As investors with a long-term, bullish outlook on generative AI, we’re excited to back early-stage companies which are scaling and innovating, often outside the limelight, as market urgency grows and companies continue to move from AI experimentation into production. Indeed, our recent “State of Enterprise Tech Spending” report, which surveyed 100 enterprise CXOs about their tech-spending plans, identified an increasing number of generative AI deployments within enterprises, but found the majority of new applications hadn’t yet been put to use.

That makes the enterprise traction of early-stage companies in our portfolio—including two which announced new, Series B funding rounds this week—even more impressive, in our view.

Take Galileo*, which this week announced it has raised $45 million in new funding. When we first spoke with Galileo more than two years ago, the company had an early product geared towards developers building applications with language models (circa May 2022!). But we fell in love with the bold vision of solving the quality-measurement problem for AI with unstructured data, and the talented technical founders who previously led AI teams at Google and Uber.

Today, Galileo helps its fast-moving, enterprise customer base, including customers like Twilio, Chegg, HP, Procter & Gamble and other Fortune 50 enterprises move from experimentation to production with gen AI products. The company’s “evaluation intelligence” platform helps customers monitor, debug and evaluate increasingly complex generative AI systems at scale.

As we do with many of our early-stage investments, we helped Galileo get its first products out the door and also assisted the company with customer introductions, marketing and making key hires.  This is an early-stage playbook we continue to execute as we search for standout generative-AI companies that are just getting started, often by former executives and developers from big-tech players. We continue to believe in the power of innovation at the infrastructure and application layers, where we think there’s a huge opportunity for value creation

Along those lines, three years ago, we helped lead the seed round for Neuron7*, a generative AI startup that that was little more than a concept at the time. Niken Patel, the CEO, had what we considered a bold and innovative thesis: Customer service in industries with complex, high-stakes products—like medical devices, industrial equipment and telecommunications—often faces significant bottlenecks. This is because the necessary knowledge to resolve customer issues is often scattered across disparate sources, such as lengthy product manuals, troubleshooting databases and the minds of expert technicians. Neuron7 aimed to solve this by leveraging large language models (LLMs) and cutting-edge generative AI to create a single system of intelligence. This approach consolidated vast, fragmented knowledge across thousands of interactions, people and data points, offering, in our view, a new level of insight and speed to resolve customer queries.

To help accelerate Neuron7’s journey, we augmented the expertise of the company’s product team with Bill Binch, a Battery operating partner with over three decades of enterprise sales experience. Within just 12 months, Neuron7 made impressive strides, securing top tier customers, including publicly listed companies that are high-profile players in sectors like healthcare and high-tech, where customer service is mission critical.

Some customers also have since expanded their usage of Neuron7 products, purchasing additional product modules to improve the efficiency and effectiveness of their support teams. Recognizing the company’s momentum, we doubled down on our investment, leading a $10M Series A round within a year of our seed investment. Today, Neuron7 continues to grow its presence across service-desk, call-center, and field-service operations and boasts an expanding global footprint. Most notably, Neuron7’s success caught the attention of ServiceNow, which through its ServiceNow Ventures arm made a strategic investment in the company this past March, further validating the company’s transformative potential.

And today, Neuron7 announced a $44 million Series B fundraising round led by Keith Block, the former Salesforce co-CEO, now at Smith Point Capital.

Another early-stage AI company we’re excited about is Orkes*, a microservice orchestration engine whose founders previously worked at Netflix, for developers to create durable workflows across distributed systems. We seed-funded the company and then doubled down to participate in the company’s $20 million Series A fundraising round earlier this year alongside Nexus Venture Partners and Vertex Ventures. This round, in our view, is a testament to Orkes’ significant growth and the continued importance of the Conductor open-source community, upon which Orkes’ technology is based. Orkes has become an important part of the critical application infrastructure underpinning digital companies in many industries.

As AI applications and services mature and more enterprises adopt them, we’re excited to keep backing the next generation of AI startups leading this charge. These companies span sectors from databases to software development to customer service to government contracting and more. We’d love to talk to you if you’re building in this area.

The post From Idea to Reality: Our Early-Stage Playbook for Generative AI Companies Serving the Enterprise appeared first on Battery Ventures.

As in previous quarters, we polled 100 CXOs who collectively represent over $35B in annual technology spending; our goal was, as always, to gauge the budget planning and overall sentiment of large enterprise technology buyers. To catch up on previous reports, check out what we published in March 2023, September 2023 and April 2024.

A few highlights from the survey:

• Buyer sentiment rose significantly relative to prior quarters, indicating a rebound in technology spending from buyers across industries.
• Overall budgets are trending upward with 74% this quarter vs. 55% in Q1’24 expecting an increase over the next year. With 59% of those increasing budgets seeking to invest in experimental initiatives and new tech, we see strong opportunities for startups in 2025
• Tech employment is leveling out. ​​The number of organizations looking to slow down or freeze hiring has dropped 19 percentage points from 46% in Q1 2023 to 27% in Q3 2024. Moreover, 42% of respondents expected to increase tech hiring over the next year.
• The AI wave is still building, but the future has been slower than anticipated. Today only 5.5% of identified AI use cases are in production, a sobering reality check on respondents’ Q1’24 projection that 52% of identified use cases would be in production over the next 24 months.
• That said, enthusiasm for, and continued investment in, Generative AI remains high. Our survey reveals some interesting trends on which use cases will deploy next, preferred AI model deployments, and what other tech priorities are emerging downstream in light of more AI production rollouts.

We see a lot of fresh opportunities for early-stage technology startups in these survey findings. Check out the full report here to learn more:

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