inhibitor-lab is the open-source R&D space for integrating the Inhibitor into agent-based systems. The audience is AI technologists who need defensible, real-time controls to keep autonomous agents from doing unsafe or wasteful work.
- Start here:
codefest/README.md - Team operations:
codefest/TEAM_MANAGEMENT.md
- Real-time guardrails for LLM-driven agents, with interruptibility and course correction rather than post-hoc filters.
- Audit-ready trails that explain why actions were blocked, enabling compliance reviews and root-cause analysis.
- Deployment agility via edge-first, stateless design that respects geographic data boundaries and GDPR expectations.
Leading AI companies scored D or worse on existential safety and lacked real-time decision safeguards. The Inhibitor is designed to close that gap with inline ethical reasoning and actionability.
References:
- Insight Mode – slower, with narrative reasoning for compliance, audits, and debugging.
- Performance Mode – fast, flag-only moderation for real-time agents and high-throughput tasks.
- GDPR compliance by design – data minimization, single-purpose processing, and stateless operation. See docs/gdpr-compliance.md.
- Global edge deployment – compute stays close to users to reduce cross-border movement. See docs/global-edge-deployment.md.
- Explained oversight – see docs/inhibitor-inside.md for a narrative on how the Inhibitor converts agent thoughts into structured, ethical decisions.
- See it live – explore the Inhibitor Demo to watch how risky prompts are detected, interventions fire, and responses get redirected in real time.
- Get an API key from appliedAIstudio.
- Review the REST API: docs/inhibitor-api.md.
- Fetch the latest OpenAPI spec (no API key required):
- JSON:
curl https://iaas.appliedai.studio/openapi.json - YAML:
curl https://iaas.appliedai.studio/openapi.yaml
- JSON:
- Run an example notebook (pick one):
- Layer the Inhibitor into your agent loop (oversight, critique, and action correction).
- Stress-test and monitor using the Inhibitor Application Sprint.
The Inhibitor tracks and surfaces violations across a maintained set of regulations. See docs/supported-regulations.md for the latest mappings.
notebooks/– interactive scenarios showing oversight and moderation patterns.examples/– lightweight code snippets for quick integration.docs/– API reference, deployment guidance, and governance resources.benchmarks/– latency and performance tracking.stress_benchmarks/– stress benchmark notebooks plus progressive load and semantic-context result sets.codefest/– Philly Codefest OpenBuild challenge kits, starter notebooks, shared logs, and team operations docs.
The stress benchmarks complement the latency benchmarks by exercising the Inhibitor under heavier load and longer-context prompts.
- Progressive load results – multi-scenario, high-concurrency runs that stress throughput and latency as user counts scale. See the latest report in
stress_benchmarks/progressive_load_results/v1.21.0/README.md. - Semantic context results – low-concurrency runs that validate detection quality across long, semantically rich prompts and large context windows. See the latest report in
stress_benchmarks/semantic_context_results/v1.21.0/README.md.
- Implementation flow – Start with the Inhibitor Application Sprint, then dive into the Reason-Observe-Adjust pattern and the Inside the Inhibitor narrative to see how the oversight loop runs.
- Adoption progression – Follow the typical Inhibitor adoption progression to sequence confidence calibration, schema hardening, error prevention, and auditability.
- Case studies – See how the inhibitor performs in production with the healthcare case impact report.
- Policy to runtime – Trace how written policies become DILL rules in the policy-to-rule examples, then compare enforcement outcomes in the API reference and supported regulations.
- Governance and compliance – Pair GDPR guidance with global edge deployment and zoom out to the ethical inference theory that underpins the system.
- Change history – Review release notes 1.3 for Codefest event enablement updates, release notes 1.2 for documentation and benchmark updates, or release notes 1.1 for earlier onboarding improvements.
- Walk the full implementation playbook: Inhibitor Application Sprint.
- Need help or an enterprise key? Visit appliedAIstudio.