Not every AI risk can be governed away with a policy. Some risks are architectural — and the fix is architectural too.
We audit what data actually flows into which AI systems today, classify it by sensitivity, and tell you plainly what genuinely needs to move and what's already fine. Deliverable: a findings report and a go/no-go recommendation — can extend directly from a Tier 1 Assessment, or stand alone if you already know you have the problem.
We design the right-sized deployment boundary for your actual risk — not the most extreme option by reflex. Model selection sized to your compute budget, a data pipeline that keeps sensitive data inside the boundary, and security controls mapped to NIST 800-171 / CMMC where CUI is involved. Deliverable: architecture diagram, build plan, cost estimate.
We stand up the environment, deploy and guard the model, integrate it with your workflows, and hand off with training. Delivery timeline scales with team size: a fast build — weeks, not months — means bringing in additional engineering capacity, and costs more. A steady, phased build can often be handled solo, at a slower pace and lower cost. We size the team to the timeline you actually need, not the other way around.
Model updates, monitoring, and security patching for the deployed enclave — rolled into Temper Steady rather than sold as a separate one-off.
The risk we're solving for isn't "cloud" versus "on-prem." It's data leaving a boundary you control. Those are different questions, and the right answer depends on how sensitive the data actually is:
| Option | Where the data sits | Right for |
|---|---|---|
| Public AI API | Leaves your boundary entirely — shared infrastructure, a vendor you don't control | This is the risk being flagged, not a solution |
| Private cloud tenancy | Still a cloud data center, but isolated to you — not shared, not used for training, often FedRAMP/IL4-5 accredited | Most CUI-moderate cases, especially without in-house data-center staff |
| On-prem / air-gapped | Physically inside your facility, no path out | The highest-sensitivity cases — classified-adjacent, ITAR, contractually mandated physical control |
Over-recommending the most extreme option is itself a failure mode — a client with no staff to maintain a physical server is often less secure than a properly configured, accredited private-cloud tenancy someone else patches. Picking the right point on that spectrum is the actual expertise in Phase 2.