I’m sharing Kakveda, an open-source project that explores failure intelligence for LLM and agent-based systems.
Most observability tools help analyze failures after they happen. Kakveda treats failures as first-class entities that can be remembered, matched, and used to warn before repeating known failure modes.
Key ideas: - Global Failure Knowledge Base - Deterministic failure fingerprints - Pre-flight “this failed before” warnings - Failure pattern detection - System health scoring over time
The project runs locally via Docker Compose and does not require a hosted service.
Docs: https://kakveda.com
I’d appreciate feedback on the architecture and ideas.