Alternatives
Products that do what FinalFlagger does
India’s 1st Decision Safety Platform for Commitments
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I built this as a personal open-source project to explore how EU AI Act requirements can be translated into concrete, inspectable technical checks. The core idea is local-first compliance: – risk classification (Articles 5–15, incl. prohibited use cases) – bias evaluation using CrowS-Pairs – automatic Annex IV–oriented PDF reports – no cloud services or external APIs (browser-based + Ollama) I’m especially interested in feedback on whether this kind of technical framing of AI regulation makes sense in real-world projects.
Jan 2026 · github.com
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We're excited to launch compliant-llm: an open-source toolkit that helps infosec and compliance teams audit AI agents against regulatory frameworks like NIST AI RMF, ISO 42001, and OWASP Top 10. Infosec and compliance teams are now responsible for tracking security and compliance risks of a growing number of AI agents across external and internal apps and third-party vendors. compliant-llm gives you a way to: - Define and run comprehensive red-teaming tests for AI agents - Maps test outcomes to compliance frameworks like NIST AI RMF - Generate detailed audit logs and documentation -…
2025 · github.com
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I got tired of slogging through walls of legal text whenever I had to sign something important, so I built a Chrome extension that uses AI to: - Spot red flags and suspicious clauses – It automatically highlights risk areas in real-time as you read through an online contract. - Score the contract’s safety – Based on industry-standard risk parameters, it gives you an at-a-glance score so you can see how risky the document might be. - Simplify the jargon – It generates a quick summary of the key points, saving you from reading every paragraph in detail. No more signing on hunches or bets!…
2025 · aayen.org
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Find out if your AI system is high-risk under the EU AI Act
Jul 2026 · ishighriskai.com
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- 20AT
We kept shipping “simple” LLM features that were fluent-but-wrong. After too many postmortems we wrote down the failure patterns and added a small reasoning layer in front of the model. It’s model-agnostic, sits beside your existing stack, and you can implement it from a single PDF (MIT). What’s inside the PDF A problem map of 16 failure modes we kept hitting in real systems (OCR/layout drift, table-to-question mismatches, embedding≠meaning, pre-deploy collapse, etc.). Four lightweight gates you can add today: Knowledge-boundary canaries (empty/adversarial/known-fact probes).…
2025 · github.com
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Classify. Assess. Document. Full compliance with EU AI Act
4d ago · share.streamlit.io
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riskline▲1Open-source EU AI Act risk engine, deterministic & auditable
Aug 2026 · new-world-coder.github.io
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