AI managed operations, the senior team that keeps it running.
AI agents in production are more like a product than a project. They need ongoing prompt tuning, eval set updates, drift monitoring, cost optimization. Most teams don't have AI ops talent in-house. We run AI in production for you with senior team on retainer.
Retainers that keep AI honest in production.
Four real AI managed-ops engagements.
12 months · 3 agents tuned monthly
Anchor's three production agents get monthly prompt tuning, eval set refresh, and drift monitoring.
9 months · cost cut 40%
Promptly's AI cost dropped 40% through model selection optimization, prompt compression, and caching.
18 months · HIPAA monitored
Anchor's RAG system runs in HIPAA-aware infra with quarterly audits, drift detection, and sustained monitoring.
6 months · 2 net-new agents
AdLib's retainer added 2 net-new agents (lead scoring, content drafting) within the same monthly retainer.
When AI managed ops fits, and when it truly doesn't.
Below is the honest read.
Right fit when
- You have AI agents or workflows running in production and need ongoing maintenance.
- Prompt tuning, eval set evolution, and drift monitoring exceed your team's bandwidth.
- You want senior AI engineers on every ticket, not a junior consultant.
- Cost optimization, model selection, and prompt compression are valuable to you.
- You expect AI to evolve as your business and data evolve.
Wrong fit when
- Your AI is a one-shot prototype that won't materially evolve.
- Your team has strong AI ops talent in-house and only needs occasional consulting.
- You only need 5 hours a month of AI work. Not the most cost-efficient option for tiny scopes.
- Your AI volume is so low that ongoing tuning isn't justified by impact.
What our AI retainer actually covers.
Below is the typical structure across the three retainer tiers.
$5K-$10K monthly · keep it running
Quality monitoring. Drift detection. Cost tracking. Minor prompt tuning. Eval set updates. Slack on-call.
$10K-$15K monthly · maintain + new
Everything in Maintain plus 1 to 2 net-new agents per quarter. Senior team on every ticket.
$15K-$25K monthly · senior advisory
Everything in Build plus quarterly strategy sessions, fine-tuning projects, custom evaluation infra, multi-agent orchestration.
From kickoff to AI that compounds in production.
Five steps. Built to make AI in production feel reliable, not fragile.
Scope
Two sessions with leadership and ops. What's covered, what triggers a change order, escalation paths. Scope written down.
Cadence
Weekly 30-min standup with retainer pod. Monthly business review. Quarterly strategy session. Always-on Slack channel.
Tickets
Standard tickets in Slack. Larger work via quick-spec doc. Net-new builds get a separate sprint plan. Senior team on every ticket.
Reporting
Monthly retainer report. Quality metrics, cost trends, prompt changes, eval set evolution. No surprise overruns.
Optimize
Quarterly review proposes 3 to 5 high-leverage improvements: cost cuts, eval expansion, new agents. We don't wait for you to ask.
Inside an AI managed operations retainer.
Real deliverables, not bullet points. Below is the typical scope across tiers.
Maintain
- ·Quality monitoring + drift detection
- ·Cost tracking and anomaly alerting
- ·Minor prompt tuning and eval set updates
- ·Monthly business review
- ·Slack-channel async support
Build
- ·Everything in Maintain tier
- ·1 to 2 net-new agents per quarter
- ·Major prompt revisions and eval expansion
- ·Quarterly strategy sessions
Strategic
- ·Everything in Build tier
- ·Fine-tuning projects
- ·Custom evaluation infrastructure
- ·Multi-agent orchestration
- ·Senior AI advisory access
Add-ons
- ·Net-new custom AI development scoped separately
- ·Migration to new model providers
- ·HIPAA / SOC 2 audit support
- ·Executive AI strategy advisory
Monthly. Tier-aware. Senior team always.
Maintain: $5,000-$10,000 monthly. Build: $10,000-$15,000 monthly. Strategic: $15,000-$25,000 monthly. 12-month minimum on Build and Strategic, 6-month minimum on Maintain.
Things people ask.
What's the difference between this and AI custom development?+
Custom development is a fixed-scope build (4 to 10 weeks). Managed operations is ongoing (12+ months) and covers maintenance, tuning, and net-new builds within the retainer envelope. Most customers do custom development first, then move to managed ops.
Can you take over an AI system someone else built?+
Yes. We've adopted 8+ AI systems built by other consultancies or internal teams. We review the code, eval methodology, and monitoring, then propose what to keep, what to refactor, and what to rebuild.
What's covered vs not covered?+
Covered: ongoing tuning, eval evolution, drift monitoring, cost optimization, minor prompt revisions. Not covered without scope expansion: net-new custom systems, fine-tuning projects beyond Build tier, migration to new model providers.
Who's on the retainer pod?+
Senior team. Typically a senior AI engineer as retainer lead, plus solution architects and ML engineers as needed. We don't put junior consultants on AI retainers.
How do you handle on-call?+
Slack-channel async support during business hours included. Pager-style on-call available as an add-on for production-critical AI systems. Most customers find Slack-async sufficient with monitoring tuned to catch issues early.
How do we get started?+
Book a 30-minute strategy call. We'll cover scope, current platform state, and the right retainer tier. Proposal within 48 hours if we're a fit.
How INSIDEA works
