Applied AI Research · Henderson, Nevada
Greybeard Holdings LLC builds tools for AI governance, behavior specification, and automation. Everything we design has to survive real use: a paying customer, a deadline, an audit. If we can't point to what caused a decision, we don't trust it.
AI governance. Verification before vibes: machine-checked constraints, provenance on every decision.
Behavior specification. Specs as executable, testable contracts - not documents.
Automation. Signal-driven runtimes where agents handle the determined work and humans own the seams.
We are a small research company with an unusual discipline: everything we design has to run a real operation. The tools below are not papers or prototypes - they answer phones, quote work, enforce SLAs, and pass audits today.
Machine-verifiable constraints over agent behavior: quality gates with deadlines, dead-man switches, idempotency, and a no-drop rule - every signal ends resolved, in a dead-letter queue, or in the audit trail. Governance you can compile, not a policy PDF.
Speckl - a specification language that turns human judgment into executable, testable code. Domain experts write what a system should do; the compiler makes it runnable, checkable, and provable.
Spec-compiled runtimes that route signals, dispatch capabilities, and keep humans at the seams where judgment matters. Deterministic where the world is determined; human exactly where it isn't.
Speckl is a specification language and a deterministic compiler. Specs describe what a system should do - never how. The same input produces the same output, every time, with no LLMs anywhere in the compilation path.
// behavior as a contract - not a document speck LeadIngestion { action ReceiveLead(id: String, name: String, email: String) { require length(email) >= 5 require not leads.has(id) // no duplicate intake leads[id] := Lead { email: email, stored: true } emit LeadReceived { id: id } } constraint "every lead receives a reply within 24 hours" { true } }
One source compiles to TypeScript, Go, SMT proofs (Z3), OpenAPI, Kubernetes CRDs, and provenance records (PROV-O, SPDX, CycloneDX) - so governance artifacts fall out of the same pipeline that ships the code.
Every system we build carries the same three commitments. They are encoded in the specs, not written on a wall.
Where the right answer can't be computed, a named person decides. Agents handle everything determined; judgment stays human.
Deadlines and quality scores are enforced by the runtime - a promise that expires is a broken promise, and the system notices.
Every event reaches one of three destinations: resolved, dead-letter queue, or audit. Nothing quietly disappears.
The full stack - spec compiler, signal runtime, governance gates - runs a working IT services company. Real phone calls route through it. Real leads are answered inside SLA. Every action leaves an audit row. When your research has to survive Tuesday, you learn what actually holds.
If you're working on AI governance, specification-driven systems, or automation that has to survive the real world, we'd like to hear from you.