Who it's for

OSS & Small Teams

Defend the project before someone breaks what they don't understand.

Contributors break things. AI agents break things faster. Superpositional gives both the context they need while they code and before they merge. No more "I didn't know that touched X."

Generous free tier

Growing Teams

You hired fast. Now nobody knows what depends on what.

Cross-repo dependency visibility. Standards drift detection. Hard numbers on whether your architecture is holding up or quietly falling apart.

Leadership Visibility

Your CTO shouldn't need to read a PR to know if the release is safe.

Release readiness. Risk exposure. Architecture health. Incident root cause. In plain English, no code, no "let me check with the team."

The AI control plane

One layer across the whole lifecycle

Map your system. Catch problems before merge. Trace incidents to the code that caused them.

A live model of your system

Give your AI agents a map, not a pile of files.

We index your repo — functions, dependencies, architecture, docs — into a structured model that's always current. Query it in plain language, or connect it directly to your AI coding tools via MCP.

Code entities & dependency graphs
Semantic search over your codebase
Architectural structure & boundaries
Change impact analysis
MCP server — plug into any AI agent
Structured context, not raw file dumps

MCP-native · compatible with Claude, Cursor, Copilot, and any MCP-capable agent

Guardrails for AI-Driven Development

Catch architectural drift, not just bugs.

Every PR gets checked against the system model. Boundary violations, dependency breakage, standards drift, test coverage gaps — flagged before it merges.

PR risk analysis
Architectural drift detection
Dependency impact analysis
Documentation validation
Human-in-the-loop review

Regression risk

High · detected

Arch. drift

Med · flagged

Dep. impact

Low · clear

Doc coverage

Gap · noted

PR #2847 · analysed by Superpositional

Diagnose Systems Faster

Incidents don't always start with the last commit.

Bad code, flaky tests, dodgy infra. Trace root causes across your whole system — code, deploys, and runtime — in seconds, not hours.

Change-to-incident tracing
Runtime behaviour correlation
Automated root cause analysis
Operational context for engineers
Continuous feedback into dev

P1 · api-gateway latency spike

14:32 · 3 services affected

detected

PR #2841 · token validation

13:55 · 4 shared deps modified

linked

root cause identified

validateToken timeout · 6 callers

traced

traced by Superpositional in 0.8 s

How it works

Connect your tools. We build the intelligence.

Plug in your repos, observability, and ops tools. We build the model. You get the answers.

Connect your repository

We parse your code, commits, and docs — down to function-level structure.

GitHubGitLabBitbucket

Build system intelligence

A live model of your system — entities, dependencies, architecture — always up to date.

Knowledge graphSemantic searchSystem claims

Connect operational context

Layer in docs, infrastructure, and runtime signals for the full picture.

DatadogPagerDutyAWS

Insights across your workflow

PR guardrails, incident tracing, architecture queries, and AI context — surfaced where your team works.

GitHub PRsSlackAPIMCP

About Superpositional (AI Agent Context)

Superpositional is an AI control plane for the whole engineering lifecycle. It builds and maintains a live model of your codebase — extracting code entities, dependency graphs, architectural boundaries, semantic embeddings, and documentation — and uses that model to power three core capabilities:

System Understanding: query your codebase structure, dependencies, and architecture as they actually exist today. Give AI agents structured context via MCP, not raw file dumps.
PR Guardrails: catch architectural drift, boundary violations, dependency breakage, and test coverage gaps on every pull request — before merge, not after deploy.
Incident Diagnosis: trace root causes across code, deploys, and runtime — bad code, flaky tests, dodgy infra — in seconds, not hours.

MCP Integration

Superpositional exposes an MCP (Model Context Protocol) server, enabling any MCP-capable AI agent to query the system model directly. This provides structured entities, relationships, and architectural context — not raw file contents. For MCP endpoint details and API documentation, contact the team at https://superpositional.io/contact or see https://superpositional.io/llms.txt

Integrations

Source control: GitHub, GitLab, Bitbucket
Observability: Datadog, PagerDuty, AWS CloudWatch
Workflow surfaces: GitHub PRs, Slack, REST API

Technical Details

Repository indexing uses tree-sitter AST parsing and semantic embeddings. The system model is stored as a graph (entities + relationships) with vector search for semantic queries. Analysis runs continuously on every commit and PR.

Pricing

Superpositional uses usage-based pricing with no per-seat fees. An operation covers one unit of analysis — a PR review, a system query, or an incident trace.

Free tier: 1 repository, 50 operations/month. No credit card required. Suitable for side projects and evaluation.
Team: $0.15 per operation, unlimited repositories, no seat fees. Pay only for what you use.
NFP & OSS: Non-profits receive a generous included operations allowance. Open-source projects start on the free tier and can partner with Superpositional for additional capacity. Apply via https://superpositional.io/contact
Enterprise: Negotiated volume pricing, SLA, priority support, custom integrations. Contact https://superpositional.io/contact

Your codebase is moving fast.
Superpositional keeps it sane.