Keep your production AI healthy.
Shipping the agent is the start, not the finish. We monitor, improve, and own the health of your production AI — evals, drift, versioning, vendor changes — tied to the metrics that matter.
Everything it takes to stay in production.
Production AI isn't software you ship and forget. This is the operating layer that keeps it working.
Continuous evals
Regression suites run on every change, so quality never silently degrades.
Drift & quality monitoring
We watch accuracy, latency, and cost in production and catch drift before your users do.
Prompt & model versioning
Every prompt and model change is versioned, tested, and reversible.
Vendor-change response
When OpenAI, Anthropic, or your platform ships a breaking change, we absorb it.
Guardrails & fallbacks
Safety rails and graceful degradation so a bad input never becomes a bad outcome.
Quarterly roadmaps
We keep improving the system against your KPIs, not just keeping the lights on.
Instrument. Operate. Improve.
Observability in
We wire up monitoring, evals, and alerting against the metrics you care about.
Keep it healthy
We watch, tune, version, and respond — so the system stays reliable under real load.
Raise the ceiling
Quarterly, we improve accuracy, expand coverage, and tie results to your KPIs.
Priced to the systems you run.
All tiers tie reporting to your KPIs — resolution rate, uptime, accuracy — so you see what you're paying for.
Monitoring, maintenance, and incident response for a single production agent.
Plus monthly improvements and a roadmap.
Full operating partnership with quarterly strategy.
Operating cost, next to the build.
Budgeting for the build and forgetting the running cost is the most common mistake in an AI plan.
A 140-person consulting firm pays $4,500 a month to keep its AI systems running.
The build was $156,000 across three phases. Operations sit inside a Year 1 total of $210,000, against $480,000 a year in recovered value. That engagement was priced on its own scope, between our Light and Standard tiers. Read the case study.
We are not a vendor who hands you the keys and vanishes the first Monday something breaks. We stay on the hook — because in production, reliability is the product. This isn’t chatbot babysitting; it’s the operating layer that keeps production AI earning its keep.
Questions about managed operations
How much does it cost to maintain an AI agent after launch?
At Gigabit, $3,000 a month for one production system, $8,000 for three, and $20,000 for five or more or a production agent platform. That covers monitoring, evals, drift, prompt and model versioning, and response when a model vendor changes something. One consulting client pays $4,500 a month to operate the AI systems we built for them over six months.
Who runs an AI agent once it has been built?
Someone has to be named before launch: your own team, the vendor who built it, or an operations partner. Gigabit runs systems on a monthly retainer, including ones built by your team or another vendor, and starts with an audit before taking over.
Do you only operate systems you built?
No. We can take over operations for AI systems built by your team or another vendor. We start with an audit, instrument observability and evals, and then own the health going forward.
What does "tied to the metrics that matter" mean?
We agree on the KPIs your AI is supposed to move — resolution rate, deflection, accuracy, cost per task — and report against them, not vanity uptime numbers.
How is this priced?
Managed AI Operations runs $3,000–$20,000/month: Light ($3K, 1 system), Standard ($8K, 3 systems), Heavy ($20K, 5+ systems or an agent platform). It's priced to the scope and number of systems under management.
What happens when a model vendor ships a breaking change?
We absorb it. Model deprecations, API changes, and behavior shifts are part of what we monitor and respond to — so your team is never blindsided.
From the field notes
Already in production? Let's keep it that way.
Whether we built it or you did, we'll instrument it, operate it, and tie it to your KPIs.