GO-LIVE IS THE START. WE KEEP SCORE.
Monitoring, evaluation, support and security upkeep for your AI systems, private or cloud, plus KPI and ROI reporting against the targets agreed before the build.
THIS DOMAIN INCLUDES //
MONITORING & EVALUATION
WHAT IT IS //
Monitoring tracks whether an AI system still does its job: answer quality, error and escalation rates, latency and cost per completed task. Evaluation re-tests it against agreed benchmarks.
WHAT WE DO //
We set up dashboards and regular evaluations on real traffic, flag drift and failures early, and report against the KPIs agreed before the build.
SUPPORT & MAINTENANCE
WHAT IT IS //
Managed support covers incidents, user questions and small changes, so the system keeps working as your business changes. It takes over when the early life support that comes with every build ends.
WHAT WE DO //
We take support requests, fix issues, tune prompts, workflows and integrations, and handle small changes on a monthly retainer. If you would rather run the system yourselves, we train your team and stay on as second-line support.
SECURITY & MODEL UPKEEP
WHAT IT IS //
Models, libraries and infrastructure need regular updates and security patches. In an on-premise system no cloud provider does this for you, so someone has to own it.
WHAT WE DO //
We plan model updates and security patches, test them before rollout, review access, and maintain backups and a recovery plan — including for systems that run on your own hardware or air-gapped.
INCIDENT READINESS FOR AI
WHAT IT IS //
AI systems need their own incident readiness. When an agent misbehaves, is manipulated or depends on a tool that has been compromised, the team has to know what exists, what the agent did, what it was allowed to do, how to contain it and who does what.
WHAT WE DO //
We keep a live inventory of agents with their owners, tools and permissions; record each run from request to action; maintain a stop switch to pause, revoke and isolate an agent while preserving evidence; and rehearse the hand-offs between your IT, security, application and business teams. Alerts feed your existing SOC.
CONTINUAL IMPROVEMENT
WHAT IT IS //
Continual improvement is the routine that keeps an AI system getting better after go-live: measure, review, decide what to change, change it safely and check that it worked — on a fixed cadence rather than when something breaks.
WHAT WE DO //
We run a monthly service review and a quarterly value and risk review, keep an improvement backlog ranked by payback, re-run the evaluation after every model, prompt or tool change, and feed the findings into a refreshed roadmap, so the next cycle starts at the audit with real numbers.
COST & PERFORMANCE TUNING
WHAT IT IS //
Tuning balances quality, speed and cost over time — routing tasks to the right model, caching, trimming prompts.
WHAT WE DO //
We review cost per completed task and quality every quarter and re-balance models and infrastructure — including moving work between private and public models where the data allows.
AI VALUE REALIZATION
WHAT IT IS //
AI value realization ties an AI system's results to its business case (hours saved, revenue protected, errors avoided, cost per task) and tracks them until the value shows up in your P&L.
WHAT WE DO //
We take the value case and KPIs agreed before the build, instrument the system to measure them, report projected against actual on a fixed cadence, and recommend the next workflow to automate — or to stop, if the numbers don't support it.
PROBLEM //
- AI systems degrade quietly as data and usage change, and nobody checks.
- After handover nobody owns the system, so small problems become outages.
- Leadership asks "is it paying off?" and nobody can answer with numbers.
OUR APPROACH //
We treat AI like any production system: owned, monitored, patched and measured. Autonomy goes up step by step, from approving every action to escalation only, as the numbers show it is safe. You own everything; we run it, or train your team to run it and stay on as second line.
WHAT WE DO //
MONITOR
- Quality, drift, errors, escalations
- Cost per completed task
- Alerts and a regular review
SUPPORT
- Incident response
- Prompt, workflow and integration tuning
- User support
SECURE & MAINTAIN
- Model updates and security patches
- Backups and a recovery plan
- Access reviews
- Stop switch and incident rehearsals
PROVE VALUE
- KPI dashboard
- Projected vs actual ROI
- Quarterly model, cost and security review
- Improvement backlog ranked by payback
WHAT YOU GET //
- Ops dashboard with agreed KPIs
- A system that keeps working after handover
- Quarterly model, cost and security review
- A clear answer to "is it paying off?"
DATA// Escalation-based operation — AI handles the volume, humans review exceptions — delivered more than twice the productivity gain of approve-everything setups. The durable advantage was the process and platform around the model, not the model itself. — Stanford Digital Economy Lab, 2026
PATH// this service covers the OPERATE and OPTIMIZE phases of the path — see all services and how it lands on the calendar.
- Your agent's real price is cost per task — the metric that keeps AI honest
- Why 95% of AI pilots fail — what monitoring is designed to catch
- Private & On-Prem AI — what we keep running on your hardware
- AI Security & Governance — the controls we keep current