Corvic AI
The enterprise knowledge backend for your agents
Corvic AI launched on September 8, 2026 with 14 votes, #893 of 8,094 launches that month and more than 90% of that year's launches.
What it does
Your agents are only as smart as the context you give them. Corvic AI turns your messy, scattered data: Slack threads, PDFs, docs, databases into a living knowledge backend: relational knowledge graphs with Memory, structured extraction with Lens, and grounded context served straight to your LLMs through MCP. Less hallucination, more real answers. Then build dashboards and custom apps on top, with no separate database and no extra infra to manage.
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A Karpathy-style LLM wiki your agents maintain (Markdown and Git)Apr 2026 · github.com · ▲260I shipped a wiki layer for AI agents that uses markdown + git as the source of truth, with a bleve (BM25) + SQLite index on top. No vector or graph db yet. It runs locally in ~/.wuphf/wiki/ and you can git clone it out if you want to take your knowledge with you. The shape is the one Karpathy has been circling for a while: an LLM-native knowledge substrate that agents both read from and write into, so context compounds across sessions rather than getting re-pasted every morning. Most implementations of that idea land on Postgres, pgvector, Neo4j, Kafka, and a dashboard. I…

Cognitora2025 · cognitora.dev · ▲86Built a multi-agent research system with OpenAI Agents SDK where specialized AI agents collaborate autonomously: Master Orchestrator → Data Analyst → Statistician → Report Writer Each agent has specific expertise. The orchestrator delegates tasks. All agents can execute code securely to solve problems. Example workflow: "Analyze e-commerce data" - Data Analyst: writes Python to load/clean data, spots trends - Statistician: performs significance tests, calculates growth rates - Report Writer: synthesizes findings into executive summary This demonstrates OpenAI Agents SDK's handoff system…


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