Accuracy monitoring
We track every workflow's accuracy, confidence distribution, and exception rate. You get a monthly report with what changed and why.
Managed AI Operations
We maintain what we built. Monitoring, model updates, new workflows, and accuracy management — so your AI keeps working six months and three years in.
What it is
AI projects don't fail at launch. They fail six months later.
Most AI consultants ship a project and disappear. Three months later the model accuracy has drifted, a vendor changed an API, a regulation updated, and your team is back to manual work. The project becomes a sunk cost.
Managed AI Operations is the retainer that prevents this. We monitor accuracy, update models when foundation providers change them, add new workflows quarterly, and adjust to regulatory and process changes as they happen. Your AI infrastructure stays current, accurate, and audit-ready.
It's how AI implementation becomes infrastructure instead of a project.
What you get every month
Model maintenance
When OpenAI, Anthropic, or your other providers update models, we test, validate, and migrate. You don't lose accuracy to a model swap.
Quarterly workflow additions
One new workflow per quarter included. We pick high-value additions together each quarter.
Regulatory and process updates
When FDA guidance, SEC rules, or your internal processes change, we adjust the workflows to match.
Audit support
When an examiner, auditor, or internal review asks how a workflow works, we help you document and defend it. Audit logs and validation evidence stay current.
Direct access
Slack, email, or scheduled calls. You talk to the people who built your system, not a ticket queue.
Monthly cadence. Quarterly planning. Always-on monitoring.
Monthly
Accuracy and exception report. Any model updates from the past month. Open issues and recommendations.
Quarterly
Workflow review and planning. What's working, what's not, what to add next quarter.
Always
Monitoring, alerting on accuracy drift, and response within one business day on issues.
Monthly retainers from $2k
Quarterly workflow additions are included. Out-of-scope new builds are quoted separately as fixed-price engagements.
Starter
Includes 1-2 workflows with low volume.
From $2,000 - $3,000/month
Standard
Includes 3-5 workflows with standard volume.
From $4,000 - $6,000/month
Scale
Includes 5+ workflows or high volume or compliance-heavy
From $6,000 - $10,000/month
Common questions about Managed Operations.
Can we do this in-house?
Sometimes. If you have a data engineer or ML engineer on staff, possibly. Most regulated SMBs don't, and hiring one costs more than this tier.
Can we cancel?
Yes. Monthly retainer, 30-day notice. You own the workflows we built — if you leave, they keep running. We just stop maintaining them.
What if a workflow breaks?
Monitoring catches most issues before you do. When something breaks, we respond within one business day and fix it under retainer.
What counts as a "new workflow" vs. an "update"?
Updates to existing workflows (new edge cases, rule changes, integration tweaks) are included. New workflows from scratch are the quarterly addition — anything beyond that is scoped separately.
Do you require Managed Operations after a build?
No. Most clients choose it because the math works. Some operate workflows themselves. We'll tell you honestly which makes sense for your situation.
How this fits with the rest.
Managed Operations works with anything we've built — Data Foundation pipelines, Workflow Automation, or both. Most clients start managed retainer immediately after their first workflow ships.
Find out what ongoing management actually looks like.
A 30-minute call. We'll walk through what's included, what's not, and whether Managed Operations makes sense for your stage.