Maintenance & tuning

Maintenance & tuning.

Most AI projects fail in production because nobody set up monitoring, evals, or model upgrades. We do that work continuously. Weekly performance review, monthly evals refresh, quarterly model upgrades, and the on-call coverage your assistant deserves.

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Weekly reviewMonthly evalsQuarterly upgrades

About this serviceWhat it is, who it is for.

Maintenance & Tuning is one of the 9 services in our AI Studio line. Monitor, evaluate, and tune your agent fleet. Monthly model upgrades, weekly performance review, evals refreshed as your data changes. Every engagement starts with a no-charge audit so you know exactly what we will build, why, and what it will move.

We work the same way across every project: an experienced lead who scopes the work and then delivers it, a written quote tied to outcomes (not hours), weekly demos, and a working preview URL inside week one. No bait-and-switch, no junior teams handed your project, no surprise invoices.

Who it is for

Owners and founders who want maintenance & tuning done by an experienced crew, not learned on their dime.
Small and medium businesses outgrowing template-built tools and ready for something custom.
Teams that have tried agencies before and want one accountable lead, weekly demos, and a transparent quote.
Kansas City businesses that want a local partner with global delivery capacity behind it.

What we deliverEverything in a typical engagement.

Seven things every AI system needs after it is live.

Performance monitoring

Latency, cost, throughput, error rate. Alerts that page when quality moves.

Eval refresh

Golden dataset updated as your domain changes. Regression suite run on every prompt or model change.

Drift detection

Shadow evaluations on a sample of production traffic. Catch quality drops before customers do.

Model upgrades

When Claude, GPT, or Llama release a new version, we run the regression and decide together.

Prompt and tool tuning

New tools, new prompts, new policies as your workflow changes.

Audit and compliance

Per-call audit logs, retention policies, access reviews. SOC-friendly architecture.

On-call coverage

Defined SLA. We page when the assistant degrades, not when you notice.

How we run itThe phases, in order.

Monitor, evaluate, upgrade, repeat.

Discover

Goals, audience, constraints. Audit anything that already exists. Written report at the end of week one, signed before any build starts.

Design

Wireframes, then hi-fi in your brand. Reviewed weekly. We design for the customer's phone first, the boardroom second.

Build

Sprint cadence with weekly demos. Preview URL or sandbox from day one. Production deploys on agreed milestones, never on Fridays.

Launch

QA across browsers and devices, performance budget, accessibility audit, analytics wired. Cutover plan reviewed with your team. Documentation handed over.

Operate

Optional managed retainer with SLA, monitoring, and incremental delivery. Cancel anytime, no lock-in.

Frequently askedThe questions owners ask.

Before kickoff.

We already have an AI assistant someone else built. Can you take over maintaining it?

Yes. We start with an audit of the evals you already have (if any), write the ones that are missing, and hand you the monitoring dashboard you should have had on day one.

How do you catch quality dropping before we notice complaints?

Shadow evaluations run on a sample of production traffic continuously. Drift detection flags a quality drop before it shows up as a customer complaint, not after.

Do you handle model upgrades for us automatically?

No, and that is deliberate. When a new model version ships, we run the regression suite first and decide together whether to upgrade. An automatic upgrade that quietly changes behavior is exactly what this retainer exists to prevent.

What is actually included in the weekly review?

Latency, cost, throughput, and error rate, with alerts that page when quality moves, not just when the system goes down. You get a short written note each week, not a dashboard you have to remember to check.

Is this only for agents you originally built for us?

No. We take on maintenance for AI systems built in-house or by another vendor, as long as the audit confirms we can actually monitor and improve it responsibly.

Already deployed an AI feature and quietly worried about it?

We will audit your evals, write the missing ones, and hand you the monitoring you wish you had on day one.

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