Archynt vs CodeSee
CodeSee is gone. If you landed here looking for a replacement, here's the part Archynt covers and the part it doesn't.
GitKraken acquired CodeSee in May 2024 and folded it into a developer experience platform. The standalone product was sunset: codesee.io no longer serves a site, and the application is behind an internal access gate. If you were a CodeSee user, or you're finding this because a bookmark broke, that's the situation.
The official continuation is GitKraken's own platform, and if what you want is CodeSee's capabilities under new ownership, that's where to look first rather than here. What follows is only useful if you're reconsidering the category rather than looking for a like-for-like port.
What Archynt does not replace
CodeSee's code tours — curated, annotated walkthroughs where a senior engineer records the path through a feature so a new hire can follow it — have no equivalent in Archynt, and we're not planning one. That was a genuinely good idea and it was CodeSee's own. If tours were the reason you used it, nothing on this page is going to substitute for that.
The same goes for the granularity. CodeSee mapped files and modules, down to the level of which function called which. Archynt's graph is coarser by design: services, components, endpoints, datastores and the dependencies between them. For "help me understand this unfamiliar file," an IDE and a call hierarchy will serve you better than we will.
Where the overlap actually is
If what you valued was not having to draw the map — that the picture came out of the code instead of out of somebody's afternoon in a diagramming tool — that's the same premise Archynt is built on, one level up. It parses Java/Spring, Node/NestJS, Python and Go repositories into an architecture graph and renders C4 diagrams from it, with no manual modelling step.
The part CodeSee never had is the runtime side. A read-only agent with no application instrumentation observes what actually talks to what in a live environment and correlates it back to the code graph, so every dependency carries a tag: seen in the code, seen in production, or both. A static map can only ever show you what the code claims. The gap between that claim and what the system does is where the expensive surprises live.
| Capability | Archynt | CodeSee |
|---|---|---|
| Available as a product today | Discontinued | |
| Map generated automatically from code | ||
| Level of the map | Services and components | Files and modules |
| Visualization tied to a pull request | ||
| Guided code tours for onboarding | ||
| Runtime topology discovery | ||
| Code ↔ runtime drift detection | ||
| C4 model diagrams | ||
| CI gate that can fail a build |
If you're evaluating the category again
The useful question after a tool you depended on gets acquired is usually not "what's the closest clone" but "what was I actually buying." If it was onboarding and code comprehension at the file level, look at GitKraken, or at your IDE, and be skeptical of anyone selling you an architecture platform for that job. If it was keeping an accurate picture of a system too big to hold in one person's head, that's the problem Archynt exists for, and the runtime correlation is the part worth evaluating.
Want to see this on your own system?
A repository URL is enough for the static graph. The runtime agent takes one docker-compose file.