qortex
2026A knowledge layer for AI agents that improves with every correction
A protocol-driven knowledge and learning layer. Retrieval combines vector similarity with Personalized PageRank over a typed-edge knowledge graph; a Thompson Sampling bandit on top learns from accept and reject feedback instead of staying frozen.
Install it as an MCP server or call the same surface over REST. One backend protocol runs it anywhere: SQLite on a laptop, Postgres + pgvector or Memgraph in production.
Every phase is instrumented. OpenTelemetry spans and Prometheus metrics feed Grafana, so you can watch the agent learn and catch it when it learns the wrong thing.