PROOF.

Product

How it works The graph Changes Agents Life after installation

Evidence

Public Proof Findings jsonparser rsync jsonparser case Correctness labels

Practice

Methodology The audit Instruments Trust Topics Labs

Compare

Jama Connect CodeRabbit SonarQube Snyk LDRA

Company

About Partners Open-source audit Install Brand Museum

Higher engineering standards.
Less manual QA. More work you can delegate.

Higher standards.
Less manual QA.

From prompt
to production.

Proof brings NASA-grade rigor for your AI workflow.
Get enough evidence to trust the change without manual verification.

Start with a change
A small figure standing among vast, curved architectural forms.

Give agents a
higher standard.

Adding proof to real-world software.

Tyk rsync Omarchy gRPC GraphQL Hive WunderGraph Apollo jsonparser

Less human time
per accepted change.

Stop rebuilding context and repeating checks. Review the evidence. Make the decisions that need you.

Less rework.
Fewer regressions.

Find problems earlier. Keep regression checks and the lesson behind each fix.

More work safely
delegated to agents.

Let agents investigate, implement and verify within your rules.

01 / How Proof works

Higher standards.
Less work by hand.

Proof is software assurance for agentic engineering. It recovers intent, keeps agents within approved requirements and brings regulated engineering rigor to each change. You get evidence your toughest QA can review without testing everything again.

See the evidence
Your change Checks set by your project and its risks.

  • Requirements management

    Recover intent. Make approved requirements the source of truth your agents must follow.

  • Hazard analysis

    Find failure risks, guide fixes and require evidence before closing them.

  • MC/DC testing

    Bring decision coverage used in safety-critical avionics to agent workflows.

  • Formal verification

    Formalize requirements and critical code. Verify selected properties under stated assumptions.

A change. And the evidence to review it.

Your agent does the engineering.
You make the decisions that need you.

The Software Intent Graph connects approved intent, code, risks and evidence to each acceptance decision.

02 / Beyond the diff

“Just one line.”

The impact rarely stops there.

The Software Intent Graph connects what your software must do to the code, dependencies, hazards and evidence behind it. Change one part, and your agent can see what else needs checking.

It lives alongside your code and reaches your agents through MCP, so each change starts with the intent, constraints and lessons already learned.

See how the checks add up

See what depends on the change.

Intent, code, dependencies, risks and the evidence needed to check them.

An illustration of scope, not a verification result.

The cutaway illustrates five connected layers: intent, what must hold; code, what implements the change; dependencies, what relies on it; risks, how it could fail; and evidence, the checks needed to support the change.

03 / Beyond code review

Code review was
never enough.

Proof helps you answer the questions a diff leaves open.

  • What am I accepting?
  • What could it affect?
  • Why should I believe it works?
  • What remains unresolved?

Below is one change, with those answers in view.

PROOF Omarchy 13512 Illustrative Needs a decision

What am I accepting?

  • A comment is dropped, so it cannot empty the menu. New rule

  • A trailing comma is dropped before the menu is read. The written rule changed

  • Only the code that reads the file was rewritten. The code changed

The menu keeps28rules

19 more are not shown here.

Why should I believe it works?

The voice walks through what you are seeing. The demo is attached to this review.

What could it affect?

23other rules sit in files this change can touch.

The two open marks are files with no rule to check. 23 is the widest possible reach, not a list of edits.

What remains unresolved?

  • 11 problems still block this change
  • 2 files with no rule to check
  • 1 safeguard still waiting for a judgment

Your decision

Keep this safeguard? When the menu file cannot be read, a time is recorded. Proof has not shown that this is as strong as before. Open. No one has accepted it.

A picture of an Omarchy review, not a live analysis.

04 / Knowledge that compounds

Every change makes
the next one stronger.

Proof keeps the intent, decisions, checks and lessons from each change in your Software Intent Graph. The next engineer or agent starts with what you already learned.

The more you use Proof, the less your agents need to rediscover.

Open issues stay visible. Evidence is checked again when its basis changes.

See what the record keeps

Proof retains

Software Intent Graph

  1. Feature / change

    New behavior or an intended update.

  2. Change record

    What changed, why, and the evidence behind it.

  3. Requirements + evidence

    New, updated and preserved requirements, with evidence.

  4. If a problem is found

    Known issue

    An unresolved problem, kept visible.

  5. Reproducer

    The failure kept as a repeatable test.

  6. Verified fix / defect record

    After verified closure: the issue, cause, fix and regression evidence.

  7. Hazard & class knowledge

    Related risks, limits and lessons. Broader risks can remain open.

  8. Next change

    Your agent starts with everything above attached.

An example of knowledge that accumulates. Open issues remain open until closure is verified.

05 / Public proof ledger

The proof is public.

Real projects. Reproducible findings. Fixes and limitations you can inspect.

Explore the proof ledger

Selected public records

  1. rsync

    Access-control fix and regression tests.

    Released in 3.5.0

  2. gRPC-Go

    Reject invalid credential metadata.

    Merged upstream

  3. GraphQL Hive Router

    Crash after request rewriting.

    Fix merged Report

  4. jsonparser

    What the checks missed, and why.

    Published postmortem Founder-maintained project

The misses belong in the record, too.

06 / FAQ

The obvious questions.

What the promise means, and where you still decide. Open any question.

  1. 01

    What does “without manual verification” mean?

    Proof adds so much engineering rigor to your AI workflow, and generates so much evidence, that in the majority of cases it is enough for you to just review the evidence without manually testing it. The best part is that with every change it becomes better.

  2. 02

    What does “NASA-grade” mean here?

    Requirement management, formalization, hazard analysis, MC/DC testing, and formal verification. It is the same bar as DO-178C. We do not have a formal certificate for that. Our goal is to make these regulated engineering practices affordable and easy to use in agentic flows.

  3. 03

    Who still has to say yes?

    You can control what is required to be approved by humans and what is required to be approved by the agents. If you want the full agentic flow for the components you trust, that is totally possible. You can whitelist a component and say that it requires human approval whenever a change will touch it.

  4. 04

    Is Proof a coding agent?

    No. Proof is a platform, and it consists of these parts.

    • Harness It lives inside your coding agent, works with any coding harness, and adds the required determinism and the engineering quality flow inside it. It then uploads these results to the dashboard.
    • Orchestrator It lives inside your CI/CD. It can automatically triage all of the issues and the pull requests and do the code reviews for them. You can also connect it via MCP and make it work by generating the pull request with those changes, technically turning it into the AI factory you can actually trust.
    • Dashboard Where those results go.
    • MCP Humans or agents can use it to review the changes, see the overview of your system, and use this data to plan future changes or fix bugs.
  5. 05

    Do I need written requirements first?

    Proof has a flow to recover the intent from your code comments, pull requests, and Jira for the initial onboarding. Moving forward, Proof can act as a sidecar, which works in parallel with your standard development. Or you can start using it for your development directly, and use requirement management as your source of truth.

  6. 06

    Do MC/DC and formal verification run on an ordinary pull request?

    If the change this pull request touches requires this kind of evidence, then yes. Proof does not cut corners. It enforces what kind of evidence is required for the given change. If that evidence is formal verification, then yes, it absolutely should be done. Proof also knows how to run only the required subset of the tests. It can cut your CI/CD time by running only the necessary tests, while increasing your test coverage multiple times.

  7. 07

    What does the first engagement include, and what does it cost?

    Start with one change, in the agent workflow you already have. The repository stays closed on the first call. If you want the standing version, that is one component over about four weeks, with a few hours from the people who own it. The fee is quoted when the scope is clear, and fixed before the work starts. What we produce stays in your repository if you stop.

Start small. Learn from real work.

Ship with proof.

A feature, a fix, or work you hesitate to delegate.
See what your agent can take off your hands.

Send a link or a few sentences.

[email protected] Book a demo

We’ll scope a first use of Proof in your existing repo and agent workflow.