Intro
Last updated
Last updated
is a measurement, observability, and control platform for GenAI applications, automations, and agentic workflows powered by Large Language Models (LLMs). Such applications include chatbots, Retrieval Augmented Generation (RAG) systems, agents, data extractors, summarizers, translators, AI assistants, and various automations powered by LLMs.
Any developer can use Root Signals to:
Add appropriate metrics such as Truthfulness, Answer Relevance, or Coherence of responses to any LLM pipeline and optimize their design choices (which LLM to use, prompt, RAG hyper-parameters, etc.) using these measurements:
Log, record, and compare their changes and the corresponding measurements belonging to those
Integrate metrics into CI/CD pipelines (e.g. GitHub actions) to prevent regressions
Turn those metrics into guardrails that prevent wrong, inappropriate, undesirable, or in general sub-optimal behaviour of their LLM apps simply by adding trigger thresholds. Monitor the performance in real-time, in production.
Create custom metrics for attributes ranging from 'mention of politics' to 'adherence to our communications policy document v3.1'.
The dashboard provides a comprehensive overview of the performance of your specific LLM applications:
Root Signals provides 30+ built-in, ready-to-use evaluators called Root Evaluators.
Utilizing any LLM as a judge, you can create, benchmark, and tune Custom Evaluators.
We provide complete observability to your LLM applications through our Monitoring view.
Root Signals is available via
Root Signals can be used by individuals and organizations. Role-based Access Controls (RBAC), SLA, and security definitions are available for organizations. Enterprise customers also enjoy SSO signups via Okta and SAML.
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