AI-Native Analyse Deck Early Access
Two products · One graph · Open Source

The future of software is AI‑native.
Understanding the past is
how you build it.

Promin builds the missing layer between what your software is supposed to do and what it actually does — a knowledge graph that both engineers and AI agents can read.

ROADMAP
Promin AI‑Native

Infrastructure for AI-native development. Requirements, code, tests, and data connected through a living knowledge graph.

Explore
Pre-Alpha
Promin Analyse

Software archaeology layer. Ingests your git history and surfaces why code exists — not just what it does.

Explore

You automated the doing.
Nobody automated the understanding.

The gap between documented intent and actual implementation is where bugs, rework, and wasted effort live. Modern stacks have four disconnected layers — and none of them talk to each other.

01
Requirements
Capture intent, then abandon it

Jama, DOORS, PRDs — they record what you wanted. Then the doc rots while the code moves on without it.

02
Code
Execute without understanding context

Copilot, Cursor, Devin — they write code fast. But they have no idea what the code is for or what it might break.

03
Tests
Verify behaviour without questioning necessity

Tests confirm behaviour. They can't tell you whether that behaviour should exist at all.

04
Analytics
Rearview metrics disconnected from steering

Amplitude, Mixpanel, PostHog — they show what happened. Not what was supposed to happen.

Knowledge graph
See your system the way it actually is

A queryable directed graph that connects requirements to code to tests to data. Discovers contradictions, traces impact, and finds orphaned goals — automatically.

promin — ingest
promin ingest ~/dev/lumin-next   stage 1 Walking commits... 100 commits stage 2 Extracting symbols... 988 symbols stage 5 Grouping features... 34 features stage 6 Detecting decisions... 11 decisions stage 6a Inferring decisions... 3 implicit (14 total) stage 8 Running signals... 3 high · 2 low   ✓ graph built nodes: 1,045 edges: 3,291
Intake gate PLANNED
No feature enters unquestioned

Every new capability is matched against the existing graph. Promin surfaces overlap, missing goals, and confidence gaps before a single line is written.

Discovered features
export_csv
94%
AuthMiddleware
91%
rate_limit
87%
bulk_export
72%
legacy_mailer
34%
Drift detection PLANNED
Watch the drift happen in real time

Bidirectional mapping between features and code. When they diverge, Promin flags the drift with affected features, severity, and suggested resolution.

Coherence monitor — live
Auth Module
94%
Export
88%
Search
67%
Legacy API
23%
Autonomous oversight PLANNED
The loop that never sleeps

The Conductor monitors every codebase change, checks it against the knowledge graph, and surfaces divergences. Autonomous system oversight without manual dashboard checking.

conductor — watching
14:23:01 push feat/export-v2 — coherent 14:23:44 push fix/auth-token — drift +3% → AuthMiddleware.refresh deviates from decision "token refresh strategy" 14:25:12 push chore/deps — no impact 14:27:08 push feat/bulk-delete — conflict → overlaps with soft_delete (68% shared logic)   watching...

From AI‑assisted
to AI‑native.

AI-assisted development keeps humans as the relay between intent and code. AI-native development puts structured intent at the centre — and lets agents execute from it.

AI-Assisted
Human relay
  • Requirements written, then forgotten
  • Developer translates intent to code
  • AI autocompletes without context
  • Tests verify what, not why
  • Drift discovered in production
build forward · understand backward

Your code says what.
Promin finds why.

An archaeology layer for your codebase. Promin Analyse ingests your git history and surfaces why code exists — so engineers and AI agents stop breaking things they don't understand.

Recoverable
The What
  • Method signatures & structure
  • Test assertions & coverage
  • Call graphs & dependencies
  • Git blame & file history
  • Runtime behaviour
The Gap
Usually gone
The Why
  • Original design intent
  • The constraint this enforces
  • What would break if removed
  • The decision that was rejected
  • The author who understood it

Archaeology findings,
delivered automatically.

Every time Promin ingests a commit, it runs the signal engine. These are the patterns it looks for.

🔴
finding
Orphaned Tests

Tests with no matching source code. The code they guarded was deleted or moved, but the tests stayed behind — asserting things about ghosts.

🟡
finding
Intent Drift

A feature has evolved away from its original commit rationale. The code says one thing, the history says another. The gap is where bugs hide.

🔵
finding
Why Void

High-confidence feature, zero explanatory context anywhere in the history. Someone knew. Now nobody does.

⚰️
finding
Extinction Candidate

Dormant feature, no recent activity, no external references, no tests. Probably dead — but verify before deleting.

🔗
finding
Silent Coupling

Two modules that co-evolve in 70%+ of commits but have no documented relationship. Hidden debt with blast radius nobody has mapped.

👻
finding
Decision Erosion

An explicit decision from history no longer matches the current implementation. The constraint was forgotten. The code moved on without it.

👤
finding
Author Bus Factor

One person wrote 80%+ of a feature's commits. If they leave, nobody else understands the code. Knowledge concentrated in a single head.

🏗️
finding
Load-Bearing Complexity

Heavily mutated code with no documented rationale. Changed dozens of times, nobody wrote down why. The most dangerous code in your repo.

🧪
finding
Stale Test

Test file untouched for months while the code it covers kept changing. The assertions are frozen in time — probably testing yesterday's behaviour.

🕳️
finding
Test Decision Gap

An explicit architectural decision exists but no test verifies it holds. The constraint lives only in a commit message — one refactor away from gone.

📄
finding
Tests Without Code

Test files that don't map to any source file. Might be integration tests, might be leftovers from a deleted module. Worth investigating either way.

MCP tools.
One archaeology layer.

Promin runs as an MCP server. Your agent, your IDE, your CI pipeline — all query the same archaeology layer.

why_does_this_exist()
Given a file path or symbol, returns inferred intent, decision lineage, confidence, and churn rate.
Core
impact_of_change()
Describe a proposed change in plain English — get back which features and load-bearing decisions are in the blast radius.
Core
explain_decision()
Given a commit SHA, reconstructs the decision context, what it was satisfying, and whether that decision is still live.
Core
get_signals()
All archaeology signals for a repo or scoped path — orphans, drift, voids, extinction candidates, silent coupling, bus factor, and load-bearing complexity.
Core
get_orphans()
Returns orphaned tests — test files with no matching source code. Tests asserting things about code that no longer exists.
Core
run_features_audit()
Full inventory of every detected feature: status, confidence, lifecycle, coverage, intent fidelity, and suggestions.
Audit
run_coding_audit()
File-level archaeology findings: load-bearing complexity, zombie code, decision erosion, test archaeology gaps.
Audit
Archaeology Debt Score
0.43
example · moderate · run: promin audit <repo>

A single 0–1 scalar measuring how legible your codebase's intent is — to humans and agents alike. Not code quality. Not smells. How well is the why preserved?

Web dashboard
See the graph, not just the data

Interactive knowledge map, commit timeline, signal browser, and full audit view. Six pages, one command, zero configuration.

dashboard
promin serve-web ~/dev/lumin-next   Backend ready http://localhost:8080   pages Overview · Map · Commits · Traceability · Signals · Audit graph D3 force-directed · 5 node types · zoom + filter repo lumin-next · 34 features · 14 decisions · 5 signals

Get early access
to Promin.

Bring a repo, get an archaeology report. We're onboarding early users now.