Session Graph

session-graph

Turn your scattered AI coding sessions into a queryable knowledge graph.

The Problem

Developers use 5+ AI tools every day -- Claude Code, ChatGPT, Cursor, Copilot, Grok, DeepSeek, Warp. Each session is an isolated silo. Knowledge dies when the tab closes.

You have solved the same problem three times across different tools and cannot find any of them. You debugged a Supabase auth flow in Claude Code last Tuesday, discussed the same pattern in ChatGPT a month ago, and asked Grok about JWT refresh tokens somewhere in between. None of these tools talk to each other.

Existing solutions are single-platform and flat-file. They give you search over one tool's history, not structured relationships across all of them. A grep over session logs does not tell you that FastAPI uses Pydantic or that Neo4j is a type of graph database. It just gives you walls of text.

session-graph fixes this.

The Solution

session-graph extracts structured knowledge triples -- (subject, predicate, object) -- from all your AI coding sessions, links entities to Wikidata for universal disambiguation, and loads everything into a SPARQL-queryable triplestore with full provenance back to the source conversation.

The key insight: a knowledge graph without relationships is just a tag cloud. The minimum viable extraction unit is (subject, predicate, object), not [topic1, topic2, topic3].

What makes this different

- Multi-platform: Ingests Claude Code, ChatGPT, DeepSeek, Grok, and Warp into a single unified graph. No other tool does this.
- Formal ontology: Composes 5 W3C/ISO standards (PROV-O, SIOC, SKOS, Dublin Core, Schema.org) instead of inventing a custom schema.
- Wikidata linking: Entities are disambiguated against 100M+ Wikidata items via owl:sameAs. "k8s", "kubernetes", and…