What is Rhesis AI used for?

It is used to test LLM applications and AI agents for robustness, reliability, and compliance by simulating user interactions and adversarial scenarios.

Does Rhesis AI support open-source deployment?

Yes, Rhesis provides a self-hosted option via Docker for teams that need to maintain full control over their data.

What kind of metrics does the platform provide?

The platform offers over 60 metrics, including factual accuracy, role adherence, tone consistency, and safety checks using LLM-as-judge and code evaluators.

Can I integrate Rhesis with my existing development tools?

Yes, it supports integrations with LLM providers like Claude and Gemini, as well as project management tools like Jira and Confluence.

Is there a free version of Rhesis AI?

Rhesis is currently in Public Preview. While specific pricing isn't listed, interested teams typically need to sign up or contact the provider for access.

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LLM Testing

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Rhesis AI

Rhesis AI is a collaborative testing platform for LLM apps, offering adversarial scenario generation, conversation simulation, and 60+ metrics to ensure robustness and compliance.

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4 months ago

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LLM Testing

AI Safety

Red Teaming

MLOps

Adversarial Testing

AI Governance

Prompt Engineering

Quality Assurance

Tool information

Provider

Rhesis AI

Platforms

Web

Docker

API

SDK

Languages

English

API Available

Yes

Added to directory

4 months ago

Last updated

about 2 months ago

Rating

Not available

Pricing

Contact

About Rhesis AI

What the tool does and who it's for

Rhesis AI is an open-source and collaborative testing platform designed for LLM applications and AI agents. It enables engineering and product teams to define expected behaviors in natural language, generate adversarial test scenarios, and simulate multi-turn conversations to uncover vulnerabilities like jailbreaks and policy violations. The platform integrates with existing workflows via an SDK, API, or UI, offering over 60 pre-built evaluation metrics (including LLM-as-judge) and OpenTelemetry-based tracing to pinpoint the root cause of failures in non-deterministic systems.

Key capabilities

Conversation Simulation: Simulates multi-turn interactions and adversarial attacks to find edge cases.

Adversarial Testing: Automatically generates scenarios to test for jailbreaks and policy violations.

60+ Evaluation Metrics: Includes pre-built criteria for factual accuracy, coherence, and safety.

Collaborative Workflow: Allows engineers, PMs, and domain experts to review and curate tests together.

OpenTelemetry Tracing: Connects failures to specific root causes within the application stack.

Self-Hosting: Supports deployment via Docker for teams with strict data privacy requirements.

LLM-as-Judge: Utilizes advanced models to automatically score and evaluate application responses.

SDK & API Integration: Seamlessly connects to existing LLM apps for automated testing in CI/CD.

Pricing

Contact — plans below

Public Preview

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