Keep your AI workforce accountable, measurable, and improving.
Managed Operations keeps your AI workforce performing as your business changes. Our managed AI services provide the monitoring, evaluations, tuning, and support behind it.
Start with an AI Workforce Review: a 45-minute conversation to find the first one or two roles for your team. Nothing to prepare.
Built for teams with production AI systems that need operational ownership without building an internal AI operations function.
Why production AI systems degrade without operational ownership
Production AI needs active monitoring, maintenance, and continuous optimization to stay reliable.
Outputs drift silently
A system that passed eval in week 1 starts producing subtly worse results by month 3. Nobody notices until a customer does.
AI infrastructure evolves constantly
Models, APIs, vendor capabilities, and costs change continuously. Without active ownership, production systems fall behind.
Context goes stale
Your CRM, docs, and playbooks change weekly. The agent's context layer needs to change with them, or the outputs stop matching reality.
No clear owner
Without ownership, production AI becomes a reactive burden for whoever notices the problem first.
Keep your AI roles dependable as the work changes.
Keep everyday work dependable. Metacto monitors your agents, investigates failures, and tests fixes before releasing them.
Scroll across to follow the full workflow →
What Managed Operations delivers
Monitoring, evaluation, and improvement that keep production AI systems reliable as your business changes.
- Production monitoring with defined reliability, performance, and cost thresholds
- Evaluation coverage for model, prompt, context, and workflow changes
- Ongoing prompt, context, and workflow tuning as your business evolves
- Model upgrade path with benchmarking, migration, and re-evaluation
- Incident response with agreed responsibilities and documented runbooks
- Regular operational reviews and expansion roadmap
How Managed Operations engagements start
We establish the monitoring, evaluations, and support behind Managed Operations. Your roles stay in your environment; Metacto keeps the system accountable and improving.
Operational AI review
We review the agents and workflows currently in production, what they do, who owns them, how they were built, and where reliability or adoption risk exists.
A clear view of operational scope, risk, and ownership.
Monitoring and evaluation baseline
We wire up monitoring, logging, evaluation coverage, and performance baselines across accuracy, latency, cost, and adoption.
A dashboard and operating baseline your team can trust.
Continuous operations
Metacto monitors, tunes, upgrades, and responds while your team focuses on the business.
Operational AI systems that keep improving instead of degrading.
Keep the roles your team depends on worth trusting.
45 minutes. We look at where recurring work is costing the most time and margin, and map the first one or two roles around it. Nothing to prepare.
Managed Operations in practice
Production renewal briefs · operating example
The problem
A CRM schema change removes a field from renewal briefs. Complex accounts become harder to review, and the customer success team starts rebuilding the missing context manually.
The outcome
Metacto traces the missing field to the source change, updates the context and regression checks, and tests the fix before release. The team gets complete renewal briefs again instead of rebuilding the account history by hand.
Common questions
What managed AI services does Managed Operations include?
Monitoring, evaluations, prompt and context tuning, model upgrades, incident response, and regular roadmap reviews for systems already in production. New workflows or agents are scoped separately.
Can you support systems Metacto didn't build?
Sometimes. If the system architecture is compatible and the implementation meets operational standards, we can scope an onboarding phase before assuming support ownership.
What are the SLAs?
Service levels are set per engagement based on the workflow’s business criticality. We agree reliability and performance targets, support coverage, and incident response responsibilities for your systems.
How is it priced?
Managed Operations is a 12-month agreement covering an agreed set of active roles. Scope is set at the AI Workforce Review. Cloud and model usage are billed directly to your account at your rates, with no markup.
Where does it run?
The roles run in your own cloud, within your security boundary and scoped access. Metacto monitors, evaluates, and improves the system. The deployment and the business intelligence it builds stay yours.
What happens when Managed Operations ends?
Stop the service, keep the workforce. Deployed roles stay in your environment and keep running on their last version. What ends is Metacto’s ongoing monitoring and improvement. Commitments follow the agreed contract.
Is this the right fit?
Good fit
- One or more production AI workflows or agents with real operational dependency
- No dedicated internal AI operations capability
- Need monitoring, tuning, evaluation, and incident response
- Willing to invest in operational ownership to protect business outcomes
Not a fit
- Pre-production AI experimentation
- Looking for implementation rather than operations support
- Staff augmentation needs
- No access or operational ownership model
How your AI workforce takes shape
Keep improving the workforce behind the work.
Metacto connects ongoing operations with the business context and engineering needed to keep your AI roles useful.
AI Consulting & Implementation
Take the right workflow from idea to production.
Find the next workflow worth changing, with a clear business case and a path from strategy into production.
Explore consulting and implementationAI Agents & Workflows
Get the work done inside the tools you already use.
Build or extend AI roles around the recurring work your team needs help with, connected to their existing systems.
Explore AI agents and workflowsOpportunity Mapping
Know where to start when the choice is not obvious.
When you need a closer look, compare the value and readiness of your workflows before committing to a build.
Explore Opportunity MappingContext Engineering
Give agents the knowledge to get the work right.
Keep agents grounded in the records and rules your team works from, so changing information does not become recurring rework.
Explore Context EngineeringOne workforce. Built and managed around your business.
See how the roles, ownership, and ongoing improvement fit together.
See where dependable AI support makes a difference.
Explore all industries →Construction
Get project paperwork out of the way.
Bids, RFIs, and change packages prepared from the records your team already uses.
Explore workflowsManufacturing
Keep missing information from slowing production.
Inspection evidence and exception records ready for the people who make the call.
Explore workflowsMSP & IT Services
Give technicians more time for difficult requests.
Account context, routine steps, and escalation details brought into the ticket.
Explore workflowsKeep a clear view of how your AI roles are performing.
Know what to monitor after launch
Track quality, exceptions, cost, and whether the role is helping the team.
Read the monitoring guide about Know what to monitor after launchCatch regressions before they spread
Recheck real examples when models, prompts, or business context change.
Explore evaluation and regression testing about Catch regressions before they spreadRespond when an output goes wrong
Contain the issue, trace its cause, and verify the fix before restoring the task.
Read the incident response guide about Respond when an output goes wrongManaged Operations
Give your existing AI systems a clear path to better performance.
45 minutes. We look at where recurring work is costing the most time and margin, and map the first one or two roles around it. Nothing to prepare.
Your Review request is received.
Our team will follow up to arrange your 45-minute AI Workforce Review. Nothing to prepare.
Explore Managed AI Workforce