Finally, a way to measure Your LLM Responses

Root Signals lets you create, optimize and embed automated evaluators into your code, so you can continuously monitor the behavior of LLM automations in production.

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Trust, Control, and Safety:
The Big GenAI App Challenges

Let's face it. You don't really know if your LLM features are delivering quality results.

1

You're relying on experts to do "vibe checks,” but they are biased and slow.

2

You've tried open source evaluators, but they are too generic for your application.

3

You've embedded basic guardrails, but they're a partial solution at best.

GenAI Apps raise complex questions...

Can you trust your GenAI application?

Trusting your application can be challenging due to unpredictability of LLMs, potential reputational risks, and incompliance with current regulations.

Can you safely ship your App to production?

Shipping your GenAI application to production can cause a lot of delays and increase development costs due to unclarity of LLM performance.

Can you control LLM's behaviour & measure quality?

Evaluating how your models perform, tracking changes, and controlling how it behaves can be a difficult and time consuming task that requires hard data science knowledge.

Get visibility into the “black box” of LLM features — so you can build better products.

Book A Demo

Platform

Leverage evaluations to optimize LLMs, judges, and prompts for the best balance of quality, cost, and latency.

Ensure LLM workflows deliver quality outputs, prevent hallucinations, and maximize accuracy.

Continue to improve your AI-powered products in production.

How it works?

STEP 1

Build use case specific AI evaluators.

Build unique combinations of context-specific testing criteria that go beyond just the generic factors of accuracy, relevance, and helpfulness.

Build Custom Evaluators

STEP 2

Test your AI automations against multiple LLMs.

Score each individual AI automation against every potentially relevant LLM, so you can select the best LLM for your specific use case.

Test Automations

STEP 3

Embed evaluators into your code to monitor AI in production.

With a few lines of code, you can continuously evaluate AI performance and identify issues that impact product quality.

Get Started

Listen what our customers are saying

AI Health-Tech Startup

Gosta Labs

“If you aim for medical device classification—you need integrated evaluation tools like Root Signals to confirm that your outputs stay trustworthy and meet those high standards.”

Watch the full Root Talks episode

International Real Estate Enterprise, 2500+ Employees

Newsec

“Overall, Root Signals is the most convincing platform I’ve encountered in terms of evaluating and validating generative AI.”

Watch the full Root Talks episode

Digital transformation consultancy, 1500+ employees

Gofore

“Root Signals definitely enhances the solutions we can offer—particularly around trustworthiness and reliable automation.”

Watch the full Root Talks episode

What makes us different?

Detailed Scoring
vs. Simple Blocking

While others focus on blocking unwanted outputs, we excel in scoring and evaluating LLM behavior, providing a more nuanced and insightful measure of performance.

Learn More

Readable Metrics

Unlike other tools that offer only technical outputs suited for ML experts, our platform provides clear and understandable evaluation metrics (e.g. truthfulness, safety, relevance, context recall, +30 others) making it easy for anyone to assess and improve LLM performance, not just experienced data scientists.

Learn More

Custom Evaluators

Root Signals allows you to easily build high-quality, LLM-based custom evaluators tailored to your specific niche use case that stay up-to-date as your models evolve and provide continuous feedback to consistently enhance your GenAI app’s performance.

Build Custom Evaluator

Finally, a way to measure Your LLM Responses

Trust, Control, and Safety: The Big GenAI App Challenges

LLMs are unpredictable & hard to trust

Shipping to production is risky and costly

Challenges to control LLM behaviour & quality

Let's face it. You don't really know if your LLM features are delivering quality results.

1

You're relying on experts to do "vibe checks,” but they are biased and slow.

2

You've tried open source evaluators, but they are too generic for your application.

3

You've embedded basic guardrails, but they're a partial solution at best.

GenAI Apps raise complex questions...

Can you trust your GenAI application?

Can you safely ship your App to production?

Can you control LLM's behaviour & measure quality?

Get visibility into the “black box” of LLM features — so you can build better products.

Leverage evaluations to optimize LLMs, judges, and prompts for the best balance of quality, cost, and latency.

Ensure LLM workflows deliver quality outputs, prevent hallucinations, and maximize accuracy.

Continue to improve your AI-powered products in production.

Flexibility for any LLM and tech stack

LLM Agnostic

Adaptable to any stack

Test our Evaluator

Try it out!

With Root Signals, we went from 65% to 83% accuracyFinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot functionSoftware Scaleup

How it works?

Build use case specific AI evaluators.

Test your AI automations against multiple LLMs.

Embed evaluators into your code to monitor AI in production.

Test your AI automations against multiple LLMs.

Embed evaluators into your code to monitor AI in production.

With Root Signals, we went from 65% to 83% accuracyFinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot functionSoftware Scaleup

Listen what our customers are saying

Gosta Labs

Newsec

Gofore

Test your AI automations against multiple LLMs.

Embed evaluators into your code to monitor AI in production.

For companies with AI at the centre of the roadmap

GenAI Companies

Enterprises

LLM Consultancies

Root Signals Evaluators Whitepaper

Root Signals Blog

Events & Webinars

Get Started with Root Signals

With Root Signals, we went from 65% to 83% accuracyFinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot functionSoftware Scaleup

What makes us different?

Detailed Scoring vs. Simple Blocking

Readable Metrics

Custom Evaluators

Trust, Control, and Safety:
The Big GenAI App Challenges

With Root Signals, we went from 65% to 83% accuracy
FinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot function
Software Scaleup

With Root Signals, we went from 65% to 83% accuracy
FinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot function
Software Scaleup

With Root Signals, we went from 65% to 83% accuracy
FinTech Company

We see instant value after buying Root Signals Evaluation SDK. We can easily implement it as part of our chatbot function
Software Scaleup

Detailed Scoring
vs. Simple Blocking