AI Control Register
A living inventory for systems, owners, risk tiers, data, controls, tests, incidents and review dates.
Lynqra begins with service-assisted delivery. A module becomes a repeatable product only after multiple paying customers prove the same problem, control pattern and buying need.
A living inventory for systems, owners, risk tiers, data, controls, tests, incidents and review dates.
Focused operational automation with bounded access, human checkpoints, logs and exception handling.
A consolidated view of AI activity, costs, exceptions, performance and governance evidence.
Each productised module starts from the same operating questions, then applies controls according to consequence and readiness.
The workflow has a named business outcome, owner and prohibited-use boundary.
Models and agents receive only the data and actions required for the approved task.
Material or uncertain actions escalate to a competent person with context.
Known cases, edge cases and acceptance thresholds are maintained as the system changes.
Actions, exceptions, cost and outcomes create evidence for review and improvement.
Operators know how to pause, override and continue the work when automation fails.
These products are not presented as mass-market, self-serve software today. They are introduced inside readiness reviews, Safe Adoption Sprints and Managed AI Office engagements where the operating context can be understood.
Licensing and standalone packaging will expand only after repeated paid deployments justify standardisation.
Product names and scopes describe the current development direction. Availability, integrations and pricing are confirmed during qualification.
A strong candidate has clear inputs and outputs, measurable volume, recurring exceptions and enough similarity across customers to support a standard control pattern.
At least three customers need materially the same capability.
Permissions, decisions and failure modes can be defined clearly.
Time, quality, throughput, cost or risk evidence can be observed.
Human setup and review can reduce as the pattern becomes proven.
Show us the workflow, volume and exceptions. We will tell you whether it is a custom sprint, a product candidate or not worth automating.
Discuss the workflow