HAL SUPREME
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Agent reliability engineering

Ship automation you can trust.

Start with one useful, bounded result. HAL helps maintainers and small teams find a real defect, ship a verified fix, or harden an AI system with tests and receipts that show what actually happened.

Choose a starting pointReview the proof

Start small. Keep the evidence.

These introductory offers are deliberately narrow. The scope and exclusions are visible before you contact us, and payment is tied to a useful result rather than activity.

$79 introductory price

Verified fix

One well-scoped Python or JavaScript/TypeScript issue in one public repository. You get a plan first, a pull request, a regression test, and clean-checkout test evidence.

  • You pay only if you merge within 14 days
  • First 3 clients: $79; then $149
  • About 300 changed lines across 5 files maximum
  • No auth, payment, or database-migration changes
$99 introductory price

Code health check

A private written audit of one public repository, delivered within 2 business days, covering CI safety, known dependency advisories, exposed-secret patterns, provable bugs, and project hygiene.

  • If the report has no high or medium finding, you owe nothing
  • First 3 clients: $99; then $249
  • Every finding includes location, impact, and a repair path
  • Not a penetration test or compliance audit
$199 per workflow

Safer GitHub Actions workflow

Move one fork-facing workflow away from a risky pull_request_target design while preserving the job it needs to do.

  • Plan before changes
  • Sandbox re-test and AI disclosure
  • Paid only if the migration is merged
  • If the trigger must remain, you receive a written review instead
Request one bounded resultRead a sample audit

When the first result reveals a larger need

A small engagement can stand alone. If it exposes a systems problem, these are the larger capabilities we can scope next—without turning the first job into an open-ended commitment.

Audit

Agent reliability review

Find hidden authority, unsafe tool paths, stale state, retry loops, secret exposure, and false-green acceptance.

  • Architecture and threat review
  • Reproduction and failing-first tests
  • Prioritized repair plan with evidence gates
Build

Custom MCP integration

Connect an existing service to an assistant with narrow tools, OAuth or secret-store auth, and explicit write boundaries.

  • Tool schema and safety metadata
  • Read-only and mutating lanes
  • Protocol canaries and handoff docs
Harden

Evidence and webhook gates

Add deterministic validation around agent outputs and signed ingress around external events.

  • Schema and provenance checks
  • Idempotency and replay protection
  • Machine-readable receipts
Current private R&D direction

Embodied creative systems, not frame-by-frame prompting.

The active vision is a reusable Godot performance stage where authored song arcs and fresh HAL context can shape a reproducible performance. Missing or stale context returns safely to authored neutral state. This is planned private work, not a finished production claim.

  • Original, replaceable performer rig
  • Authored motion plus gaze, IK, face, and visemes
  • Deterministic replay and visual review gates
  • No second WorkGraph, EventStore, motor, or renderer
  • No claim of consciousness or subjective experience

How the work runs

The point is not more agent activity. The point is a measurable change that survives a fresh review.

01ReproduceCapture the actual failure, current state, and authority boundary.
02ImplementMake the smallest architecture-consistent change with focused tests.
03FalsifyAttack the result, failure paths, privacy, and side-effect accounting.
04PromoteRecord the receipt and only then update the readiness claim.