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Engineering Wiki

A codebase wiki that writes itself.

Entelligence indexes your repos, incidents, and coding sessions to build a comprehensive engineering wiki for your org. Architecture docs, runbooks, error pattern guides, and skill insights: always current, never manual.

engineering-wikiauto-generated
ARCH
payments/retry.ts: Retry Strategy OverviewUpdated from PR #4821 · 2 patterns linked
auto-doc
RUNBOOK
Incident Response: connection pool exhaustionSourced from INC-892, INC-1041 · 3 steps
from incidents
PATTERNS
Error pattern EKU-4471: idempotency timeout7 occurrences · root cause documented
active
SKILLS
Top skill gap: context reuse in long sessionsAffects 4 engineers · recommendation attached
insight
ARCH
auth/middleware.ts: OAuth 2.0 flowUpdated from PR #5102 · last modified today
auto-doc
100%of docs generated automatically from your real codebase
0 hrsof manual documentation required from your team
Alwaysin sync, wiki updates when your code and incidents do
The Problem

Your codebase is undocumented. Your agents pay for it every day.

Architecture decisions live in Slack threads. Runbooks go stale. New engineers spend weeks asking questions no one has written down.

Searching for docs that don't exist4.2 hrs/wk
Onboarding takes weeks, not days3–6 wks
Runbooks written once, never maintained+40 min/incident
Same incidents, rediscovered from scratchrecurring
Tribal knowledge walks out the doorirreversible
72%of engineering docs are stale within 6 months
3–6 wksaverage onboarding without a living wiki
4.2 hrslost per engineer per week to missing docs
0 hrsof manual writing required with Entelligence
Context at every stage

The right knowledge injected at every stage of the pipeline.

Coding agents are only as good as the context they have. The wiki feeds generation, review, and incident response with exactly what's needed at each stage.

1
Code Generation
46% fewertokens per generation session

Fewer tokens. Better first drafts.

The wiki feeds existing patterns and module context to your agent upfront, so it generates closer to correct without wasting tokens reinventing what already exists.

Context injected by wiki
payments/retry.ts: existing backoff patternarch-docs
withConnection(): established pooling patternarch-docs
EKU-4471: idempotency timeout, avoid this patternincident-patterns
2
Code Review
3x fasterreview cycles on high-risk changes

Catches issues that have happened before.

The wiki surfaces matching incident patterns for the code being reviewed. Known failure modes get flagged before they merge, not after they page someone.

Context injected by wiki
EKU-5120: race condition in concurrent retriesincident-patterns
PR #2841: conn.acquire() leak, same patternincident-history
Runbook: connection pool exhaustion linkedrunbooks
3
Incident Mitigation
68% fastermean time to resolution

Root cause in seconds, not hours.

When an incident fires, the runbook and past root causes are already in context. Your agent starts from a known baseline instead of blank, cutting MTTR from hours to minutes.

Context injected by wiki
Runbook: connection pool exhaustion, 3 stepsrunbooks
EKU-3892: prior root cause at processor.ts:246incident-patterns
Fix history: withConnection() resolved in PR #2842incident-history
What the wiki covers

Four layers of knowledge, built automatically.

From architecture docs to runbooks to skill insights, Entelligence builds and maintains the full knowledge stack your engineering org needs.

Codebase Documentation

Architecture docs that stay current with every PR.

Entelligence reads your repositories and generates structured documentation for modules, services, and key patterns. Every merged PR triggers an update, so the wiki reflects your code, not a snapshot from six months ago.

  • Indexes all repos and maps service dependencies
  • Auto-generates module docs from code structure and PR diffs
  • Links related files, patterns, and prior incidents
codebase-docs / payments
payments/3 modules documented
retry.tsRetry strategy, idempotency, backoff logic
updated
processor.tsConnection pooling, withConnection() pattern
updated
webhooks.tsSignature verification, event dispatch
auth/2 modules documented
middleware.tsOAuth 2.0 flow, token refresh lifecycle
updated
Incident Pattern Library

Error patterns documented the moment they're resolved.

When incidents are triaged and closed, Entelligence captures the root cause, affected files, and fix approach into your wiki's error pattern library. The next engineer who hits the same issue finds the answer in seconds.

  • Root cause, affected code, and fix documented per incident
  • Error patterns grouped by type and frequency
  • Linked to runbooks for immediate response guidance
incident-patterns / active
EKU-4471: idempotency timeout on retrypayments/retry.ts:88 · 7 occurrences · fix documented
high
EKU-3892: connection pool exhaustionpayments/processor.ts:246 · 3 occurrences · runbook linked
resolved
EKU-5120: race condition on concurrent retriespayments/retry.ts:112 · 2 occurrences · fix in review
active
Automated Runbooks

Step-by-step response guides built from real incidents.

Entelligence synthesizes resolution steps from closed incidents and structures them into actionable runbooks. When the same issue recurs, your team knows exactly what to do. No war room needed.

  • Generated from resolved incident timelines, not templates
  • Includes root cause, diagnostic steps, and fix commands
  • Updated automatically when a pattern recurs with new context
runbook / connection-pool-exhaustion
Trigger: latency spike on /payments/processConfirm in Datadog: conn_pool_wait > 200ms
Check active connectionsentelligence incident logs EKU-3892
Identify leak sourcepayments/processor.ts: look for missing withConnection()
Apply fix or rollbackentelligence incident fix EKU-3892 --repo acme/backend
automated
Verify recoveryconn_pool_wait < 50ms for 5 min
Coding Skill Insights

Team-wide skill gaps surfaced from real session data.

Entelligence indexes coding sessions across Claude Code, Codex, and Cursor to surface where your team is losing time. Skill gaps, low-efficiency patterns, and personalized recommendations, all in one place.

  • Per-engineer skill profile built from session history
  • Team-wide gap analysis with specific improvement areas
  • Recommendations updated as sessions and patterns change
skill-insights / team
Context reuse in long sessionsAffects 4 engineers · avg retry rate 18% vs 6% team norm
top gap
Task scoping before promptingAffects 6 engineers · reduces rework by ~30%
gap
Structured output promptingAffects 3 engineers · improves first-pass accuracy
insight
How it works

Connect once. The wiki builds itself.

Entelligence pulls from your existing tools. No manual entry, no templates to fill out. The wiki grows as your codebase evolves and your team ships.

GitHub + Agents01

Connect your repos and tools

Link your GitHub repositories, incident data, and coding agent sessions. Entelligence indexes everything without storing your code.

Auto-generated02

Entelligence builds the knowledge base

Architecture docs are generated from code structure and PR diffs. Incident patterns, runbooks, and skill insights are synthesized automatically.

Always in sync03

The wiki stays current as you ship

Every merged PR, closed incident, and new coding session updates the wiki in real time. Your documentation is always a reflection of your actual system.

Time saved per engineer4.2h/wk

Engineers spend an average of 4+ hours per week searching for documentation that doesn't exist or is out of date. Entelligence eliminates that entirely by keeping the wiki current automatically.

Features

Now supports

agents.md

format

Documentation that never falls behind

AutoDocs automatically generates and maintains your documentation by connecting to your GitHub repository. No more outdated docs, no more manual updates.

Features

Now supports

agents.md

format

Documentation that never falls behind

AutoDocs automatically generates and maintains your documentation by connecting to your GitHub repository. No more outdated docs, no more manual updates.

  • assistant-ui

  • Allocore

  • VECTORIAL

Trusted by engineering leaders across teams

Build unified experience of maintaining code!

Entelligence AI Docs is an advanced documentation engine that automatically generates accurate, structured, and developer-friendly documentation from your codebase.

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Generated from your codebase

How Entelligence Keeps System Documentation in Sync

How Entelligence Keeps System Documentation in Sync

Automatically generate and maintain accurate system documentation directly from your codebase.

One-Click Generation

  • Instantly create full documentation from your codebase.
  • Automatically generate high-level architectural overviews and component relationships.

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Real-Time Collaboration

Changes made by one user are instantly reflected across all team members' views, ensuring consistent and collaborative editing.

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Manual Edits

You can directly modify or enhance any AI-generated section. Edits are preserved across regenerations when possible.

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We raised $5M to run your Engineering team on Autopilot

We raised $5M to run your Engineering team on Autopilot

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Production reliability, solved.

The AI engineer that reviews every PR against your incident history, watches production, and self-heals when things break. The same class of bug will not ship twice.

Talk to Sales

Production reliability, solved.

Connect with our team to see how Entelliegnce helps engineering leaders with full visibility into sprint performance, Team insights & Product Delivery

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