As enterprises rush to deploy AI agents across their operations, a critical gap has emerged: while foundation models possess PhD-level general intelligence, they struggle to perform domain-specific enterprise tasks with the accuracy and reliability businesses require. Today, just 25% of AI projects deliver the outcomes companies want, according to IBM research, yet AI agents represent a projected $200B market over the next decade. Veris AI has built a solution through experience-based learning for AI agents using high-fidelity simulated environments. The company’s end-to-end platform allows enterprises to train AI agents in realistic digital sandboxes that mirror production environments, using proven techniques like reinforcement learning and targeted fine-tuning to ensure agents learn the job rather than just being told what to do. With early customers across financial services, enterprise productivity, and manufacturing already seeing results – including a consumer fintech company deploying compliant chatbots and a manufacturer training supply chain agents – Veris AI tackles the fundamental challenge of making AI agents production-ready and trustworthy for enterprise deployment.
AlleyWatch sat down with Veris AI CEO and Co-founder Mehdi Jamei to learn more about the business, its future plans, recent funding round, and much, much more….
Who were your investors and how much did you raise?
We raised $8.5M in seed funding. The round was led by Decibel Ventures and Acrew Capital, with participation from The House Fund, Idris Mokhtarzada, Ian Livingstone, Dorothy Chang and others.
Tell us about the product or service that Veris AI offers.
Enterprises are excited about AI agents, but they’re struggling to get the systems to work well within their own organizations. Self-driving car companies relied on simulated environments to get their vehicles ready for the road. What AI agents need is a high-fidelity, digital training ground so they can learn the specifics of the jobs they’ll actually be doing in a secure environment. That’s what Veris provides.
What inspired the start of Veris AI?
Between my cofounder Andi Partovi and I, we have over 25 years of experience helping companies deploy technology like AI in their organizations. And over the last few years, we’ve learned the unique barriers that prevent organizations from utilizing AI agents to their fullest extent. With demand for the systems outpacing anything we’ve seen, Andi and I realized a new training method was needed, one grounded in experience not static tests, to make sure businesses can actually trust AI agents to perform in the real-world.
How is Veris AI different?
As foundation models like those from OpenAI, Anthropic and others become more intelligent, enterprises need to find ways to harness the raw power of these LLMs, but also get them to perform really well in their unique environments. We’re pioneering the shift from instruction to experience-based learning, so agents learn the job to do – not just get told what to do. Supported by proven techniques like reinforcement learning and targeted fine-tuning, our end-to-end platform helps enterprises unlock the full value of their AI.
What market does Veris AI target and how big is it?
AI agents are projected to be an over $200B market over the next decade. Critical to achieving this growth is ensuring the systems actually deliver value for businesses. That’s the market Veris plays in, and we expect substantial demand over the coming years for our platform.
What’s your business model?
We offer our solutions as-service to customers, with a usage-based pricing model.
How are you preparing for a potential economic slowdown?
During times of economic slowdown, the most forward-looking companies tend to double-down on technology. And with AI, even more businesses are realizing the need to increase investment – even while cutting in other areas. So while there may be some impact, like longer deal times, we expect the AI market to stay robust even amid any broader economic slowdown.
What was the funding process like?
The fundraising process was quite smooth and quick. Overall, the industry has mostly come to the conclusion that to actually unlock the promise of autonomous agentic systems, we need new types of infrastructure that goes beyond what we’ve been trying. Veris’ pitch was exactly at the right time. Also, we were fortunate to have a deep network of investors who shared this vision. Our round ended up being very competitive and over-subscribed.
What are the biggest challenges that you faced while raising capital?
The biggest challenge was actually meeting the demands of some potential investors. In this market, time is of the essence. Our focus had to be on product market fit, not meeting the due diligence requirements of certain firms.
What factors about your business led your investors to write the check?
Around the world, companies are rushing to adopt AI agents. But today, just 25% of AI projects are actually driving the outcomes businesses want, according to an IBM survey of CEOs. This performance gap has the potential to create significant trust issues in the technology. And if they aren’t addressed, it will be tough for AI agents to get broad adoption. Veris offers the solution, which is why investors were so interested.
What are the milestones you plan to achieve in the next six months?
Over the next six months, our primary focus is on advancing and refining the Veris AI product as we move from early deployment into broader adoption. We’re excited to roll out Veris AI to our growing list of customers and begin capturing meaningful, real-world impact across key use cases.
Over the next six months, our primary focus is on advancing and refining the Veris AI product as we move from early deployment into broader adoption. We’re excited to roll out Veris AI to our growing list of customers and begin capturing meaningful, real-world impact across key use cases.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Building your network when you don’t need it is the best advice that I’ve heard and certainly helped us in our fundraising. This is especially true for seed-stage startups, where an outsized emphasis is placed on the team and their ability to execute.
Where do you see the company going now over the near term?
We’re using the new funds to help build out our team of engineers and data scientists to help us improve and scale the platform.
What’s your favorite spring destination in and around the city?
In the city, sunset concerts at Central Park (e.g. summerstage festivals) are fantastic. Outside of the city, Storm King Art Center is a must-visit in the spring.
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