Platform

A living graph of your entire
engineering system

Bito indexes your code, business context, and tribal knowledge into a single knowledge graph so every agent reasons like your best architect.

What your best architect knows available to every agent

Sources feed the knowledge graph. The graph powers agents through MCP. Agents deliver skills to every phase of your engineering workflow.

Layer 1 - Ingestion

Data sources

Indexing & analysis

LAYER 2 - INTELLIGENCE

Knowledge graph

MCP

LAYER 3 - EXECUTION

Agent ecosystem

Agent skills

Layer 4 - Value

Skills & use cases

160+ data points across 15+ dimensions

Traditional RAG retrieves text chunks. Bito’s knowledge graph understands how your system is actually built.

Each repository is analyzed across 160+ data points spanning 15+ dimensions, from service topology and dependency graphs to architectural patterns, implementation standards, and deployment context.

Topology & dependencies

Typed, directional graphs covering API calls, database connections, and message queues across all repositories.

Architectural patterns

Detects event-driven architecture, microservice decomposition, and shared-library structures with confidence scoring.

System clusters

Automatically groups tightly coupled repositories into bounded contexts.

Runtime & deployment context

Database schemas, build configs, deployment targets, and security constraints per service.

Cross-repo symbol index

Every function, class, interface, and type is indexed and cross referenced. Millisecond symbol resolution.

Implementation standards

Coding conventions, design patterns, error handling, and testing strategies — extracted from your actual code.

Code is only half the picture

The richest engineering context lives outside the codebase, in ticket discussions, design documents, Slack threads, and decisions that never make it into code comments.

Code & version control

Every repo across GitHub, GitLab, and Bitbucket — indexed and cross-referenced into the graph.

Commit patterns, branch topology, and change frequency feed into system understanding.

Business context

Issue history, epic structures, sprint context, and why features were built a certain way.

Design docs, ADRs, runbooks, and onboarding guides — linked to the services they describe.

Tribal knowledge — incident discussions, architecture debates, undocumented context.

Code & version control

Code + business context + tribal knowledge
=
complete understanding

One graph. Every agent.

Same graph, same truth, every workflow, Bito’s own agents and any third-party coding agent your team uses.

Bito Agents

Bito Issue Analyzer

Analyzes issues and epics against your live codebase to deliver feasibility analysis, technical design, and effort estimation — directly in Jira and Linear.

Bito Code Review

Codebase-aware PR reviews with cross-repo impact analysis, dependency risk detection, and blast radius mapping across GitHub, GitLab, and Bitbucket.

Bito Slack Agent

Answers system-level engineering questions in Slack, grounded in your knowledge graph — architecture, dependencies, past decisions, and incident history.

Other agents

Coding agents

Claude, Cursor, Codex — any MCP-compatible coding agent connects to the same knowledge graph for grounded code generation.

Chat agents

ChatGPT and conversational agents query the graph for system-level answers and architecture exploration.

Connected through Model Context Protocol Connected through MCP

Any MCP-compatible agent can query your system the way an experienced architect would.

Context powers capabilities

Each skill draws from the knowledge graph to perform work that previously required deep system expertise.

Feasibility analysis

Reads specs against your live codebase. Flags what's buildable and what risks exist.

Technical design

Architecture documents grounded in your service topology and history.

Impact assessment

Maps every service and dependency a change will touch before code is written.

Code generation

Production code following your team's actual patterns and contracts.

Code review

Full-system PR review — cross-repo impact and dependency risk.

Production triage

Trace failures through service topology. Surface root cause fast.

Onboarding

System-level answers from the live graph — not outdated wikis.

Epic breakdown

Epics into stories with enough context for any developer to act.

Beyond embeddings and RAG

Most AI coding tools retrieve text chunks. Bito understands system structure.

STRUCTURED, NOT FLAT

Typed relationships

Every edge has a type — API call, database connection, message queue. Not just ‘related’ but exactly how they’re connected.

MULTI-DIMENSIONAL

15+ analysis dimensions

Patterns, standards, deployment context, runtime behavior, security posture, and schemas — simultaneously.

CROSS-BOUNDARY

System-wide visibility

All repositories in a single call. Every downstream consumer of a data schema — instantly.

CONTINUOUSLY UPDATED

Living, not stale

No manual re-indexing. The context your agents use is always the context that’s true right now.