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Finnish startup Root Signals lands $2.8M to help accelerate GenAI adoption

Root Signals founders
Picture credits: Root Signals

Root Signals, a Helsinki- and Palo Alto-based startup specialising in GenAI measurement with LLM-as-a-judge techniques, has raised $2.8 million in funding. The round was led by Angular Ventures with participation from Business Finland, which backed Enifer and NADMED

Funds utilisation 

The startup will use the fresh capital to accelerate its platform and model development, and sales and marketing capabilities.

“Root Signals’s approach of using AI to manage enterprise AI implementation makes intuitive sense,” said 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.”

AI needs human judge

To guarantee AI applications behave as expected, companies are using tools to evaluate their output. These tools are like human judges, but they’re automated using AI. This helps keep AI safe, reliable, and accountable.

This is where Root Signals comes into the picture with its system called EvalOps, which makes this process easier. EvalOps helps companies measure how well their AI works, making it reliable, trustworthy, and auditable. 

By automating the evaluation process, EvalOps reduces the need for manual human review, saving time and resources. Additionally, it provides a consistent and objective measure of AI performance, which is essential for ensuring that AI applications meet high standards of quality.

Accelerates GenAI adoption 

Founded in 2023 by a team of AGI researchers and engineers, including Dr. Ari Heljakka, Root Signals helps businesses accelerate GenAI adoption by providing them with enterprise-grade tooling to comprehensively measure, control and monitor LLM applications.  

It solves the GenAI reliability problem for teams and enterprises. It helps companies 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, which is crucial for enterprises in regulated industries.

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.

“Our evaluations distil the best practices and insights of essentially over 50 papers of recent years,” said Oguzhan Gencoglu, Head of AI at Root Signals. “While measuring AI behaviour 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.” 

“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,” added Dr. Ari Heljakka, Founder and CEO of RootSignals, with a PhD in GenAI. 

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