The platformto enforce
AI agents ignore your rules. Your pricing logic, your refund policies, your escalation triggers, your compliance requirements. Open Bias catches violations before they reach your users.
Everything between your
agent and a bad decision.
Evaluator Engines
Four engines to match your enforcement needs. Judge uses a sidecar LLM for nuanced policy scoring. FSM handles deterministic workflows at zero latency. Choose the right tool for each policy.
Natural Language Policies
Write rules in plain English and compile them to executable policies. No DSL to learn, no config to debug. openbias compile "verify identity before refunds"
Automatic Intervention
Three strategies when policies are violated: amend system prompts, inject corrective messages, or modify responses directly. Enforcement happens before the next turn.
Observable by Default
Every enforcement decision is logged with per-condition pass/fail results. OpenTelemetry tracing, Langfuse integration, full audit trail. Answer "why did the agent do that?" with data.
Overview
Click any layer to expand.
WITHOUT GUARDRAILS
vAI agents don't follow instructions reliably. They hallucinate, skip steps, and drift from policy — especially across long conversations and edge cases.
MONITORING GAP
vYour agents are running hundreds of sessions simultaneously. Some follow policy. Some don't. Without enforcement, you find out from a customer complaint — not a dashboard.
PROXY
vIt sits between your app and the LLM provider. In between, every call is evaluated, logged, and — if needed — corrected. Zero changes to your agent code.
ENGINE
vA refund flow needs deterministic enforcement. Tone of voice needs judgment. Open Bias lets you match the engine to the constraint, so you're not paying for LLM calls where regex would do.
INTERVENE
vDetection without action is just monitoring. Open Bias closes the loop: every violation triggers an intervention strategy that steers the agent back on course, automatically.
How it works
1# policy.yaml2policies:3 - name: identity-check4 trigger: "before refund"5 conditions:6 - "user identity verified"7 action: amend_system_prompt89 - name: pricing-guard10 trigger: "discount offered"11 conditions:12 - "discount <= 20%"13 action: block_response
Performance you
can measure.
Deviation detection
Watch an agent drift from policy compliance in real time — and see the guardrails kick in.
Works with everything
you already use.
Connects to every major LLM provider, agent framework, and observability tool.
Ship policies,
not workarounds.
A proxy that gets out of your way. One line change to your client, full policy enforcement on every request.
Python native
Full type safety with Pydantic models.
YAML config
One file. Sensible defaults. No magic.
Provider agnostic
Anthropic, OpenAI, Google, Mistral, and more.
Open source
Self-host. No vendor lock-in.
pip install openbias
"Enforce identity verification before processing refunds. Automatically amend system prompts when policies are violated."
Customer Support Agent
Use Case, Support Automation
Policy violations caught
Simple, scalable
pricing
Open Source
Self-host the engines
- Unlimited agents & policies
- OpenTelemetry tracing
- Community support
Pro
Hosted enforcement with audit trails
Pay per policy evaluation. Coming soon.
- Everything in Open Source
- Managed cloud proxy
- Policy dashboard & analytics
- Audit trail with decision logs
- Team management & RBAC
- Priority support & SLA
Enterprise
Dedicated infrastructure for regulated environments
- Everything in Pro
- VPC / on-premise deployment
- SSO & SAML
- Compliance packages
- Dedicated support engineer
- Custom SLAs & contracts
What if your agents
couldn't break the rules?
Join teams enforcing AI agent policies in real-time. Open source. Free to start.
No credit card required