The company’s tools help enterprises accelerate GenAI adoption by offering robust capabilities for measuring, controlling, and monitoring large language model (LLM) applications.

The funding round was led by Angular Ventures, with additional backing from Business Finland. Root Signals plans to use the capital to scale its platform, enhance its AI models, and expand sales and marketing efforts.

AI engineers developing GenAI-powered applications are increasingly using guardrails to prevent unintended outputs, but while these mitigate risks, they often fall short of unlocking the full potential of AI systems. To overcome this, engineers are realising that a more nuanced approach is needed: one that involves thoroughly evaluating AI outputs through a variety of automated measurements, simulating the role of a human reviewer.

This growing trend is known as LLM-as-a-judge, which involves using AI models to assess and quantify aspects such as the likelihood of hallucinations, the relevance of responses, or compliance with regulations. However, many existing AI systems struggle with the complexity, cost, and unreliability of such assessments.

Root Signals addresses these challenges with what it calls EvalOps – a scalable framework that simplifies the creation and automation of these intricate measurements. This approach ensures that GenAI applications can be deployed with confidence, as they are more measurable, reliable, and auditable, while also ensuring long-term scalability and reusability.

"GenAI has no built-in quality control. You cannot treat it as traditional software, but rather you need to think of it as an unreliable freelancer. You have to be pedantic in instructing it, and then check its work in seven different ways – and then check again tomorrow. We make this scalable with metrics that are understandable and easy to maintain in production. Most other power tools in this sector are overly low-level and complex, or they provide more black boxes that kick the reliability can down the road," says Dr Ari Heljakka, Founder and CEO of Root Signals, with a PhD in GenAI.

The most eager adopters of Root Signals have been independent software vendors providing GenAI-powered vertical bots to their specific domains of expertise, AI teams of fast-moving  incumbent industry players seeking to develop competitive advantage, and LLM software consultants. With Root Signals, companies can build comprehensive metrics quickly, making detailed model-to-model comparisons easy. This unlocks a principled way to replace large models like GPTs with smaller, faster on-premise models – crucial for enterprises in regulated industries.

“Our evaluations distill the best practices and insights of essentially over 50 papers of recent years," says Oguzhan Gencoglu, Head of AI at Root Signals. “While measuring AI behavior is one thing, our users constantly ask: ‘How can I or my customers trust your AI itself?’ So, unlike other players, we baked self-measurability into the core of our evaluation engine.”

"Root Signals’s approach of using AI to manage enterprise AI implementation makes intuitive sense,” says Gil Dibner of Angular Ventures. "Everyone knows 90% of enterprise GenAI projects are stalling. To succeed, enterprises will need to implement LLM-specific evaluation tooling, which is not easy to begin with. Doing this well enough for enterprise use cases means building a robust constellation of LLM judges, and few enterprises have sufficient know-how to do this. Fortunately for them, the Root Signals founders have been thinking about this problem for 20 years."

To date, Root Signals has gathered $2.8 million in total funding. The company has offices in Palo Alto, California, and Helsinki, Finland.