The Platform

Intelligence.
Control.
Execution.

Three purpose-built layers. One closed loop. Each layer feeds the next — no human relay required at any step.

01 — INTELLIGENCE LAYER
Signals
The Score

Reads every data source in your enterprise and computes a living intelligence layer — velocity scores, anomaly alerts, yield diagnostics — across engineering, finance, HR, and operations.

15+ Live Connectors
Jira, GitHub, AWS Cost Explorer, Harvest, BambooHR, Slack, QuickBooks, New Relic, PagerDuty, and more — all normalized into a single intelligence model.
1,000+ Repositories
Under active AI orchestration across live enterprise deployments.
Cross-Function, Not Just Eng
Most tools stop at the codebase. Signals ingests business signals from every function — so patterns surface before anyone files a ticket.
Velocity & Yield Scoring
Compute productivity efficiency per engineer, per team, and per project. Identify yield gaps, capacity blockers, and sprint-over-sprint drift automatically.
Feeds Maestro Directly
Signals doesn't just surface data — it hands actionable context to Maestro so agents have full business awareness before they act on anything.
Signals → Maestro
02 — CONTROL PLANE
Maestro
The Conductor

The enterprise control plane. Routes work to the right agent or human, enforces policy at every step, and maintains a tamper-evident audit trail for every AI action taken on behalf of the enterprise.

Multi-Agent Orchestration
A fleet of specialist agents — each scoped, credentialed, and policy-constrained. Maestro routes tasks to the right agent and enforces authorization at every handoff.
Cross-Function Coverage
Engineering, finance, AP, collections, HR, operations — Maestro orchestrates agents across every function. Not just a dev tool; the entire operating layer.
Full Governance & Audit
Hash-chained audit log for every agent action. Who authorized what, under which policy, at what time. Complete defensible record for compliance and legal.
Human-in-the-Loop by Design
Maestro decides what to automate and what to escalate. Auto-dispatch is policy-gated. Agents create drafts; humans approve. Trust is earned incrementally.
Maestro → Shipyard
03 — EXECUTION ENGINE
Shipyard
The Musicians

The SDLC execution engine. Receives approved work orders from Maestro and executes end-to-end: spec, branch, build, test, review, merge, deploy, validate — across ~1,000 repositories.

Multi-Repo Orchestration
Coordinates changes across repositories simultaneously. Since 2025 — before competitors launched equivalent capability in 2026-Q2.
Full Pipeline: Spec to Deploy
Each pipeline stage is an agent: spec writer, branch creator, test runner, reviewer, deployer. Every stage logged, costed, and audited by Maestro.
Drift Detection
Post-merge, Shipyard scores the final code against the original spec. Drift above threshold triggers automatic review and human escalation.
Self-Healing via Telemetry
Runtime telemetry feeds back into Maestro. Anomalies post-deploy trigger automatic ticket creation and optional rollback — the loop closes itself.
End-to-End Scenario

One signal. Three layers. Shipped.

How the platform handles a real-world alert without a human relay at any step.

Signals

Signals detects a cost spike

AWS Cost Explorer ingested at 4am. Signals flags a 40% MoM increase in Lambda spend tied to a single service. Cross-references GitHub commit history. Identifies probable cause. Hands context to Maestro.

Maestro

Maestro routes, authorizes, drafts

Routes to the cost-optimization agent. Checks authorization policy — senior eng approval required for infrastructure changes. Drafts a fix spec and a Slack message. Queues for human review. No action taken yet.

Shipyard

Shipyard executes on approval

Engineer approves the draft. Shipyard branches, implements the fix, runs tests, gets automated review, opens PR. Post-merge, monitors Lambda spend. Confirms 38% reduction. Closes the loop in Signals.

Why the Control Plane Matters

The loop only closes if someone owns the middle.

Most AI tooling stops at the task level or simple code rewriting. The enterprise needs a platform that owns the entire workflow — from signal to shipped across both code and knowledge work, with governance at every step.

We match pure software-factory speed while delivering the full operating system for labor yield, finance automation, portfolio intelligence, and exit readiness that code-only platforms do not provide.

01
One contract, not 100 licenses
Consolidate AI spend under a single enterprise contract. Finance sees exact per-project token costs. No more 100 individual developer subscriptions with no oversight.
02
Governance that scales with AI adoption
As AI agents handle more decisions, the audit trail becomes more critical — not less. Maestro's control plane was designed to scale with the fleet, not lag behind it.
03
Cross-function context in every agent call
Agents in Maestro know what's happening in finance, HR, and operations — not just the SDLC. Context-aware automation has fewer false positives and better outcomes.
04
Production today, not roadmap
Thrasoz is live in production at multiple enterprise clients. The platform handles real workloads, real incidents, real approvals — not a demo environment.

See the platform running in production.

Request a Demo → Why Thrasoz?