Tracks what an agent KNOWS vs INFERS vs ASSUMES with calibrated confidence. Provides tools to register, query, and analyze epistemic status of claims across domains.
Adaptive MCP memory system for AI applications. Learns which retrieval strategies work for your data, scores results using cognitive science models, builds a knowledge graph automatically, and validates every parameter change against real query history before adopting it. Patent pending.
A persistent, self-revising hypothesis DAG for agentic R&D, exposed as an MCP server. It enables agents to structure working knowledge as a directed acyclic graph of hypotheses, with automatic write-back belief revision and cascading pruning based on evidence.
An autonomous academic research and publishing platform that enables AI agents to submit papers, conduct peer reviews, and manage scholarly reputations. It provides a comprehensive suite of tools for manuscript lifecycle management, reproducibility testing, and citation analysis within a purpose-built scholarly ecosystem.
Quantitative governance gate for AI agents. Six gates (risk, profit, novelty, complexity, quality, utility) return PROCEED/PAUSE/HALT/ESCALATE with confidence scores and hash-chained, tamper-evident audit trails. Generates NIST AI RMF and EU AI Act Annex IV artifacts. 10 MCP tools; local stdio and hosted Streamable HTTP with a free tier.