AI systems · Advise · Build · Control · Operate
The execution layer for enterprise AI.
We design, build and run AI systems that act inside your workflows, with clear permissions, human approval where it matters and a record of every decision.
Most AI projects don't fail on the model. They fail on the data, permissions, costs and ownership around it.
AI initiatives stall between the model and the business.
- 01 · DataBuilt in
Data the system can trust
Sources, freshness and access are defined before a model reads anything.
- 02 · AuthorityBuilt in
Permissions someone decided
What the system may read, change, spend and approve is written down and enforced.
- 03 · CostBuilt in
Cost someone watches
Budgets per task and per workflow, with alerts before a limit is crossed.
- 04 · OwnershipBuilt in
An owner for the outcome
A named person accepts the result and decides when the system earns more autonomy.
A capable model is not yet a working system. The missing layer is controlled execution, and that is what we build.
Four ways to start.
Start with the stage you need now: Advise, Build, Control or Operate. Each one stands on its own, and they connect into one program when you need more.
- 01Advise
Qualify the opportunity before committing capital or operational trust.
Explore advisoryWhat you receive
- Opportunity assessment
- Architecture direction
- Prioritized roadmap
- 02Build
Engineer the capability around real workflows, systems, and acceptance criteria.
Explore build capabilitiesWhat you receive
- Working system
- Acceptance evidence
- Operational documentation
- 03Control
Define authority, evaluation, evidence, and cost boundaries before scale.
Explore controlWhat you receive
- Control requirements
- Review boundaries
- Change and escalation path
- 04Operate
Maintain selected systems under explicit responsibilities and review cadence.
Explore operationsWhat you receive
- Defined coverage
- Operating cadence
- Transition path
Value begins when intent becomes controlled action.
Cyryx designs the execution layer between AI models and the workflows, systems, data, and people they are expected to affect.
- 01
Intent
Define the business outcome.
- 02
Authority
Set who and what may act.
- 03
Execution
Connect models, software, data, and tools.
- 04
Evidence
Record consequential decisions and actions.
- 05
Improvement
Measure quality, cost, and exceptions.
One run, end to end
Every step is scoped, reviewed where it matters, and recorded.
The system works inside the limits it was given. Exceptions stop for a person. What happened, who approved it and what it cost stays on the record.
- IntentClassify inbound supplier invoices and route exceptionsdefined
- AuthorityMay read the ERP · may not approve payments above $5,000scoped
- Execution142 invoices processed · 9 exceptions foundcomplete
- Human review3 exceptions sent to the finance leadapproved
- EvidenceDecision log, cost per task and acceptance check recordedrecorded
Every engagement leaves evidence you can review.
Before a system gets more trust, three documents make its design, its limits and its behavior explicit. Here is what each one looks like.
Architecture brief
Sample · illustrative data- Objective
- Route supplier-invoice exceptions to the right approver the same day.
- In scope
- Invoice intake, classification, exception routing
- Out of scope
- Payment execution, vendor onboarding
- Systems
- ERP (read) · shared inbox (read) · ticketing (write)
- Authority limits
- No approvals above $5,000 · no changes to vendor master data
- Open risks
- Duplicate invoices across two legal entities
Governance is architecture.
Before AI can act inside an operation, its authority, limits, evidence, cost, and owner must be explicit.
- 01
Authority
Define what the system may access, decide, spend, and change.
- 02
Boundaries
Hold high-impact actions for the required human decision.
- 03
Evidence
Preserve the context behind consequential decisions and actions.
- 04
Value
Monitor quality, cost, and exceptions before deciding what should scale.
Control before scale.
Explore governance architectureWhat should AI be trusted to change in your business?
Tell us about the workflow, product or constraint. We will tell you whether AI belongs there, what it would take, and where to start: Advise, Build, Control or Operate. Sometimes the right answer is not to build.