Fewer surprises between the diff and production

Two costs quietly dominate an engineering org: the months it takes a new hire to become productive in a codebase nobody fully remembers, and the regressions that ship because a diff looked small but its consequences weren't. Graphify attacks both with the same primitive — an on-device knowledge graph of the codebase that engineers and their AI assistants query instead of grepping.

The problem: understanding is the bottleneck

Your team's AI assistants generate code faster than ever; understanding the existing system hasn't sped up to match. Onboarding still means weeks of building a mental map. Review still means a human guessing how far a change propagates. And the assistants themselves rediscover the architecture from scratch every session, paying for the same file reads again and again across the whole team.

What ships today — open source, free

The core is an MIT-licensed CLI, live now. It parses the codebase on-device into a graph where every edge carries provenance: EXTRACTED straight from the AST, INFERRED where a model connected docs or schemas to code, AMBIGUOUS where the evidence couldn't be resolved — flagged, never silently guessed (see how it works). Concretely, for your org:

• Onboarding from a generated map.Each repo gets an interactive graph and a report naming its communities, god nodes, and surprising connections — the architecture overview that's usually stale by the time it's written. Details in use cases.
• Blast radius before the merge."What breaks if I change this?" becomes a traversal query with a traceable answer, and graphify prs puts open PRs in context of what they actually touch — the question behind most production incidents, answered before the incident.
• Lower assistant spend. Assistants that query the graph receive the relevant nodes and edges instead of whole files — retrieval cost paid once at parse time, not per session per engineer, across the 17 assistants your team already uses.

Because it's a local CLI with no account and no telemetry, one engineer can validate it this afternoon — the quickstart is one install command — and the core is free, without an enterprise asterisk.

The enterprise layer — honestly: early access

For teams that want the graph doing work at the org level, Graphify Enterprisebuilds on the same graph: verification at the merge gate (changes proven to preserve behavior, or flagged precisely — never a false all-clear), graph-aware code review, a daily engineering digest, and a Jira connector that links tickets and decisions into the graph. All of it deploys self-hosted in your VPC. To be clear about maturity: this layer is in early access, rolling out to a first design-partner cohort — it is not GA, and we'd rather tell you that here than on a sales call. The security page covers the data-flow model, including SOC 2 Type II being in progress for the enterprise track.

What it won't do

Graphify won't give you developer-productivity dashboards or DORA metrics — it's a codebase map, not a measurement platform. It doesn't make weak models strong, and the open-source core enforces nothing; it informs. If your codebases are small enough for an assistant to read whole, the graph isn't worth the ceremony yet.

Where to start

Have one team run it on your gnarliest repo (docs) and judge the generated report against what your senior engineers know. If the enterprise layer is the interesting part, early access starts with a scoping call — deployment, data flow, and success criteria mapped together before anything is set up.