Understand how your software is built, and how it changes
Humans and agents both work on your codebase now, and both need the same picture of how it fits together and what has moved. SourceAnt keeps that picture and serves it to whoever is working.
Every change judged against the decisions, constraints, and contracts your system actually has, not against the diff alone. Velocity stops costing you trust.
Watch coverage and architecture drift against real code churn, so direction is a decision your team makes rather than something you discover after the fact.
Open core and self-hostable, priced on usage rather than seats, bring your own keys. The graph stays private to your workspace and travels to every tool over MCP.
Self-host free · No credit card to try the cloud
The daily reality
AI made code cheap to write and expensive to trust.
On a large, critical codebase, velocity now outruns anyone’s ability to hold the architecture in their head, judge a change against the real system, and ship it safely.
-
The why lives in people’s heads, and they are outnumbered
Agents open more changes in a day than your seniors can trace back to the decisions behind them. The reasoning that keeps the system correct never made it out of a Slack thread or a closed PR.
-
The system outgrows anyone’s grasp, and quietly drifts
It gets bigger and more AI touches it, until no one holds the whole shape anymore. It keeps changing in a direction nobody deliberately chose, and you only notice once it is hard to undo.
-
Quality and reliability slip as you scale AI
The more you ship with agents, the more workarounds get reverted, conventions drift, and contracts break. Trust in the codebase erodes right when you are moving fastest.
-
Your AI spend climbs and the context never sticks
Every session re-explains the same architecture, burning tokens and per-seat fees, and none of it is captured for the next engineer or the next agent.
Teams that capture the why compound understanding with every change. Teams that do not ship faster into a system they understand less each week.
One platform
One knowledge layer, many jobs on top
SourceAnt captures how your codebase works and serves it everywhere, so your tools and your team act on real understanding instead of skimming files.
Context that persists
Decisions, constraints, workarounds, conventions, and patterns captured once and governed by your team, so the why behind your code never has to be re-explained.
A graph, not guesswork
Your code, contracts, and decisions linked into a typed knowledge graph, so tools and people follow real relationships and see what a change actually touches.
Applications on top
Put the knowledge to work: review that checks a diff against real decisions and blast radius, issue triage that dedupes and auto-labels, and analytics on quality, coverage, and spend.
Lower token bills
Serve only the relevant slice of the graph instead of whole files or full history. Fewer tokens, sharper answers, and AI spend you can actually see and control.
The whole system
Capture the knowledge once. Put it to work everywhere.
One living map of how your system works: your team sees where it is heading and steers it, your agents build with the full context, and the jobs you rely on run on top.
Understand your own system, and keep your agents on it
SourceAnt captures the decisions, constraints, contracts, and conventions behind your code and structures them into a living map of how your system actually works, one that stays current as the code changes.
For your team
See how the system is built, how it is changing, and where it is heading, so you catch drift early and decide whether that is the direction you want before it is baked in.
For your agents
The relevant slice is served back over MCP the moment an agent acts, so it builds with the full why instead of guessing at it.
Context-aware review
Check each change against your real decisions and its blast radius, so the bugs that read fine and the workarounds it wants to delete get flagged before they merge.
Issue triage
Duplicate detection and intelligent auto-labeling on issues and PRs, so your backlog stays deduped and routed without hand-sorting.
Engineering analytics
See token usage and savings, review quality, context coverage, and triage stats, so you can watch reliability and AI spend as you scale.
Portable
Works with the tools you already use
SourceAnt speaks MCP, so your context and every application show up in whatever your team codes with. And it is not just for humans: agents query the knowledge headlessly, mid-task, without anyone re-pasting context. No lock-in, no new habits.
See it
How your software is being built, and how it is changing
Humans and agents both need the same picture. This is what it looks like in use.
Knowledge, not review output
What your codebase knows about itself
Decisions, constraints, and conventions captured from reviews and pull requests, each tied to the repository it came from. This is the durable asset. Review is one thing that reads it.
Large, complex, critical
A diff means nothing on its own
Group repositories, services, and datastores into the system they actually form. Every edge keeps the file it was read from, so a reviewer can check a claim instead of trusting it.
Cross repository
Your frontend and backend, reviewed as one system
Detected relationships wait until a person confirms them. Nothing enters the confirmed graph because a model felt sure.
Humans stay in charge
Triage what your code learned, like email
Each proposal arrives with its reasoning, its confidence, and the paths it applies to. Approve, edit, or reject. The graph moves when you move it.
Three delivery channels
Preview it to yourself before GitHub ever sees it
Run a review on any open pull request and read it here first, or post it. GitHub delivery is unchanged and needs no migration.
Risk position
Where the risk sits, before you read a line
A risk position composed from evidence, with the files nobody needs to open marked as such, and claims held open until someone signs them.
Evidence, not opinion
Every claim shows its work
Read the whole change with the reasoning beside it, anchored to the lines that provoked each claim. Dismiss one and the reasoning stays on the record.
Served over MCP
The context your agent is missing
Files, systems, and contracts with the decisions that explain them, served to whatever assistant you already use. Bring your own keys. The graph stays yours.
Where it is heading
See the architecture drift before it becomes a rewrite
Coverage and capture tracked against code churn week by week, so you can see whether understanding is keeping up with change.
How it works
A graph, not a pile of text
Capture the why, link it into a knowledge graph, and serve only the relevant slice to any AI tool the moment it acts.
1. Capture
Decisions, constraints, workarounds, conventions, and patterns are extracted from reviews, sessions, and discussions, captured automatically as proposals your team curates on its own schedule.
2. Structure
Everything is linked into a knowledge graph, code to decisions and decisions to each other, so retrieval is precise.
3. Serve via MCP
Any AI tool queries the relevant slice before it acts. No re-explaining, no context-blind suggestions.
Drag to rotate
In practice
The decisions your agent would otherwise undo
An assistant reads the code in front of it. It cannot read the incident that set the retry limit, or the discussion that ruled out jitter. SourceAnt hands it both before it writes.
An assistant is asked
Refactor the payment retry logic to use exponential backoff.
src/payments/retry.ts
SourceAnt answers with what that code already decided
Max retry stays at 3. Higher values caused duplicate charges once already.
Jittered backoff did not survive the rate limiter. The fixed delay is deliberate.
Idempotency keys are generated client-side. Changing that breaks the mobile app.
It ships the backoff and leaves the retry ceiling, the fixed delay, and the idempotency key where they are.
Served over MCP, so this works in whichever assistant your team already uses.
Illustrative example
Why SourceAnt
Why not comments, ADRs, a vector database, or another per-seat review bot?
Structured, not prose. Context is typed and linked in a graph, so tools retrieve the exact slice instead of grepping comments that have gone stale.
Governed, not hallucinated. Knowledge carries a status your team controls and your tools filter on: approval marks what the team vouches for, and it never queues capture behind a person. A vector store just guesses.
Portable and private. Served over MCP to any tool, open source you can self-host, with your own model keys. Your knowledge and your AI spend stay on your side, never in a vendor’s silo.
Priced for how you actually work. Usage-based and bring-your-own-key, one flat team price, no per-seat AI tax as you add engineers or agents.
Who it's for
For teams shipping fast with AI on code that cannot break
You run a large, critical codebase, you move at the pace of your agents, and you care as much about architecture and reliability as about velocity. You self-host, you want usage-based pricing and your own keys, and you need humans to keep understanding the system, not just the code.
The architect holding the why
You are the reason the system still hangs together. SourceAnt gets the decisions, constraints, and contracts out of your head and into a graph every tool and teammate can query, so the architecture survives the pace you are shipping at.
The platform lead who self-hosts
You run this on your own infrastructure, with your own keys, and you watch the AI bill. SourceAnt is open source, priced on what it analyses rather than on seats, and private by default, and it cuts tokens by serving only the slice a task needs.
The engineer on the hook
You are accountable when an agent’s change breaks production. SourceAnt judges each change against the real system and hands your tools the reasoning behind the code, so speed does not cost you trust.
Keep understanding your codebase at AI speed
Self-host the open-source core for free, or start SourceAnt Cloud at $49 a month. Every engineer and every agent you have, for the same price, with your own model keys if you want them.