Dependency
Core operations inherit an external control point.
Pricing, availability, behavior, and policy remain tied to a provider the enterprise does not control.
AI Governance
Built to optimize AI capital and control.
NACD's Q2 2026 private-company survey shows AI is now the top board agenda item for Q3, cited by 74% of respondents and tied directly to cybersecurity, workforce planning, capital allocation, and economic uncertainty. Autonomakers gives boards and management teams one evidence base for AI investment and control—then converts approved workflows into owned autonomous runtimes.
Capital control. Runtime governance. Defined autonomy levels. Enterprise ownership.
Owned autonomous runtimeoperating within certified authority
Workflow policy
Enterprise data
Approved actions
Human escalation
Specialist runtimereliable · auditable · owned
Models used to manufactureRuntime owned by enterprise
The problem
Capital control and operational governance are now the same board problem.
Directors and management teams must decide which AI investments deserve funding while also proving those systems operate with accuracy, privacy, cybersecurity, IP, compliance, data-quality, reputational, and autonomous-agent controls. Both duties require the same operational evidence.
Value leakage
Learning compounds outside the balance sheet.
Workflow improvements and operating data strengthen the rented platform rather than an asset owned by the enterprise.
Governance gap
Prompts are not an operating control system.
Production autonomy requires explicit authority, certification, auditability, reversibility, and escalation.
The third way
Owned autonomous runtimes.
A runtime is a specialist intelligence an enterprise owns outright. It is manufactured using rented general models, then packaged into an independent, reliable operating asset rather than a permanent model dependency.
The model is manufacturing equipment—not the finished asset.
Frontier models help interpret policy, generate workflow artifacts, test edge cases, and accelerate engineering. Production authority is transferred into a controlled runtime the client owns.
Build
Use frontier models
Compile policies, historical cases, schemas, and operating knowledge into reviewed artifacts.
→
Certify
Define autonomy level
Each workflow receives bounded authority, evidence requirements, intervention rules, and release criteria.
→
Transfer
Own the runtime
The enterprise receives the operating asset, governance system, source artifacts, and improvement loop.
What we do
A contract manufacturer for enterprise autonomy.
Think Honeywell or ABB for owned AI: financing and governance make autonomy investable; contract manufacturing turns workflows into reliable assets.
Financing
AI operations infrastructure
tlacap.com provides financing and governance structures that make AI operations investable, auditable, and accountable.
- Capital structure and underwriting
- Governance and control architecture
- Auditability and performance measurement
- Portfolio-level operating discipline
Contract manufacturing
Custom runtime production
milli.run converts AI use and priority workflows into reliable autonomous runtimes clients own.
- Workflow and autonomy-level design
- Runtime engineering and integration
- Validation, deployment, and operation
- Build-operate-transfer ownership
Autonomy levels
Every priority workflow receives a defined, certifiable level of autonomy.
Using the logic of NHTSA L0–L5 autonomy, authority advances only as evidence, controls, and operating reliability justify it.
L0
Manual
Human execution with instrumentation and workflow capture.
L1
Assist
Runtime prepares analysis or recommendations; people decide.
L2–L3
Bounded autonomy
Runtime executes defined cases and escalates exceptions.
L4
High autonomy
Runtime manages the workflow under certified operating conditions.
L5
Full domain autonomy
Runtime operates across the approved domain with continuous governance.
Why us
Investors, inventors, consultants, and engineers with a decade of owned AI experience.
2014
Founded a safe, explainable AI company.
Built specialist intelligence for law and commerce before the current generative AI cycle.
2017
Recognized for AI at scale in litigation funding.
Applied explainable AI to a high-stakes financing workflow with institutional requirements.
Pre-ChatGPT
Built a specialist conversational agent.
Developed for one of the world’s largest commerce data providers three years before ChatGPT.
2023
Acquired into the EQT portfolio.
Operating experience carried into a global private-equity portfolio environment.
Today
Industrializing owned autonomy.
Combining transaction discipline, governance architecture, and runtime manufacturing.
Outcome
Enterprise economic power remains with the enterprise.
Clients own the runtime, operating knowledge, improvement loop, and resulting asset value.
Entry engagement
Owned Runtime Design
Identify a priority workflow, assign its target autonomy level, define the governance and financing structure, and produce a decision-ready manufacturing plan.
- Workflow and value map
- Target autonomy level
- Governance and certification plan
- Runtime architecture
- Financing and ownership structure
- Build-operate-transfer roadmap