Private sector
Governance that keeps
pace with the build.
Adoption is moving from generative to agentic to agent-to-agent faster than most control environments can follow. We make the risk and the run rate legible early, so controls enable delivery instead of blocking it. We do not sell or build AI systems. We align yours to the frameworks that will hold you accountable for their impact.
Audience
Who this is for
Enterprise leaders across governance, risk, and compliance, plus product, engineering, and design, usually in regulated industries: finance, insurance, healthcare, and legal.
You have capital and a mandate to move. The risk is not spending the money. It is spending it blindly, or committing to the wrong approach.
Constraints
What you are up against
Risk compounds faster
than controls
Each step from generative to agentic to agent-to-agent multiplies the surface area. Governance has to move at the speed of the build.
Controls have to enable delivery
The buyer often sits in compliance and in engineering at the same time. A control that blocks the roadmap does not survive contact with it.
Unit economics decide
Speed to market and cost per outcome both matter. A use case that works but cannot be run profitably is a pilot that never ships.
Price the use case before you build it
The planner
Plan the run rate for an AI workload, see the exposure if it runs away, and get the controls that cap it. The business view asks plain questions. The technical view exposes the engine
Human review is
usually the largest line
On governed workloads where mistakes carry real consequence, human review often exceeds three quarters of the monthly total, larger than the AI itself. An estimate that leaves it out is giving you a smaller number, not a truer one.
Messy data costs
you twice
Bigger prompts on every run, plus failed runs that have to be redone. The planner shows retries as their own line.
Agentic workloads
have a blast radius
The worst credible day, stated plainly, with the controls that cap it: iteration ceilings, budget stops, rate limits, and spend anomaly alerts.
Differentiation
Why Optimum
Governance with
engineering reality
We are fluent in the same compounding-risk problems your teams live with, and we make cost and risk legible before the build starts rather than after the invoice arrives.
We govern what we do not sell
No AI product line and no reseller margin, so the assessment is not an argument for a purchase.
Built for scrutiny
Four decades delivering systems that hold up to examination, hosted in environments where evidence and chain of custody are the product.
The planner
Price a use case
before you commit to it
The AI Cost and Control Planner models a workload end to end, including the human review that responsible operation actually requires.
Contact
Talk to us about governing AI
Tell us the use case you are weighing and we will tell you what it takes to govern it.