#reliability

Mindlas catches your coding agent drifting before the bad code lands. Real-time tracking and correction for context rot, unverified done claims, patch sprawl, and tool loops in your Claude Code session.

Reliability for LLM agents through enforcement, not model size — Agent-Contract-Kernel + a fail-closed orchestration engine. Model-agnostic. 🇦🇪 Built in the UAE.

AI-agent reliability and governance layer: auto-firing compliance checks, persistent memory, security scanning, and verification loops that wrap any AI agent.

Self-hostable LLM inference gateway: policy routing with fallback chains, circuit breakers, semantic caching, per-tenant cost accounting, and Prometheus metrics.

Do your agent pipeline's own checks catch planted faults? Measured on LangGraph, CrewAI and AutoGen: median 16.7%. One prompt-level change takes it to 55.0%. Pre-registered spec, Apache-2.0 harness, every raw trace published.