Service ยท The software audit firm for the AI era
Continuous correctness audits for critical software paths.
Senior engineers, amplified by the Proof verification engine, audit the behavior your business depends on. Continuously, not once. Every finding is confirmed and reproducible, every fix is re-verified, and the evidence stays in your repo where your team and your customers can rerun it.
Launch review establishes scope, risk model, first findings, and initial evidence corpus.
Every few days, weekly, per release, monthly, or custom cadence.
Findings, reproducers, tests, patch verification, and executive summaries.
Why this exists
Fast code needs evidence that moves with it.
AI-assisted development changed how fast software is written. It did not make product intent, requirements, review, tests, or audit evidence scale at the same rate.
Most failures come from edge cases nobody specified, behavior that drifted from intent, tests that encode the current implementation, and releases that ship without reusable evidence.
Reviewed surfaces
Use it where ordinary review is not enough.
Gateways, routers, parsers, SDKs, protocol implementations, federation, and request pipelines.
Auth, permissions, tenancy, billing, quotas, scheduling, state machines, and irreversible transitions.
Agentic workflows, AI-assisted product features, upcoming releases, and customer-facing behavior claims.
Typical engagement
What happens in the first 7 to 10 days.
Confidential scoping
Agree on the reviewed path, release pressure, disclosure boundary, access mode, and buyer questions the evidence must answer.
Evidence setup
Collect source, tests, docs, prior findings, traces, and known risky behavior. Public-source reviews can start without private repo access.
First signal pass
Proof looks for correctness drift, missing negative paths, edge cases, severity candidates, and evidence gaps worth validating manually.
Findings review
Only confirmed issues are delivered as findings. Unconfirmed leads stay out of the buyer report unless explicitly useful as research notes.
Retest plan
Agree whether Proof continues weekly, per release, every few days, or as a one-off launch review.
Packages
Choose the buying shape before the cadence.
Best when a feature, parser, router, policy, or customer commitment needs outside evidence quickly.
Best when the code changes often and findings need patch verification, not one static report.
Best when leadership, AppSec, or customers need an artifact tied to each release window.
Best when the team needs reusable evidence for procurement, security review, or remediation proof.
Best for GraphQL, router, parser, SDK, protocol, federation, and gateway paths with broad downstream blast radius.
Pricing, scope, access, and first-deliverable timing are confirmed after confidential scoping.
Deliverables
Durable artifacts, not just a findings list.
A Continuous Correctness Audit produces evidence your engineering team can run, review, and reuse.
Scoped risk model
Selected component, behavior claims, release risk, and what is explicitly out of scope.
Gap analysis
Requirements, implementation, tests, and documentation checked for drift and missing behavior.
Confirmed findings
High-signal correctness and security issues with clear impact and affected surface.
Reproducible evidence
Reproducers, regression tests, expanded coverage, MC/DC, or formal-verification artifacts where applicable.
Retest and review
Patch verification, recurring findings review, and executive summary for leadership or customer conversations.
Who buys this
Different buyers, same need for reusable evidence.
Needs customer trust, enterprise readiness, or confidence before a high-risk release.
Needs evidence that fast-moving implementation still matches approved intent.
Owns parsers, gateways, SDKs, auth, policy, billing, tenancy, or routing paths with broad blast radius.
Needs an external reviewer with high signal-to-noise, not another automated backlog to triage.
Needs reusable evidence for customer security reviews, procurement, or audit conversations.
Needs precise reports with reproducers and low disclosure friction.
Reproducer standard
A finding must be runnable or explicitly bounded.
- Affected version, commit, branch, or release window.
- Minimal failing test, script, fixture, request, trace, or scenario.
- Exact command or replay steps where feasible.
- Expected failure before the fix and expected pass after the fix.
- Environment, dependencies, and CI suitability notes.
- Evidence owner, retest status, and residual risk.
AppSec fit
Complements existing security work.
- Not a replacement for pentest, SAST, SCA, fuzzing, or bug bounty.
- Focused on correctness and security drift in scoped critical paths.
- Can ingest previous audit findings and regression tests.
- Maps confirmed findings into existing ticketing and remediation flows.
- Verifies patches so reports do not age out immediately.
Cadence
Matched to the way your team ships.
Initial corpus, risk model, and first findings for a critical path.
For fast-moving teams or active feature development where drift appears quickly.
For regular engineering cadence and ongoing coverage of critical changes.
For teams that want evidence attached to a release gate.
For lower-change systems that still need senior review and regression checks.
Aligned to customer commitments, audit windows, or security review timing.
What this is not
Not an automated backlog. Not a claim of total correctness.
- Proof does not claim your whole software system is mathematically correct.
- Proof focuses on scoped critical paths and concrete, reviewable evidence.
- Proof is complementary to traditional security audits and existing tests.
- Proof can later connect to CI/CD and development-time feature review where useful.
IP boundary
Public methods, private engine.
- Safe to discuss: MC/DC, formal verification, reproducers, traceability, coverage, audit cadence, sanitized methodology.
- Not public: prompts, agent orchestration, proprietary scoring, private benchmark corpora, customer intelligence, and the internal engine.
- Every delivered finding should stand on inspectable evidence: reproducer, affected surface, severity rationale, and retest result.
Next step
Bring one critical workflow.
Proof will tell you where intent, code, tests, and evidence diverge.
Do not submit secrets or private source code here. Form data is used for scoping and follow-up; see Trust.