ProofAgent is the accountability platform for production AI agents. It turns agent risk into deployment evidence through adversarial multi-juror scoring, production log audits, artifact reviews, signed readiness reports, and human review. The platform is built around the open-source ProofAgent Harness.

How do I test my AI agent with ProofAgent?

Install the open-source harness with 'pip install proofagent-harness', wrap your agent in a function returning AgentResponse, then call Harness().evaluate(my_agent, role, goal, knowledge, context). The harness runs adversarial multi-turn sessions and returns a /10 readiness score with traceable findings and fix recommendations.

What is adversarial multi-juror scoring?

Adversarial multi-juror scoring is ProofAgent's evaluation approach: a planner picks domain traps, a conductor applies sustained pressure across 25+ turns, and three independent juror agents score every behavior change. No single LLM call ever decides the verdict — the jury agents reach consensus or debate to a final score.

Is ProofAgent SOC 2 / HIPAA / GDPR compliant?

ProofAgent is SOC 2 Type II aligned, HIPAA-ready (BAAs available for enterprise customers), and follows GDPR best practices. Enterprise customers can deploy on-premises or in a private cloud with SSO/SAML, RBAC, tamper-evident audit logs, TLS 1.2+ in transit, and AES-256 at rest.

Can I use my own LLM with ProofAgent?

Yes. ProofAgent is BYO Harness LLM — the harness internals can run on any LLM provider (OpenAI, Anthropic, Google, local models). You bring your own model and API key; the harness orchestrates the multi-juror evaluation around it.

What metrics does ProofAgent measure?

11+ production metrics including Task Success, Hallucination Control, Safety, Policy Compliance, Memory Stability, Tone and Empathy, Manipulation Resistance, Tool Picking, Reasoning Quality, Relevance, and Drift Detection. Every metric is anchored to per-turn transcript evidence.

What is the difference between ProofAgent Platform and ProofAgent Harness OSS?

ProofAgent Harness OSS is the open-source multi-turn adversarial testing engine — Tier 1 of the platform, available standalone for developers and CI under Apache 2.0. ProofAgent Platform is the enterprise product that adds the other four tiers (production log audit, artifact review, multi-agent orchestration scoring, expert human review), a hosted dashboard, REST API, governance features, signed readiness reports, and dedicated support.

ProofAgent SDK documentation for AI agent evaluation

Name: ProofAgent Platform
Brand: ProofAgent
Availability: InStock

Official ProofAgent SDK docs: install with pip, wire your agent as a callable, run Harness-LLM-led or log-based evaluations, bring your own LLM, get readiness reports with per-metric scores and transcript-linked findings.

Install

The SDK is published to PyPI. Install with pip install proofagent-harness. Requires Python 3.10+. Set the environment variable for your LLM provider (ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY, or any LiteLLM-supported provider).

Wire your agent

Your agent is any Python callable that takes a message string and returns either a string (simple) or an AgentResponse (for deeper scoring — exposes tool calls, retrievals, and memory snapshots to the Harness Jurors). Wrap your existing LangChain, LangGraph, CrewAI, OpenAI Agents SDK, or custom agent in a 5-line adapter.

Run an evaluation

Call Harness.evaluate(your_agent, role=..., goal=..., context=AgentContext(...)). The harness runs the full 5-stage pipeline and returns a Report object with final_score, per_metric scores, certification tier, transcript, findings, and remediation guidance. Save as JSON or Markdown.

CI/CD integration

The SDK includes pytest integration with assertion-style thresholds: assert report.final_score >= 8.5; assert report.per_metric['safety'] >= 9.0. GitHub Actions, GitLab CI, CircleCI, and any pytest-compatible runner works out of the box.