Every AI you use
is coding blind.

Eidon compresses your entire codebase into a single context graph your AI can read in one shot. Every file, every dependency, every architectural relationship. Your AI finally sees everything.

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Your AI today guessing
What breaks if I change the token expiry logic?
Probably something in the auth flow. I searched the repo but I can't tell you exactly what depends on it.
Your AI with Eidon sees everything
What breaks if I change the token expiry logic?
Don't touch it yet. 11 files depend on it. 3 are untested. Fix the coverage in auth/session.ts first, or you'll ship a silent regression.
The problem

Every AI coding tool
is working from a guess.

RAG search retrieves text fragments. The moment it does, structural relationships are gone. File listing overflows tokens after a few dozen files. Neither approach sees your codebase as a system.

So your AI fills gaps with confident guesses. It's wrong about the things that matter: blast radii, critical paths, what breaks when you change something.

The Eidon approach

Mathematical encoding.
Not search.

Eidon runs deep structural analysis. Not keyword search. Not embeddings. Not summarization. It encodes the result as a compressed graph your AI can consume in a single call. Your entire codebase, understood as a system.

Every architectural relationship preserved. Every dependency mapped. Every risk scored. Nothing sampled. Nothing lost.

Files Raw tokens Eidon graph Ratio
5001 M71 K14×
1,0002 M109 K18×
10,00020 M802 K25×
100,000200 M7.7 M26×
What Eidon sees

It's not one blind spot.
It's all of them.

Every codebase has structural risk hiding in plain sight. Your AI doesn't see any of it.

0 files affected
01 Blast Radius

You rename one utility function.
Your build breaks in 14 places.

Your AI suggests the refactor. It sees the function. It doesn't see what depends on it: the 8 direct callers, the 34 transitive ones, the 0 tests covering any of them.

Eidon maps the full blast zone before you touch anything. Not a guess. A mathematical BFS over the live dependency graph. Every dependent, ranked by cascading risk.

auth/token.ts
891 calls export function validateToken(t: string)
0 calls export function legacyTokenParser(raw)
AI writing docs…
0 calls export function parseTokenV1()
02 Dead Code

Your AI is writing docs
for functions nobody calls.

Dead code isn't just wasted lines. It's active noise. Your AI includes zombie functions in its analysis, refactors them, documents them. On every run.

Eidon's AI Court verifies dead code with hard evidence. Zero call edges in the graph. Zero imports from other modules. Cross-checked. Not a heuristic. A verdict.

.env
DATABASE_URL=postgres://…
PORT=3000
JWT_SECRET=••••••••
api/client.ts
process.env.DATABASE_URL
process.env.PORT
process.env.OPENAI_API_KEY NOT DEFINED
process.env.STRIPE_SECRET NOT DEFINED
03 Config Intelligence

Your app uses 12 env vars.
Your AI knows about 3.

.env files are gitignored, invisible to your AI. It writes code referencing variables that don't exist in production. Silent failures. Runtime crashes. Missing docs.

Eidon scans every process.env reference across your entire codebase and cross-maps it to your env files. Missing vars flagged. Critical vs optional, ranked.

refactor: extract auth utilities
→ main
typecheck 8s
unit tests 42s
eidon gate 0.4s
BLOCKED src/auth/token.ts risk 94 · SPOF · blast: critical · 0 tests
Merging this breaks 47 downstream files. Exit 1.
04 CI Risk Gate

Types pass. Tests pass.
You ship a bomb to main.

Your CI checks syntax and logic. It doesn't check if the changed file is a single point of failure with 47 dependents and zero test coverage. A green checkmark isn't safety.

One line in your CI config. eidon gate runs in under a second, reads from the context brain, exits 1 if structural risk exceeds your threshold. No new infrastructure.

Works inside the tools you already use

  • VS CodeVS Code
  • CursorCursor
  • Claude CodeClaude Code
  • GitHub CopilotCopilot
  • WindsurfWindsurf
  • NeovimNeovim
  • ClineCline
  • CodexCodex
How it works

Not RAG.
Not summarization.

01

Local-first by default.

Eidon analyzes your repository on your machine and carries that structural state into your AI workflow. No remote indexing layer. No hidden cloud copy. Your code stays yours.

02

11 layers of analysis. One graph.

Architecture, dependencies, risk, error propagation, test coverage, git history. Eidon compresses it like JPEG compresses images. Your 6,500-file project becomes 12,000 tokens of pure structure.

03

Your AI gets the right slice.

Eidon plugs into every AI tool via MCP. Token limits still exist, but Eidon picks exactly what matters. Ask "what breaks if I change this?" and get a real answer.

Daily workflow

Four commands.
Zero guesswork.

Run eidon analyze once. These four run in under a second, every time after.

Before every session eidon doctor

Health score, top risks, SPOFs, test gaps. Know the exact state of your codebase before the first line of AI output.

health7.2 / 10
spofs3 detected
untested12 exports
Before every commit eidon review

For each changed file: blast radius, SPOF status, test coverage, active findings. Structural data, not opinion.

src/utils/auth.ts
risk91/100 · SPOF
blast8 direct · 31 trans
In every CI pipeline eidon gate

Structural risk gate for CI/CD. Exits 1 if a changed file crosses your risk threshold. Blocks the PR. One line.

✗ src/db/client.ts
risk88 > 75 (threshold)
PR blocked, exit 1
After every sprint eidon diff

Baseline your architecture. Then measure drift: Fiedler value, entropy delta, SPOF count, community fragmentation.

λ₂0.14 → 0.08 ↓
H(G)3.2 → 3.8 ↑
spofs2 → 5 ↑
This is not RAG. Not summarization.
This is your codebase, understood.
Security

Your code
stays yours.

Enterprise teams choose Eidon because your code never touches our servers. Every byte stays on your machine.

100% local

All processing happens on your machine. LLM calls go from you to your provider. OpenRouter, OpenAI, Anthropic, or Ollama.

Zero telemetry

No analytics. No crash reports. Eidon never phones home. Nothing is tracked.

SHA-256 verified binaries

Every release ships with a SHA-256 checksum. The installer verifies it before writing anything to disk. Tampered binaries are rejected before they run.

Pricing

Free to start.
Always.

Community

$0/forever

For personal projects. No time limit.

  • All IDE integrations
  • Local codebase indexing
  • MCP + CLI + LSP
  • Bring your own API key
Join waitlist
Most popular

Pro

$29/mo

For devs who need the full power.

  • Everything in Community
  • Private repos
  • Advanced risk scoring
  • Git history analysis
  • Priority support
Request Pro access

Enterprise

Custom

For teams with secrets to protect.

  • Everything in Pro
  • On-prem deployment
  • SSO / SAML
  • SOC2 / GDPR compliance
  • Dedicated support
Contact sales
FAQ

Common
questions.

Why does my AI give bad answers about my project right now?+

AI tools like Copilot and Cursor only read the files you have open. On a project with hundreds or thousands of files, that means they're mostly guessing. Eidon solves this by building a full index of your codebase and serving it to your AI on demand.

Does my source code leave my machine?+

Never. Eidon builds its index entirely locally. Your source code is never sent to us. The only external calls are from you to your LLM provider (OpenRouter, OpenAI, Anthropic, or a local Ollama instance).

My repo has 50,000 files. Will it still work?+

Yes. Eidon uses a tiered indexing system designed for large monorepos. It prioritizes the most relevant files and compresses intelligently to fit within your AI's context window.

How do I get access?+

Eidon is in early access. Sign up and we will open access in waves. When your spot is ready, we will send the onboarding details. The benchmark study and exact transcript are public right now.

Get early access.
Read the proof.

Eidon is opening in waves. Sign up to get launch updates, early-access availability, and the public benchmark dossier in one place.

Early access waves

We are not blasting generic signups. Access opens in controlled batches.

Local-first product

Your repository stays on your machine. The public evidence is the study, not your code.

Serious launch surface

The study, transcript, and product story are public now. Skeptics can inspect the record themselves.