AI that earns its place in your company.
We help companies choose the right models and cloud, build the agents and automations that take real work off the team, and secure the whole estate behind one sign-on: every server, database, tool and model, with access by role and one cost ledger across all of it. Vendor-neutral, and honest about what we could not read.
Engineers who run production systems under PCI DSS and ISO 27001, across Huawei Cloud, AWS and Google Cloud, with Kubernetes, Terraform, and the certificates, keys and quotas that come with them.
Three services. Most companies need them in this order.
AI adoption goes wrong in two places: paying for the wrong model in the wrong place, and letting it touch systems nobody has secured. We start where the money and the risk actually are, on the cloud you already have.
Choose
Which models, which provider, hosted where, at what price per task, decided from your own traffic rather than a vendor benchmark. The same discipline for the cloud underneath.
Cloud and model selectionBuild
Agents and workflows that take real work off your team: deployments, provisioning, reporting, reconciliation, compliance evidence. Each one proposes before it acts, and waits for a person where it matters.
Agents and automationSecure
One login for everything your people and your agents touch: cloud consoles, servers, databases, internal tools and the AI ones. Access by role, sessions recorded, keys rotated on a schedule, sensitive data kept out of prompts and logs.
Single sign-on, access and evidenceWhat the review hands back.
Three parts, two to three weeks, every figure beside the provider's own. The sample below is illustrative; yours is built from your account.
| Line | Provider states | We attribute | Finding |
|---|---|---|---|
| Cloud, all services | $7,638.66 | $6,408.57 across 18 services | $1,230 unattributed, named as such |
| Model usage | $2,300.00 | $1,790 on one model, 95% of calls | 3× output tokens for the same answer |
| Idle public addresses | $41.40 | 6 addresses routing nowhere | release, saves $41/mo |
| Quota headroom | — | model quota at 94% | alert at 80%, before it fails |
| Check | Found | Requirement | Next step |
|---|---|---|---|
| Database reachable from the internet | none | PCI DSS 1.3 | — |
| Security groups open to the world | 2 | PCI DSS 1.2.1 | restrict to known ranges |
| Access keys older than 90 days | 3 | PCI DSS 8.3.9 | rotate, then schedule |
| Identities with no sign-in in 90 days | not readable | PCI DSS 8.2.6 | grant iam:users:list to include |
| Workload | Today | Recommended | Measured on your traffic |
|---|---|---|---|
| Short answers, routing | large reasoning model | small, fast model | 1.8 s vs 8.1 s · same answer |
| Code changes | large reasoning model | keep | quality holds, cost justified |
| Fallback | 26% of requests | under 3% | one misconfigured timeout |
| Development traffic | production model | flat-rate coding plan | off the metered bill entirely |
Figures are illustrative, in the shape a real report takes. Every line names its evidence and, where we could not read something, the permission that would let us.
Every request lands on a ledger, whether or not a model was involved.
This is what sits underneath our work. Point an app, an IDE or an agent at one endpoint and every request is answered, routed, and written down with what it cost. Pick a request below to see what happens to it.
| Request | Gate | Memory | Model | Billed |
|---|---|---|---|---|
| “thanks” | answered | — | — | no |
| “what changed on prod last night?” | passed | attached | small, fast | $0.0031 |
| “refactor this migration” | passed | attached | larger, reasoning | $0.0418 |
Answered at the gate. No model was called, nothing was billed, and the request is still on the ledger.
We measure before we recommend anything.
The first engagement is a fixed-fee review of what you pay for AI and cloud, who can reach production, and which models fit which jobs. You keep the report either way. Build and run follow only if the review says they should.
Review
Read-only access to your cloud account and model traffic. Out comes a report in three parts: cost, access, and model fit, every figure beside the provider's own.
Build
The agents, automations and access controls the review called for, built on your keys and your models, in your environment or ours. Nothing goes live without a person approving it.
Run
We operate it and report the ledger each month: what ran, what it cost, what it would have cost without us, and what we still could not see.
Start with the review.
Tell us what you run and what AI costs you today. We reply within one working day.