Managed retainer
Managed AI agent operations so your team does not inherit a fragile deployment.
The managed retainer is what keeps the deployment useful after launch. We stay in the loop for support, monitoring, optimisation, and controlled expansion of your AI workforce.
Powered by OpenClaw + NVIDIA NemoClaw. Deployed and operated by Agentex — India's only managed AI employee deployment partner.
Most enterprise AI deployments fail not because the technology doesn't work — they fail because no one maintains them after go-live. The model drifts, the integrations break, the team that managed the deployment leaves, and the AI employee gradually stops being useful. The managed retainer exists to prevent this.
Agentex's managed AI operations retainer is a structured post-deployment engagement that keeps your AI employees working at full effectiveness: monitoring for anomalies, responding to incidents, optimising performance over time, and expanding the deployment in a controlled way.
What managed operations covers
The retainer includes: real-time monitoring of all deployed AI employees; incident response within agreed SLA for critical failures; monthly optimisation cycles to reduce escalation rates and improve response accuracy; controlled rollout of new workflows or integrations; and a monthly operations report showing what the AI employees handled, what they escalated, what they cost, and what changed.
Escalation rate optimisation
The primary quality metric for any AI employee is escalation rate — the percentage of interactions routed to a human instead of handled autonomously. A high escalation rate means the agent is uncertain, poorly scoped, or encountering cases outside its training data. Agentex's optimisation work focuses on systematically reducing escalation rate through role definition refinements, expanded test cases, and targeted integration improvements.
Controlled workflow expansion
The Sprint deploys one workflow. The retainer is where the second, third, and fourth workflows get added — each scoped, tested, and deployed with the same rigour as the original Sprint. We do not expand scope without a defined rollout plan and acceptance criteria. Scope creep in AI deployments is a reliability risk, not a feature.
Transparency and reporting
Every month, you receive a full operations report: total interactions handled, escalation rate breakdown, cost per interaction (AI token usage at provider cost, no markup), incidents and resolutions, and the next month's optimisation priorities. You always know exactly what your AI employees are doing and what they cost.
Frequently asked questions
Is the retainer required after the Sprint?
No. The Sprint delivers a fully functional, documented AI employee. You can run it independently after the Sprint. The retainer is optional and designed for teams that want Agentex to maintain and expand the deployment.
What is the minimum retainer duration?
Three months. This gives enough time for the first optimisation cycle and at least one workflow expansion to show value. Month-to-month renewals are available after the initial three months.
How is AI token cost handled under the retainer?
Agentex charges AI token costs at provider cost with zero markup. You receive monthly receipts showing exactly what was consumed. Token cost is invoiced separately from the retainer management fee.
Can we add new workflows without a new Sprint?
Simple workflow additions are handled within the retainer at no extra cost. Complex new workflows — with new integrations, new channels, or significantly different role logic — are scoped as mini-Sprints with a fixed additional fee.
Ready to deploy your first AI employee?
Book a 30-minute discovery call. We'll scope your first workflow and give you a fixed-cost Sprint proposal within 48 hours.