Welcome, Second Front!

• CEO: Tyler Sweatt 
• Sector: Cybersecurity & Infrastructure, GovTech
• Location: Washington, D.C.

The Opportunity

For years, we’ve heard from portfolio companies and the broader Salesforce ecosystem about the challenges of selling and deploying software into all federal government levels – from civilian agencies to the Department of Defense (DoD) to the intelligence community. Companies today spend millions for custom security and compliance configuration over multiple years to reach the necessary accreditation, not to mention the continuous re-accreditation process that’s often required. 

We’re still in the federal government’s early innings of cloud software adoption (just ~15% of the $100B+ gross technology spend this past year). Government agencies have begun embracing a software-centric future by increasingly buying commercial solutions at the “speed of relevance” vs. building in-house. The past few years have been a turning point for this movement, as federal agencies have begun dedicating budgets and even entire offices (e.g. the DIU, NavalX, Kessel Run) towards streamlining the procurement process for best-in-class cloud software vendors. With the foundation laid, the next five years are ripe for the proliferation of next-generation commercial software within the federal government.

The Solution

Second Front is a critical bridge to accelerating the delivery of mission-critical software solutions to government agencies. The company’s Game Warden product is a DevSecOps platform that abstracts the security and compliance requirements (i.e. the DoD’s Authority to Operate, or ATO) necessary to win and deploy into government end-customers. 

Getting started on Game Warden can be as simple as pushing a container image to the platform, which then automatically identifies and helps resolve the vulnerabilities and controls necessary for deployment. Game Warden’s CI/CD pipeline is tightly integrated with core infrastructure like GitLab, Chainguard, and Grafana to streamline the process further. Pushing product updates, which previously required lengthy and costly manual re-review, is also seamless.

Second Front saves customers millions in consulting fees and has reduced the software adoption process from years to weeks. Second Front’s customers range from the largest enterprise SaaS companies globally to emerging companies breaking into the defense market for the first time. Similar to how our portfolio company, Drata, unlocked the enterprise market for thousands of software vendors via SOC II automation, Second Front has transformative capabilities for the government and every vendor looking to do business with it.

Why We’re Backing Second Front

We’re investing in Second Front because we believe they’re poised to become the default technical rails that enable thousands of commercial software vendors to capture their share of the $100B+ public sector software market. These rails allow real-time, secure collaboration between government agencies and cutting-edge software companies, breaking down barriers between the best technologies and the most pressing pain points. 

Tyler and his entire team bring a rare combination of expertise across the highest levels of military, civilian government, and Silicon Valley – including the former digital transformation leaders in both the U.S. Navy and U.S. Air Force, Chief Data Scientist of the CIA, CISO for the Director of National Intelligence, and veterans of major service branches. This experience means Second Front possesses a firsthand understanding of the pain points in government software acquisition. As such, few are better positioned to be trusted partners to commercial software vendors and government agencies.

What’s more, Second Front has incredible synergy with the broader Salesforce Ventures portfolio. Game Warden is poised to become the de facto integration layer that our broader arsenal of application and cloud security tools can plug into to further protect software from threats and vulnerabilities. The platform’s centralized monitoring and compliance capabilities help ensure data integrity across the modern data stack. We’re also thrilled to be the first champions of the platform for any software company in our ecosystem serving the public sector.

What’s Ahead

We’re looking forward to the next phase of growth as Second Front brings a world-class suite of software tools to public sector agencies across Australia and NATO, along with a host of regulated industries that value Second Front’s security and compliance controls. We share the team’s vision of providing a single, unified design pattern for software deployment in any government network or commercially regulated environment globally. We’re particularly excited by the opportunities the broader Salesforce ecosystem can bring to Second Front. 

Getting to know Tyler and the team over the past several quarters has been an incredible journey. When we attended Second Front’s annual conference, Offset Symposium, we not only heard glowing feedback from customers and partners but also appreciated the unique community of technology and government leaders this ‘n of 1’ team has cultivated. We broke bread with Tyler, Sam, Enrique, and others on the team across California and Virginia, where we aligned around shared values of building a generational company while strengthening our national institutions. It’s a privilege to be partners for the years ahead as we lead their $70M Series C alongside new investor Battery Ventures and existing investors NEA, Moore Capital Management, and Artis Ventures.

Onwards and upwards. Welcome to Salesforce Ventures, Second Front!

Welcome, Odigos!

• Founder: Eden Federman, Ari Recht
• Sector: Infrastructure
• Location: Tel Aviv, Israel

The Opportunity

In today’s world, software performance *is* the business – if your software’s not running, you’re not in business. As such, observability – the monitoring and troubleshooting of software performance – is a mission-critical component of every enterprise’s technology stack. Enterprises today spend 20-30% of their IT budgets on observability, but they’re being poorly served by these dollars in three critical ways. 

First, enterprises have trouble getting rich tracing data on all their applications for complete observability. Traces provide an end-to-end view of the flow of requests as they traverse components of a system. They sit alongside logs and metrics as a key pillar of monitoring. As software has shifted to a cloud-native architecture, traces have become the most important telemetry type (debugging based on logs and metrics alone does not scale well over multiple microservices, leading to longer times to resolve incidents). 

But traces are very hard to collect because they require manual changes to the code to instrument it to emit telemetry. Code changes are a burden on engineering teams and risk introducing errors. Automatic instrumentation, which should relieve developers of manual changes, slows down application performance, cannot be applied to all code languages, and does not always collect the deepest insights. As a result, teams are missing this critical end-to-end view.

Second, enterprises are overwhelmed by volumes of noisy data that make it difficult to discover meaningful signals. This data surge is partially driven by an attempt to compensate for lack of traces with more and more logs. In a study by Chronosphere, 69% of observability professionals reported that data is growing at a “concerning rate” and in order to reduce it, they’re often limiting the applications observed or the monitored metrics. Meanwhile, data growth is not getting us closer to true observability — in a survey by Elastic, only 10% of professionals report being able to identify the root cause of an issue. The upshot is enterprises are missing key data and drowning in it.

Third, enterprises face spiraling costs driven by escalating data volumes and vendor lock-in. Observability costs are regularly in the tens of millions because they’re driven by the amount of data collected, analyzed, and stored — which so far has only gone in one direction. Further, the underlying collection of telemetry data is done by proprietary vendor agents which are inserted into your code. The collected data is emitted in closed vendor formats, compatible only with their tools. 

To fight back against these costly, closed systems, there is a transformational movement underway to converge on open standards like OpenTelemetry. However, this is not an easy shift. While 87% of respondents to the Elastic survey agree that OpenTelemetry will be the standard for observability data within the next 5 years, only 9% of teams have moved it to production thus far. OpenTelemetry instrumentation is difficult and requires hundreds of engineering hours to implement; expertise in the technology is rare. Incumbent monitoring vendors certainly have little incentive to help customers as the move to OpenTelemetry reduces their lock-in power. Enterprises are stuck.

The Solution

Odigos offers an observability solution that gets to the root of these data and cost issues. Odigos uses a powerful combination of eBPF technology and OpenTelemetry to instrument applications to emit rich traces data in OpenTelemetry format. By acting at the kernel level through eBPF, Odigos’ platform can collect traces with zero changes to the code and de minimus impact on app performance. Their technology also allows for instrumentation changes on the fly and deeper dives into traces to show request flows that had previously been black boxes to observability teams. Crucially, Odigos takes a modular approach, allowing customers to export their collected data to any monitoring backend they choose – freeing organizations from costly vendor lock-in. With Odigos, enterprises can instantly access the meaningful telemetry data they need in an OpenTelemetry format they can control.   

Odigos began as an open-source project that rapidly gained popularity and its enterprise version is now used within Fortune 500 organizations across tens of thousands of microservices. Odigos’ customers are saving engineering hours that would have otherwise been spent on instrumentation. Customers are reaching convergence to the OpenTelemetry standards on their own terms (not tied to a single vendor ecosystem) and with dramatically less effort. As such, customers are getting the critical traces telemetry needed to monitor cloud-native applications. 

Why We’re Backing Odigos

The Odigos team, vision, and technology excited us from our first meeting. Odigos stands out for their technical achievements, unique perspective on the industry, and personal integrity. CTO and co-founder Eden Federman is a lifelong observability expert who created and donated to CNCF the code that underlies OpenTelemetry’s auto-instrumentation for the Go language. Eden has assembled a stellar team of OpenTelemetry Maintainers and eBPF experts. Eden and co-founder and CEO Ari Recht graduated from Y Combinator in 2023 and since then have shipped fast and robust products with a small but scrappy team. 

We believe Odigos is solving two of the most important challenges in the market — data and cost — while ultimately helping enterprises achieve cloud-native observability and transition to open standards. We love that they’re tackling the most difficult problems in the little-noticed, but critical “first mile” of observability. And they have a unique go-to-market wedge in helping enterprises transition to OpenTelemetry and free themselves from dependence on vendor-provided agents. From the get-go, they have worked with the world’s largest enterprises, showing their ability to deliver to the highest standards at scale. 

What’s ahead?

We’re excited to partner with Odigos as they emerge from stealth and launch their enterprise product to the market. We believe their technology is key to unlocking true observability for the cloud-native era.  

And we’re thrilled to be backing Odigos alongside Venture Guides, Mango Capital, Firestreak Ventures, and angels that are observability founders themselves, including Martin Mao (co-founder, Chronosphere), Christine Yen (co-founder, Honeycomb), Yuri Shkuro (creator of Jaeger), and Ben Seigelman (co-founder, Lightstep). 

Welcome to Salesforce Ventures, Odigos!

Welcome, Altana!

• Founder: Evan Smith, CEO
• Sector: Climate Tech and Supply Chain
• Location: New York, New York

The Opportunity

From climate change to geopolitical conflicts to the lingering effects of the pandemic, our global supply chain has never been under more pressure than it is today. Businesses the world over must reassess and diversify their supply chains to mitigate potential vulnerabilities and become more sustainable. However, companies are struggling to reinvent their supply chains in the face of ever-changing risks, the evolving regulatory landscape, and legacy solutions that can’t keep up with the pace of change. The market is in dire need of a new supply chain management solution that reflects the realities of the modern logistics industry.

The Solution

Altana applies artificial intelligence to vast quantities of public and non-public data to create a high-resolution, multi-relational, searchable map of the global supply chain for all physical goods for enterprises, logistics providers, and governments. 

Customers using Altana benefit from its federated data platform that provides every user visibility and AI across the global network while their personal data remains protected and secure. Altana’s AI solution can detect and share information across a customer’s value chain to help identify risks, such as high-emitting activities, out-of-compliance actions, signs of poor labor practices, and much more.

Further, Altana is one of the only platforms that can calculate Scope 3 emissions as well as inform companies of forced labor and modern slavery in their supply chain given their view into suppliers in a customer’s network. 

All in all, these factors make Altana the first dynamic, intelligent, universal map of the global supply chain. 

Why We’re Backing Altana

We believe Altana is best positioned to create and scale a Scope 3 solution. Altana’s recently announced partnership with Climate TRACE, alongside the platform’s proven ability to understand the intricacies of supply chains, means the team can illuminate emissions across suppliers. 

This capability will become increasingly important as new sustainability regulations are passed across Europe and the United States. Most companies are currently unprepared to quantify and report their Scope 3 emissions, as is required per incoming EU law. Altana is building an industry-leading solution for Scope 3 tracking at just the right time for market adoption. 

In addition to the climate benefits, Altana’s global supply chain map has many critical applications. For example, Altana can help customers root out forced labor from customers’ supply chains, coordinate supply and demand across multiple tiers of the supply chain to reduce costs and working capital, and price and insure against the risks of supply chain business interruptions.

Therefore, Altana is going after a global market that is expansive and growing. The supply chain management market is estimated to reach ~$45B by 2027. The pandemic and recent geopolitical rifts have laid bare the criticality of a dynamic, transparent supply chain for all businesses. Altana is offering a mission-critical solution to large brands across the world. 

And importantly, Altana possesses a strong data moat with its federated data model. Roughly 50% of Altana’s supply chain visibility comes from first-party and proprietary customer data. The strongest product in the market will depend on access to good data, and Altana already has a clear edge.

Finally, we’re excited to back a three-time founder Evan Smith, and a team that has years of experience building AI products.

What’s Ahead?

We’re excited to work with Altana to continue building out their Scope 3 functionality and capabilities. Given Salesforce’s commitment to sustainability, we foresee many potential collaboration opportunities both internally and across Salesforce’s ecosystem of partners and customers. Salesforce is already tracking the evolving regulatory landscape as new sustainability and human rights regulations are instituted, and Altana is well-positioned to support us and our partners.

Welcome to Salesforce Ventures, Altana!

Welcome, Uplimit!

• Founders: Julia Stiglitz, Sourabh Bajaj, Jake Samuelson
• Sector: Workforce Development
• Location: San Mateo, CA

The Opportunity

AI has created an unprecedented need for new professional skills, and the education market is currently ill-equipped to handle the demand. According to Harvard Business Review, executives estimate that 40% of their workforce will need to reskill as a result of AI and automation over the next three years. At the same time, 75% of workers say they don’t know how to acquire the skills their employers will require in the future. This gap exists because current solutions are either inaccessible, slow-moving, or have low engagement. 

For instance, workers can seek out graduate and certificate programs in AI and ML from accredited institutions, but these courses are often prohibitively expensive. The rapid pace of innovation in AI and ML also makes it difficult for self-taught individuals to keep up. Further, reskilling platforms often suffer from low engagement and completion rates, according to Forbes. 

If we as a society are to realize artificial intelligence’s enormous potential, we’ll need a new high-quality adult learning resource that can help today’s workers transition to an AI-enabled future. 

The Solution

Uplimit is pioneering a new approach to scaling effective enterprise education. Their end-to-end solution uses AI to supercharge authoring, learner support, and course management, so companies no longer have to choose between impact and scale. The platform enables companies to train their employees and customers on the skills of tomorrow. Customers use Uplimit to dramatically scale their learning programs, relying on AI-powered learner support features, a generative AI content creation engine, and live cohort management tools to decrease costs while improving outcomes. 

Focusing on individuals and organizations worldwide, Uplimit aims to surpass traditional learning limitations and achieve exceptional outcomes at scale. The company is harnessing AI to deliver affordable and effective professional education.

Why We’re Backing Uplimit

We believe Uplimit is the platform that will help individuals and companies access the skills of the future for several reasons. 

It starts with the founding team. CEO Julia Stiglitz was among the first hires at Coursera, and she built and scaled their enterprise business from zero to well over a thousand customers. Most recently, she left her role as a partner at top-tier ed-tech fund GSV Ventures to start Uplimit because she recognized an opportunity for major disruption in the ed-tech market. Her co-founder and CTO, Sourabh Bajaj, was previously an ML Lead at Google. Rounding out the founding team is Jake Samuelson, who brings years of product experience at companies like Wayfair and Coursera. This trio brings a unique and powerful combination of AI expertise, enterprise GTM experience, and ed-tech chops to Uplimit. 

Uplimit is also already seeing traction in the market. They’ve signed several large enterprise contracts with organizations like GE Health, Procore, and Kraft Heinz, and are seeing 75-80% completion rates on their courses — an extremely positive outlier in the edtech market.

Finally, Uplimit is entering the market at an ideal time. Only 4% of the global $6T education market is digitized today. Nearly all large enterprises are grappling with the opportunities and risks of AI for their workforces, and Uplimit is quickly becoming a trusted partner and solution within this context. Uplimit has proven to be able to upskill employees and customers on AI in a scalable fashion, and the team is receiving tremendous interest as a result.

What’s Ahead?

Learning is a lifelong journey woven into the fabric of every career. We’re excited to support Uplimit to reimagine what outcomes can be for those upskilling on AI and other skills of the future.

We’re also excited about the potential value we can deliver to Uplimit. Their organization is already partnering with other members of the Salesforce Ventures’ portfolio, including Databricks. We foresee many potential opportunities for partnerships internally within Salesforce and across our broader ecosystem of partners.

Welcome to Salesforce Ventures, Uplimit!

Welcome, Sixfold!

• Founders: Alex Schmelkin, Jane Tran, and Brian Moseley
• Sector: GenAI, Insurance
• Location: New York, NY

The Opportunity

Insurance underwriters today have a “front door” problem: with limited capacity, they’re typically only able to process ~10% of the submissions they receive from brokers. Capacity is restricted by workflows that are largely manual, and that require underwriters to aggregate unstructured and disjointed data sources before applying a risk assessment framework. Few software tools currently exist to automate the risk assessment process and support underwriters in their decisioning, leaving a large number of submissions unreviewed. The result is significantly less revenue for insurers.

The Solution

Sixfold leverages generative AI to accelerate the underwriting process. The company’s proprietary engine ingests broker submissions and triages them against the carrier’s underwriting manual to intelligently prioritize and route submissions. Sixfold combines submission data with third-party and proprietary data sources (all previously requiring a human to synthesize) to generate a risk score and recommendation to support the underwriter’s decision.

Sixfold accelerates the speed at which carriers can process submissions, increasing the volume of gross written premiums per underwriter by more than 3x. By increasing the volume of submissions that an underwriting team can process, Sixfold enables carriers to prioritize the underwriting of the submissions that best fit their risk profile. Not only does this drive incremental revenue gains, it also differentiates carriers competing for quality business from brokers.

Why We’re Backing Sixfold

Salesforce Ventures is excited about the opportunity in vertical applications for AI. We’re interested in teams with deep domain expertise that are using AI to drive meaningful outcomes for users. We look for founders who have an industry and distribution network that can form a moat against newer market entrants. The Sixfold team—Alex Schmelkin (CEO), Jane Tran (COO), and Brian Moseley (CTO)—feature this depth of experience and connection in the insurance sector, alongside deep technical expertise and a strong entrepreneurial pedigree. Alex and Jane were both founding members of the team at Unqork, and Brian was previously Head of Developer Experience at AMEX.

Due to heavy compliance requirements and long procurement cycles, insurance is often a challenging sector to sell into. The Sixfold platform is built with industry-grade security and reliability, data traceability, and data lineage that supports compliance. The Sixfold team’s deep understanding of the sector has allowed them to build a product that truly captures the mindset of the underwriter, making it the only turnkey solution currently in the market.

Sixfold is solving a long-term pain point for insurance carriers, with clear and outsized ROI. Since launching the platform in mid-2023, Sixfold has seen strong pull from global carriers across commercial underwriting lines, including property & casualty, life, and specialty (e.g. cyber) insurance. The company has also received industry recognition, including selection for Lloyd’s Lab’s Accelerator program, the #1 insurance-focused accelerator in the world.

What’s Ahead?

Sixfold is well-positioned to benefit from a moment of evolution in an industry that has historically been a late adopter when it comes to technological transformation. Awareness and access to generative AI has catalyzed interest and budget allocated to new technologies, with potential use cases that drive measurable topline revenue growth. As such, insurers see a huge opportunity in implementing AI technology, and Sixfold is working alongside industry leaders and regulators to facilitate this transition.

We’re incredibly excited to be partnering with Sixfold on their journey to unlock huge efficiencies for underwriters in the coming years. And we’re thrilled to be leading the Series A round in Sixfold alongside Scale Venture Partners and MTech, and existing investors Bessemer Venture Partners and Crystal Venture Partners.

Welcome to Salesforce Ventures, Sixfold!

Welcome, Together AI!

• Founders: Vipul Ved Prakash, Ce Zhang, Chris Ré, Percy Liang
• Sector: Artificial Intelligence
• Location: San Francisco, CA

The Opportunity

2023 was a year of incredible growth and innovation in open-source AI. The year started with a meaningful gap in model performance between open-source and closed-source models, but the paradigm quickly shifted when Meta introduced Llama in February, catalyzing the emergence of a host of more powerful open-source models like Falcon and Mistral/Mixtral. At Salesforce Ventures we’re big believers in open source, having worked with and invested in numerous companies that focus on open-source, including Hugging Face, Airbyte, Astronomer, dbt, Starburst, and MuleSoft. 

We believe the AI world will be hybrid in the future, and that companies will utilize both closed-source and open-source technologies. Furthermore, having a powerful model is no longer enough. To fully unlock adoption, we need an entire stack built around the models to enable the right balance between performance and cost. With this context in mind, we searched for the right team with a bold vision that could build the best infrastructure for training and running open-source models in production, which is why we’re beyond excited to announce that we’re leading a new round in Together AI. 

The Solution

Together AI is capturing the market at exactly the right moment—open source is taking off and the need for good, performant, cost effective GPU infrastructure is more acute than ever. While the GPU hardware supply shortage is a prominent factor, it’s not the only factor that contributes to the question of “why now.” 

The GPU supply crunch makes it difficult for companies from all market segments to get their hands on GPUs. This shortage is exacerbated for companies that don’t have long-term relationships or big contracts with hyperscalers or cloud providers, given that’s where most GPU supply currently resides. 

Even for companies that do have these relationships, the ability to train and serve models in production well is a different set of challenges. There are many layers of complexity when it comes to running training and inference workloads to ensure criteria users care about, such as latency, throughput, lower failure rate during training, and effective training cycles. As such, there’s a growing desire for an abstraction layer to automate training, finetuning, and deployment so customers don’t have to spin up their own infrastructure or hire their own teams with backgrounds in AI or systems engineering.

Together AI captures customers’ end-to-end needs for AI workloads through its full-stack approach. The company offers both compute and software packaged in products that vary in volume of software abstraction on top of the hardware compute resources. For customers that want dedicated clusters for training (or inference), Together AI offers GPU Clusters comprised of high-end compute and networking, plus a software layer that incorporates the optimizations needed for users to run AI workloads efficiently without needing to manage infrastructure. The Together AI team has also led the development of efficient kernels like FlashAttention for training, and a number of techniques to speed up inference of transformer models that can extract 2-8 times more work from GPUs for generative AI workloads. 

For customers that want an additional layer of abstraction, typically for model deployments, Together AI supports an extensive list of open-source models (e.g., Llama-2, Code Llama, Falcon, Vicuna, Mistral/Mixtral, SDXL, etc.) as well as its own models (e.g. RedPajama, StripedHyena, Evo) that are at the frontier of model architecture research. Together AI will also soon support the option for customers to bring their own models. Customers can host these models using dedicated API instances built on top of the Together Inference Engine optimized with open-source and proprietary techniques. What’s more, Together AI will soon be able to deploy in customers’ own cloud environments. The ability to bring their own models and deploy in their own environments will open up numerous use cases for enterprise customers. 

Together AI also offers fine-tuning as part of this product, which is an attractive value-add for open source use cases. For customers who have specific needs, they can choose to build their own Custom Models, leveraging the Together AI software and hardware stack as well as support from their technical team on finding the optimal data design, architecture, and training recipe.

Why We’re Backing Together AI

We first met the CEO and co-founder of Together AI, Vipul Ved Prakash, back in the summer of 2023. It didn’t take long to realize Vipul had built something special, starting with an outstanding founding team. Both Vipul and co-founder Chris Ré are serial entrepreneurs with previous successful exits. Chris and fellow co-founder Percy Liang are also the leading researchers in AI model architectures and infrastructure. Ce Zhang (CTO and co-founder) is an expert in decentralized and distributed training/learning as well as data-centric ML Ops. The team’s combined expertise and experience suggest they can build proprietary IP around optimizing the AI infrastructure stack, as well as scale talent and functional teams.

We believe Together AI’s “full-stack” product approach is the right approach to the open-source AI market. By offering a suite of products that vary in how close they are to the underlying hardware—from dedicated clusters to serverless endpoints—Together AI captures demand from all types of workloads: training, fine-tuning, and inference. There is no inference without training or fine-tuning, and we think customers will increasingly want to deploy where they fine-tune and train their models, especially given some of the features that the Together AI team are working on to increase reliability, privacy, and security. 

As training and inference workloads ebb and flow, Together AI can move the freed up GPU resources across different types of workloads, allowing the company to scale efficiently. In this sense, Together AI straddles two distinct categories of companies that have emerged in this new AI era: specialized GPU cloud providers and serverless endpoint / LLM Ops platforms. We like this approach, as it provides differentiated software on top of hardware when compared to pure GPU cloud providers. This approach also provides more control over hardware utilization and optimizations compared to pure serverless endpoint providers / LLM Ops companies.

Together AI is also, at its core, an AI research company. Two of Together AI’s co-founders are bona fide luminaries in the AI research community. In addition to having Ce Zhang as the CTO, Together AI also brought onboard Tri Dao, the creator of FlashAttention and FlashAttention-2, as Chief Scientist in summer 2023. The power behind Together AI’s products is vested in the company’s ability to rapidly bring research innovations to production. 

In the spirit of open-source, Together AI has been prolific in publishing some of the optimization techniques (FlashDecoding, Medusa, Cocktail SGD) and model research (RedPajama, StripedHyena) that are garnering a lot of attention from the broader AI community. The research and models are great tools to drive demand to Together AI’s platform, creating a flywheel for growth. Together AI’s continuous research capability differentiates its platform from other GPU Cloud/serverless endpoint platforms and hyperscalers, cementing a longer-term technical moat. 

What’s ahead?

Amid the litany of 2024 AI predictions that have been circulating online, one common thread we keep seeing is how 2024 will be the year that customers go from training models to deploying models in production. While we believe this is directionally correct, we suspect that process to be much slower and more gradual than people anticipate. There’s still additional customer education to be done and infrastructure for model deployment needs to continue to improve. 

Together AI is not the only company that has realized this—the field of GPU cloud/serverless endpoints platforms keeps expanding to fill the need for better infrastructure. This entrepreneurial enthusiasm speaks to the immense market opportunity founders see in this space. Vipul and his team have a bold long-term vision that requires precise and vigorous execution to accomplish. We are confident they will realize their vision, and Salesforce Ventures will be there to support them every step of the way.

We’re thrilled to partner with Vipul, Ce, Chris, Percy and the rest of the Together AI team. Together, we will bring the fastest and most performant cloud in generative AI to more  users who are pushing the frontier of AI development. Welcome to the Salesforce Ventures family!

Welcome, Oleria

• Founder: Jim Alkove, Jagadeesh Kunda
• Sector: Cybersecurity
• Location: Seattle, WA

The Opportunity

For 30+ years, organizations around the world have utilized Identity and Access Management (IAM) solutions to enable their workforce as they incorporate more technology/devices. Over time, technology has evolved dramatically—from specific individual users part of an on-premises server in a basement, to users now accessing their corporate networks through multiple devices across the world while browsing the public internet. The rise of cloud computing has added to this change, as the server in the basement has been replaced by ephemeral instances of the cloud that change identities by the minute. 

This is where we see an opportunity. While IAM has evolved over the decades, the IT DNA has persisted through legacy vendors. Even relatively newer vendors brand themselves as security companies while providing IT/compliance/governance DNA solutions that continue to fail the modern enterprise. These organizations struggle to keep up with the growing demand and complexities of modern identity infrastructure that brings together different users, networks, micro-services, SaaS applications, and more.  

The way we see it, while today’s solutions are good at provisioning access and creating basic identity workflows / authenticating users from an IT perspective, they lack the intelligence, agility, and security context required to keep up with the rise in cyberattacks. Crowdstrike reports that 80% of all security breaches are the result of compromised identities. Further, Gartner states that “by 2026, 70% of identity-first security strategies will fail unless organizations adopt context-based access policies that are continuous and consistent.” 

We believe IAM needs to be rebuilt with a security-first & cloud-native DNA. This is where Oleria comes in 🙂 

The Solution

Oleria has developed an innovative approach to IAM that’s designed to provide appropriate access to the right users, at the right time, for the right duration, with a focus on great UX. 

Oleria’s Adaptive Security solution continuously assesses and validates the people, applications, and assets involved in each digital interaction, enabling organizations to adapt security to specific contexts and changing needs. With modern businesses adopting an ever-increasing number of interconnected SaaS applications and cloud infrastructure to drive global operations, Oleria represents a massive improvement over legacy security solutions that require significant manual effort to combat identity-based threats. 

Oleria’s AI-first approach, combined with a security and identity DNA, can orchestrate IAM across an organization without needing constant manual input. Oleria can understand user behavior and patterns of access to become smarter while enabling organizations to adopt a just-in-time + zero-trust philosophy at scale. 

Oleria’s value proposition is already resonating, as the company has built a strong pipeline of unicorn startups and large enterprises ready to implement Oleria’s Adaptive Security solution.

Why We’re Backing Oleria

Our excitement for Oleria stems from our confidence in the team and our optimism for the market they’re building in / massive problem they’re solving. 

Founders Jim Alkove and Jagadeesh Kunda possess a wealth of cybersecurity expertise. Jim is the former Chief Trust Officer at Salesforce with 25+ years of experience building cybersecurity products for Microsoft and Google. Jagadeesh is the former VP of Identity at Salesforce and has 20+ years of experience in the infrastructure, security, and identity space—most recently as the CPO at JumpCloud. They bring together the right combination of product-building expertise and operational security prowess at the largest of enterprise scales. 

This problem of enterprise identity is also close to their hearts. While at Salesforce, Jim and Jagadeesh invested heavily to modernize Salesforce’s identity infrastructure. Their shared experience was the spark that has become Oleria.

The duo are entering a market that’s ripe for disruption. IAM / IGA (Identity Governance and Administration) is a $17B+ industry dominated by legacy enterprises and private equity roll-ups that have been slow to keep up with the shift to SaaS and cloud. As more and more hacks are wedged in through lack of identity governance, the timing for building a security-focused IAM / IGA solution is ideal.

What’s Next?

We’re very excited to back Oleria’s Series A round alongside Evolution Equity. 

This new round of funding will enable Oleria to ramp up hiring to accelerate product innovation, including their AI strategy and GTM strategy. We look forward to supporting the team as they work to build the next-gen cybersecurity solution for enterprises.

Welcome to the Salesforce Ventures family, Oleria!

Welcome, AutogenAI!

• Founder: Sean Williams
• Sector: GenAI, Bid Writing
• Location: London, UK

The Opportunity

The bid writing process is mired in the past. Many global enterprises require hundreds of staff working several months to submit a single bid, and the existing tech stack is wholly insufficient to support the needs of these organizations. The result is numerous underserved organizations wasting time, money, and effort writing failed bids.

The Solution

AutogenAI is revolutionizing the time-consuming and highly sensitive bidding process by introducing generative AI to the equation. The product is a unique combination of gen AI-native and bidding-first.

The AutogenAI team builds secure, bespoke language engines for Fortune 500 companies, international government agencies, management consultancies, and construction companies, as well as charities and nonprofits applying for grant funding. These language engines harness the power of large language technology to turbo-charge the sales function. By leveraging AutogenAI, organizations can draft high-quality bids quickly and accurately, giving them a significant leg up against their competition.

To date, AutogenAI has helped businesses achieve a 30% uplift in win rates and cut associated costs by up to 85%. The team has already seen immense interest from large corporations selling into the public sector—particularly amongst global consultancies, and companies in the construction and utilities sectors. AutogenAI was appointed to the UK Government’s AI Framework, allowing them to offer their services to all UK public sector organizations. AutogenAI also recently expanded services to the U.S. and Australia.

Why We’re Backing AutogenAI

AutogenAI is an excellent example of a company utilizing generative AI to address a real pain point in a verticalized market. The team’s combination of deep bid writing experience and technical expertise makes them well-equipped to build relevant solutions that address customer needs.

Our investment in AutogenAI represents our conviction that their software is a game changer for enterprises that secure business via tendering and drafting proposals. While every business is in the midst of being remade by generative AI, AutogenAI is far ahead of the market in terms of the capability of its technology.

AutogenAI is one of the fastest-growing companies we’ve encountered in the generative AI application layer space, and we’re excited to back the team as they continue to work to revolutionize the bid writing process.

What’s Ahead?

As one of AutogenAI’s customers said to us on a reference call, “This whole industry is about to change. Soon bid writers will become prompt writers. Anyone not using this technology will fall behind.”

We’re excited to partner with AutogenAI alongside Spark Capital, Blossom Capital, and other investors as the team works to further develop its bid-writing product suite to help businesses efficiently win more work.

Welcome to Salesforce Ventures, AutogenAI!

Welcome, Amini!

• Founder: Kate Kallot
• Sector: Sustainability
• Location: Nairobi, Kenya

The Opportunity

Africa is the last and biggest emerging market. The continent is home to 65% of the world’s uncultivated arable land with a population that’s set to double to 2.5B by 2050. But Africa’s largely agrarian economy is under threat by a changing climate that’s expected to expose up to 118M people to droughts, food shortages, and extreme heat by 2030—and the region is under-equipped to handle this challenge.

Consider that Africa has just one-eighth the minimum density of weather stations recommended by the World Meteorological Organization. This scarcity of data leads to inaccurate forecasts and puts civilians and supply chains at risk. With climate change driving more frequent and extreme weather events, more and better data is needed to predict environmental trends, enhance operational resilience, and safeguard people and supply chains across the continent. 

The Solution

Amini AI was launched against the backdrop of a rapidly growing African population uniquely exposed to climate change impacts. Founded in Nairobi in 2022, Amini is building the single source of truth for verifiable, immutable, and actionable environmental data across the African continent.

Leveraging satellites, existing data sources, and AI / ML, Amini has built a data ingestion engine and proprietary unification protocol that delivers reliable, precise, and unbiased environmental, climate, and vegetative data to public and private sector stakeholders at scale. This data can provide meaningful insights to farmers, governments, corporations, financial institutions, and supply chain operators to drive informed decision-making and sustainable growth.

Amini’s data is already being utilized in crucial functions like climate resilience planning, agricultural insurance risk assessments, and supply chain analysis. Amini AI unlocks solutions previously held back by data deficiency and can serve as a starting point for Africa’s transition to climate-smart agriculture and the development of sustainable supply chains.

Why We’re Backing Amini AI

There are many reasons to be excited about Amini, but for us it starts with the team led by CEO Kate Kallot. Before founding Amini, Kate led NVIDIA’s ecosystem expansion in emerging markets and also created the NVIDIA Emerging Chapters Program dedicated to supporting developers in Africa and beyond. Prior to NVIDIA, Kate led AI/ML teams at Arm and Intel, and has been recognized as one of the 100 most influential people in AI by TIME magazine. 

Kate has surrounded herself with an all-star team that’s motivated to build at the convergence of people and planet. The strength of the Amini team is evident in the company’s early success: Amini has already signed a partnership with the global brand Aon and has received inbound interest from numerous organizations that want to leverage Amini’s data to tap into the African market. 

Further, Amini is building in a large and growing market with strong tailwinds. The African data observation market has more demand than any other continent, and the markets for digital climate solutions, earth observation data, and supply chain software are all expanding at a rapid pace.

The problem Amini is tackling is significant and widespread, but we believe it’s the right time and the right team to get the job done. The opportunity for scale and impact is vast. 

What’s ahead?

We’re thrilled to partner with Amini alongside Female Founders Fund and existing investors Pale Blue Dot and Superorganism as Kate and team build their core technology, onboard new customers, and make inroads across Africa. Amini has already started to foster a more sustainable, climate-resilient future for the African continent. In the future, Kate foresees a company that will play a meaningful role in Africa’s economic and environmental transformation.

We’re excited to be along for the journey.

Welcome to Salesforce Ventures Impact Fund, Amini!

Welcome, Hugging Face!

We are thrilled to announce our investment in Hugging Face. Hugging Face has built the largest and most important AI open source community 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 artificial intelligence. 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’re excited to announce we’re leading the Series D round in Hugging Face, the leading open source platform for data science and machine learning (ML). Hugging Face 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 and 2019, Hugging Face 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 pre-trained models, including state-of-the-art NLP models. Since then, Hugging Face has expanded into other categories beyond 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 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!