning of the generative AI revolution, and we are still at the very first inning of putting AI into production for enterprise use cases. As customers become more and more sophisticated in choosing the right AI partners, the developers of AI are also constantly pushing the boundaries of what models can do and striving to build something that is better, faster and more powerful. Cohere is one of the companies innovating at the frontier and is well set up in this environment with the right team and right focus. We are beyond excited to be investing in this team and helping them accelerate the development of Cohere’s world-class AI platform and empower enterprises around the world to build incredible products.

Welcome to Salesforce Ventures, Cohere!

Welcome, Anthropic!

The Anthropic Vision

The advancements in foundational models over the last couple of years have precipitated a paradigm shift in how everyone uses, thinks about, and builds technology. While the landscape of AI research is ever-changing, an increasing area of focus that has persisted since day one is the safe and reliable use of AI systems. This has only received more attention in recent months as technologists, industry luminaries, and governments from all around the world came out to debate the potential benefits and harms AI can exact on humanity and the right framework for implementing regulation.

Anthropic is at the forefront of innovation driving this paradigm shift and has preempted this debate since 2019 when its founding team left OpenAI to make a concentrated bet on AI safety. Anthropic is founded by Dario Amodei (previously VP of Research at OpenAI), his sister, Daniela Amodei (previously VP of Safety and Policy at OpenAI), and a team of amazing former OpenAI researchers. Since its founding, the team has trained one of the most capable large language models (“LLM”) in the world today, called Claude. Claude is a general purpose model that excels at a wide range of tasks from sophisticated dialogue and creative content generation to Q&A, coding, detailed instruction following and reasoning. Recently, Anthropic released a lighter, less expensive, and much faster option called Claude Instant, which can handle similar tasks such as casual dialogue, text analysis, summarization, and document question-answering. Customers can request access to Claude and Claude Instant via API and try Claude in Slack.

Claude is based on Anthropic’s research breakthrough in Constitutional AI, which is a unique approach the company is taking toward AI safety. As AI systems become more capable, they can supervise other AI systems with self-critique and self-revision – the only human oversight is a predetermined set of principles. Claude was trained using Constitutional AI to promote the principles of helpfulness, harmlessness, and honesty in its outputs and prevent misuse or harmful and undesirable behaviors. Because of the self-improvement aspect of Constitutional AI, it also allows Anthropic to improve model safety without sacrificing model performance. Claude can take a limited amount of the highest-quality human feedback, create synthetic data modeled off this feedback, and train itself on this data. This allows Anthropic to provide increased transparency and steerability while still maintaining high degrees of natural language fluency.  

Beyond its focus on AI safety and the high quality of its models, Anthropic is also winning enterprise customers’ mindshare with an increasing emphasis on customization, which will drive long-term defensibility. It enables customization through a few different areas, such as incorporating a customer’s expert human-labeled feedback to the model, making it better at specific tasks, or working with the customer to create a “constitution” that is based on values and branding of the company to shape overall behavior of the model.

Why we’re backing Anthropic

Claude’s capabilities and Dario’s long-term vision for the company quickly captivated us. As we spent more time with the Anthropic team, it was clear that Anthropic and Salesforce share a clear vision for creating innovative technology that is rooted in safety. We built strong conviction that Anthropic is one of very few foundational model players that have built the right technology and have the right team to capitalize on this paradigm shift. Anthropic is one of the first investments we made out of the new $250 million Generative AI fund Salesforce Ventures launched in March 2023. We are excited to partner with Anthropic and strengthen the relationship between our two companies. 

As we look at the AI tech stack, we believe value will accrue in the AI tech stack at the core foundational model layer. Anthropic is one of a few companies operating at this layer that has built technological differentiation and is well-positioned to maintain its lead. The technical know-how needed to train foundational models to a highly performative state is rare, and the capital needed to purchase compute for model training and hosting creates a natural barrier that prevents heavy proliferation. While the open-source side of the AI community has made more progress recently, there are still meaningful questions around safety of use and a clear and significant gap between the performance of open-source and closed-source models in production. Anthropic’s models are viewed as some of the best in the world by customers, developers, and academic institutions. The important research the Anthropic team has published around Constitutional AI, reinforcement learning from human feedback (“RLHF”), and others also indicate that it has the technical capabilities today to compete with others. Both open and closed source will continue to evolve, and there will be demand for both types of models – the future will be hybrid. In the meantime, Anthropic is well positioned to support growth and push forward the next generation of Claude.

On top of that, Anthropic has an A+ team with an incredibly strong research background. Anthropic is led by the former head of research at OpenAI, Dario Amodei, who spearheaded the GPT-2 and GPT-3 projects. The rest of the founding team and technical leadership come from OpenAI, Google Brain, and Baidu (leaders in AI research who co-authored the papers at OpenAI). One of the members of the founding and leadership team is Jared Kaplan, a theoretical physicist by training who taught at Johns Hopkins for over 10 years. Jared was a research consultant at OpenAI and developed the alignment model that is essential to Constitutional AI and Claude. A specialized research background is required to maintain a technical advantage and truly compete in a fast moving environment where new model developments are happening weekly if not daily. The gravitas and mindshare Anthropic holds in the research community also helps them attract the right talent in an arena where competition for talent is becoming more intense. 

Constitutional AI remains a key differentiator and aligns well with Salesforce values. Anthropic’s research team pioneered the concept of Constitutional AI which enables models to be trained with a set of constraints designed to promote helpfulness, harmlessness, and honesty. This approach and its continuous focus on safe AI aligns well with Salesforce’s vision for trusted generative AI and is a key differentiator as AI safety is always top of mind for Salesforce and its customers. 

What’s ahead?

We are in the first inning of generative AI adoption. A new survey of more than 500 senior IT leaders conducted by Salesforce reveals that 67% are prioritizing generative AI for their businesses within the next 18 months, with one-third naming it as a top priority. Most of them believe that generative AI is a “game changer,” and the technology has the potential to help them better serve their customers, take advantage of data, and operate more efficiently. As the survey results suggest, enterprise usage of AI systems will continue to grow, and customers will only become more mature and sophisticated in evaluating AI technology. Concurrently, regulatory changes are inevitable and will help create a structure for AI system deployments. Anthropic is well positioned to address any challenges coming out of this environment, and we expect Claude to become one of the go-to LLM partners for customers. 

Welcome to Salesforce Ventures, Anthropic!

Salesforce Ventures Launches $250M Generative AI Fund

We’re thrilled to announce the launch of our new $250 million generative AI fund to bolster the startup ecosystem and spark the development of responsible generative AI. 

Learn more about it from our team and companies within the fund here.

Welcome, WeaveGrid!

The Opportunity

A decade ago, decarbonizing the transportation sector was a daunting task, but the landscape has drastically changed, and today the electric vehicle (EV) era has officially arrived. Estimates suggest that over 25% of all cars on the road will be EVs by 2030, and auto manufacturers have committed $200B in investments towards transitioning their new fleets to be at least 50% electric over the next eight years. The rise in EV production is driven both by booming consumer demand in recent years and policy and regulation at the federal and state level. The Inflation Reduction Act (”IRA“) is monumental legislation that provides increased and lasting incentives for consumers across income levels to choose EVs over fuel combustion vehicles. It also increases incentives for automakers to produce more EVs and further invest in their deep supply chains. We also see states like California passing regulation mandating that all new car sales must be fully electric by 2035. While the new opportunity for automakers is exciting, they are increasingly mindful of ensuring their consumers have the best possible experience. One pain point unique to EVs for consumers is their well-documented “range anxiety” and worry about when to optimally charge their EVs. 

With the accelerating transition to EVs also comes a critical problem for utilities: how to manage the power grid to support the increased load demand from charging EVs. To address this challenge, utilities will need to make significant upgrades in grid infrastructure and invest in software solutions to complement their capital expenditures.    

The Solution

WeaveGrid directly solves the problems facing utilities, automakers, and consumers with the rise in EVs. Their product connects EVs to the grid in an autonomous way, leveraging the best rates for charging while mitigating overload risks to the grid. From the utilities’ perspective, WeaveGrid enables them to understand how EVs are operating on the grid (when they are charging, when they are in motion, etc.), manage the load so that EVs do not overwhelm electricity capacity, and dictate when cars should be charging, all while ensuring that the car owners are meeting their own charge requirements to operate their vehicles. Optimizing the grid also has a significant impact on how clean the energy sources to the grid are and allows utilities to minimize the need to turn on peaker plants, which emit disproportionately high levels of pollutants and are also the most expensive sources of energy. For resource-constrained utilities, WeaveGrid provides measurable ROI, significantly reducing the costs of managing EVs on the grid by 70% annually.  

For automakers who have committed billions in capital to electrifying their vehicle offerings, WeaveGrid helps ensure the electric grid can serve the millions of new EV drivers entering the scene. Automakers are taking a hands-on approach to helping first-time EV drivers understand the charging experience. By improving the driver experience around home charging and building WeaveGrid into their increasingly sophisticated tech stacks, automakers are also delivering ROI in software-defined vehicles as part of their ambitions to diversify revenues into software and services. 

For consumers, WeaveGrid provides a seamless experience for EV owners to charge their vehicles in the most optimal way, regardless of where they are. With 80% of charging happening at home, WeaveGrid’s solution provides utility cost transparency and savings recommendations to help consumers validate the switch to electric. The WeaveGrid solution is cost-effective and reduces range anxiety for drivers. WeaveGrid’s platform is also incredibly easy for consumers to use; the platform prompts the owner to set their personal charging requirements and goals, and then enables WeaveGrid to manage the right time to charge at the lowest possible prices. This seamless integration between the vehicle and the grid signifies a first-of-its-kind relationship between the EV owner, their vehicle, and the grid. 

Why we’re backing WeaveGrid

WeaveGrid is the first investment that the Salesforce Ventures Impact Fund has led, owing to our strong conviction that WeaveGrid is a category-leading company building the future of climate technology. In the time that we spent getting to know the market, the business, and the team, we reinforced our thesis that WeaveGrid is uniquely positioned to execute on sectoral tailwinds to capture a very large market opportunity and meaningfully decarbonize the transportation and energy sectors. 

Co-Founders Apoorv Bhargava (CEO) and John Taggart (CTO) both bring highly relevant experience to a business that operates at the intersection of utilities and automakers. Apoorv has spent his entire career working in the energy sector, deploying utility grid management programs at both NRG and Opower. John brings deep technical auto experience and is a leading expert in EVs and their impact on the grid from his time working in Tesla’s Office of the CTO and on the Special Projects team at Nissan leading product innovation. Together, they have the combined skill set to build a sophisticated technology stack that sits at the intersection of two rapidly transforming industries. 

And the proof points are compelling: WeaveGrid operates in thirteen states and serves leading U.S. utilities, including Pacific Gas and Electric Company (PG&E), Exelon Utilities, and Xcel Energy. WeaveGrid’s PG&E launch is especially significant; among all US utilities, PG&E hosts the most EVs on its grid, with one in six EVs in the U.S. registered in their service area. WeaveGrid has also partnered with many of the key automakers. As WeaveGrid’s utility and auto network continue to grow, more and more U.S. customers will have access to their product to optimize charging.

What’s ahead?

As automakers accelerate EV production, and as grid management continues to be a critical pain point for utilities, both industries need agile solutions to help mitigate costs and enable the shift to electrification. WeaveGrid is at an exciting moment to be the leading software company enabling this transition.

With almost 25% of all GHG emissions in the U.S. coming from transportation, shifting to electric vehicles is imperative to meeting our country’s goal of reducing overall emissions by 50% by 2030. We see WeaveGrid as a critical piece of this puzzle with its innovative software solution for both utilities and automakers. 

Please join us in welcoming WeaveGrid to Salesforce Ventures!

Transforming Tomorrow: The Business of Belonging with Jasmine Shells of Five to Nine

Employees who work after-hours to build community at their jobs are greatly appreciated by their peers, but rarely well-rewarded by their employers. That’s about to change.

By now we’ve all seen research showing the value of diverse teams. Organizations across the country have been making strides toward recruiting from a broader pool of talent. More recently, business leaders have focused on retention as they learned about the importance of feeling welcome at work. From The Great Resignation to The Quiet Quit, we’re witnessing a broad rejection of old corporate culture rules and a movement toward helping employees feel more deeply connected to their colleagues about things that personally matter to them. 

“Over the past few years, we saw different trends or shifts that put leverage into employees’ hands. Employees are advocating for a workplace where they belong. It’s not just ‘We pay top dollar and have the best benefits,’ because everyone can do that,” says Jasmine Shells, Co-founder and CEO of Five to Nine. “How are you going to create a best-in-class, winning, and inclusive workplace? How do you create opportunities to connect in a hybrid world?”

“Your nine-to-five only describes a portion of who you are; we also want to know who you are outside of work. Your five-to-nine is what you want to accomplish and who you are and what you value and want to dedicate your time to.” 

— Jasmine Shells, Co-founder and CEO, Five to Nine

Deloitte found that when employees feel like they belong, companies see a 56% increase in job performance, a 167% increase in employer net promoter score, a 50% reduction in turnover, and a 75% decrease in sick days. In a 2021 article, a group of analysts at McKinsey concluded that when employees feel their personal purpose is aligned with their company’s purpose, they are more engaged and loyal. As we wrote in our Cloud 100 coverage earlier this month, we are seeing more and more CEOs of fast-growing companies attribute a significant amount of their success and competitive advantage to the strength of their culture and community.

And yet, the work of community building, which can include building affinity groups, leading Employee Resource Groups (ERGs), connecting people through a shared sense of purpose, and generally bringing people together, is often unpaid, under-resourced and under-recognized. “More than 90% of Fortune 100 companies have ERGs, but fewer than 10% of those have any way to measure impact,” says Shells. “Companies are spending thousands to millions on programming and typically have no way of measuring their impact on culture, inclusion, and the business.”

Chicago-based Five to Nine aims to solve these and other problems with its event management software for the workplace. The company offers multiple tools to help your company build, manage and measure events, communities, and their outcomes. Five to Nine offers templated event landing pages, as well as contact and guest list trackers. The software is integrated with communication tools from Google, Outlook and Slack, among others, so it’s easy to reach out to employees wherever they already are. Five to Nine makes it easy to send surveys, run analytics on who did and didn’t show up, and compute net promoter scores. 

One customer told Shells that when her boss asked for a year-end report on all of her ERG-related activities, she previously threw together an incomplete document based on memory. But after getting Five to Nine, she was able to easily work up a detailed progress report, including data and feedback to support the assertion that ERG programs were increasing employee retention for participants. Her boss was so impressed that she got a promotion. 

“We care a lot about eradicating the diversity tax,” says Shells. “ERG leaders are spending 15-40 hours monthly outside their jobs helping to retain the best talent, but they aren’t getting paid or being recognized. When there is no data, there is no review.”

Five to Nine was born from personal frustration. After college, Shells worked as an IT consultant and spent the majority of her time on the road. She enjoyed the perks, but also felt lonely and disconnected. One day, her mother told her that she had the power to do something about it. She reminded her that when her mother would take her shopping as a little girl, Shells wouldn’t leave until she had chatted up everyone in the grocery store. “That conversation helped me realize that my nine-to-five and my five-to-nine don’t have to be exclusive,” says Shells. 

Soon after that call with her mother, Shells started taking steps to create a mentorship program for employees at her firm, as well as a Black Professional Network group. Once she began rolling out those programs, she realized how difficult it was to plan events, boost engagement, and determine impact. She was juggling emails, spreadsheets and design software, among other things, but struggled to keep it all together and wondered if there might be a way to streamline the whole process. 

Helping community builders become more efficient is the first step toward a bigger vision. Shells wants to launch a movement that will expand communities, increase diversity, and elevate the role to reflect its growing importance. The company hosts an annual event for its burgeoning community of community builders to network with one another and share ideas. The most recent event in January attracted more than 1,500 people from all over the country. “We started with a best-in-class product. Next up is sharing best practices and trends in the market,” says Shells. “We’re creating a category.”

Welcome, Balance!

The Problem

We’ve all experienced the magic of the easy eCommerce purchase experience – whether that’s guilty pleasures bought off Instagram or buying your basics on Amazon.

But if you’re a business, the experience remains totally different, even in 2022. Say you’re buying industrial chemicals or restaurant supplies, what is your experience like? Answer: phone calls back and forth with suppliers, handling invoices, dealing with wonky ACH transfers or giving credit card details over the phone and sometimes even a fax machine gets involved!

Further complicating matters, businesses are looking to buy from their suppliers on “net terms” – i.e., telling the supplier: “I’m a creditworthy business – you can trust me and we’ll settle the invoice in 30 to 90 days.” In fact, 70% of B2B transactions are done on net terms. But offering net terms means the supplier must understand the credit risk of the buyer and only collects the cash later. This burdens suppliers with the processes of underwriting credit risk and chasing collections, all while tying up their cash in working capital. Balance is solving the complexity of the B2B payment experience – bringing Stripe-like simplicity to B2B trade.

What’s Changing Now?

The B2B commerce market is over $120 trillion, ~5x the size of the B2C market. Yet it is far less digitized with only ~7% of B2B sales done through eCommerce vs. ~19% of B2C sales. This is changing now for three reasons:

  • the pandemic forced B2B buyers and sellers to use digital channels because they could not physically sell in-person, e.g. trade shows 
  • B2B sellers realized that they can make big efficiency gains by offering digital, self-service ways to buy, reducing overhead tied up in manual, paper-based processes
  • the rise of e-commerce in retail trade is seeping into the B2B mentality.
  • Thanks to these changes, McKinsey finds that now B2B sellers are offering ecommerce buying channels more frequently than in-person selling for the first time.

Alongside the changing habits in B2B trade, we are seeing the rise of B2B marketplaces with their sales growing over 130% in 2021 to $56B. Marketplaces have emerged as a more efficient way to match buyer and seller demand. 

Serving this rising landscape of digital B2B commerce and marketplaces, while catering to the complexity of B2B trade, demands new infrastructure. That’s where Balance’s solution for B2B payments comes in.

Balance’s Solution

Balance offers an end-to-end platform for B2B payments with a modern, API-first approach. This caters to all the particularities of B2B payments, including cards, wires, ACH, checks, installment and milestone-based payments. Importantly, Balance has a fully integrated net terms offering that allows businesses of all sizes to get paid upfront while offering 30-90 day terms to their customers – instantly. This is underpinned by a robust credit underwriting approach that best suits the counterparties of each client or marketplace.

Importantly, with Balance’s best-in-class, developer-friendly API infrastructure, it’s as easy to implement Balance into an eCommerce experience or B2B marketplace as it is with Stripe.

Why We’re Backing Balance

We are excited about the size of the opportunity, the secular tailwinds, the quality of the product, but most importantly, the Balance team. Bar and Yoni, Balance’s co-founders are driven but humble, kind leaders. They met while working together at PayPal and have deep expertise in payments, risk and data. We believe they are building an attractive organization with a compelling vision of the future of B2B trade. In fact, one customer told us that if they had a friend looking for a job in fintech, he’d recommend they go work for Balance – quite an endorsement.

Balance is emerging as a market leader in B2B payments, winning praise from dozens of blue-chip clients and on track to process hundreds of millions in payment volumes in less than a year from launch. 

Our support of Balance aligns with Salesforce Ventures’ belief in the ongoing modernisation of payments infrastructure, alongside our investments in Modern Treasury, Stripe, Flutterwave, GoCardless, Razorpay and more. Further, we are backers of the enablers of the rise of eCommerce such as Vercel, Contentful, Bringg, Stord and Forter, and we believe Balance is bringing the same innovation to B2B commerce.

What’s Ahead?

We are just at the beginning of the digitization of the huge B2B trade market. And we believe that a dedicated payments infrastructure, that brings consumer-grade experience to B2B commerce and is tailored to the specific needs of B2B trade, is needed to power this change. Balance is the stand-out leader in this space on team, product and traction. We’re excited to support the next phase of their journey. 

We hope you will join us in welcoming Balance to Salesforce Ventures!

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