You shipped AI to production. Now the bill is climbing, an agent has been rolled back, and the person who built it has moved on. We monitor it, govern it, and cut its cost — across whatever models and clouds you run — and hand you a dollars-saved number every month.
Building got easy. Operating didn't. Models update, agents drift, costs spike, regulations tighten — and most companies have no one who owns the ongoing health of what they deployed.
Sound familiar? Each one is a problem we fix — and a reason to start.
"Did your AI bill multiply?"
We find the 40–80% you're overspending on routing, caching, and model choice — and the retainer pays for itself out of the savings.
"Have you had to roll back an agent?"
We show you why it broke, what's still fragile, and put eval gating and guardrails in place so it doesn't happen in front of a customer again.
"Can't hire an MLOps engineer?"
In this market you effectively can't. Rent the function from us — an AI-native ops team, on call, for a fraction of one senior hire.
"Compliance deadline coming?"
EU AI Act Art. 50, FINRA, HIPAA, Colorado AI Act. We map your exposure to the dates and build the audit trail regulators will ask for.
Get into the on-call seat so you don't have to staff one. An AI-native ops team handles first-line monitoring, triage, and routine fixes around the clock; our specialists own every judgment call, escalation, and the relationship.
Every LLM, tool, and retrieval call traced. Reliability and uptime you can see.
Faithfulness scoring and statistical drift detection — we catch it before you do.
Routing, caching, model right-sizing. A dollars-saved figure every month.
Guardrails, model inventory, and a tamper-evident audit trail. Audit-ready.
Provider deprecations and new releases handled as config, not a fire drill.
A quantified operations report every month — uptime, incidents handled, drift caught, and the dollars we saved, in writing.
Illustrative report · "Nothing broke" is invisible, so we make it visible.
A three-step relationship designed so the next step is the obvious one — never a leap of faith.
A fixed-fee, time-boxed diagnostic of the AI you have in production: what it costs, where it'll break, what regulators will ask — plus one fix already shipped.
We take the on-call seat: monitoring, drift correction, eval gating, cost optimization, governance, and a quantified report every month. This is the relationship.
Fractional AI leadership, additional workloads, net-new implementations, and team enablement — added as your footprint grows.
Hybrid pricing — a fixed monthly base plus usage. Priced against the value of the work, not a per-seat license. We commit to what we control: monitoring uptime and response time, never the model's output.
Eyes on your AI. For teams that need a safety net, not a full ops function.
The full ops function, rented. The default for most clients.
For regulated, customer-facing, and always-on AI where downtime is unacceptable.
In 2026 the model labs launched their own services arms and began acquiring services firms. The clean answer to "why not just use the lab's own services arm?" is simple: because we don't sell you lock-in. We run you on whatever serves you — Anthropic, AWS, Google, or cost-efficient open-weight models on neutral infrastructure. Neutrality isn't a slogan; it's a monthly cost-savings deliverable only a neutral operator can offer.
Rolling Claude out to a team isn't a licensing decision — it's a standards problem. Fifty seats produce fifty private workflows: different Terraform, different answers, different risk. We design and build a private plugin marketplace for your org — your conventions, your knowledge, your policy — that your whole team installs with one command.
Proven on ourselves first: our proposals, delivery docs, time tracking, and company knowledge base all run as plugins on this stack. We don't resell it — every engagement is a custom build on the same pattern, and our first enterprise builds are standardizing Terraform for teams that just rolled out Claude.
Built on Claude Code's plugin system. The pattern — versioned skills, Git-native knowledge, hooks — lives in your repos, not ours.
"Can't we just ask Claude to do this?"
Go ahead — every engineer you have already did. That's how you got fifty setups instead of one standard. Claude writes a skill in minutes; it can't get your seniors to agree on the convention, ship it to every seat, notice the drift, or keep it current when the model changes next month. That's an operations job, and it's the one we do. (A three-person team? Honestly — just ask Claude.)
A diagnostic of the AI you already run — not a slide deck of generic advice. You get a scored maturity baseline, a dollar-quantified cost teardown, a prioritized roadmap, and at least one improvement we ship during the engagement.
Best fit: AI already in production, a small (or no) dedicated AI team, and at least one of the triggers above already biting. Deepest in financial services and ops-heavy B2B SaaS.
Book the audit →A paid, three-week diagnostic with a fix already shipped — and a clear path to never worrying about your production AI again.
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