Agentic AI Services
Three ways we take agentic AI from pilot to production: Diagnose & Advise, Design & Build, and Deploy & Operate. Every engagement starts by fixing the process, then automating it with governed AI agents.
From Pilot to Production
We start with a fixed-scope readiness diagnostic, build agents around the workflows it identifies, and operate them with monitoring, human approvals and audit trails until your team is ready to take over.
Diagnose & Advise
Find out what is ready to automate, and what has to be fixed first.
AI Workflow & Readiness Diagnostic
A fixed-scope diagnostic that maps your systems, ownership, definitions and workflows, sets a measured baseline and ranks the use cases worth automating.
Governance & Trust Center
Least-privilege agent access, human approval at consequential decisions and full observability, designed in from the start.
How We Engage & Price
Four engagement models and a four-stage path from diagnostic to enterprise rollout, with written specifications and regular reporting.
Design & Build
Governed AI agents built around the workflows the diagnostic identifies.
Agentic AI Development
AI agents that plan and use tools inside the permissions you set, integrated with your applications, data and approval steps.
Multi-Agent Systems
Coordinated agents with defined roles, hand-offs and escalation paths for workflows that are too large for a single agent.
RAG & Knowledge Systems
Retrieval-augmented generation over your own documents and data, with source citations and evaluation against benchmarks agreed with you.
MCP & Legacy System Integration
Connect agents to ERPs, CRMs and legacy systems through APIs, middleware and Model Context Protocol servers, with controlled tool permissions.
Customer Support Automation
Agents resolve routine requests end-to-end and escalate exceptions to your team, with conversation history and audit logs.
Deploy & Operate
Run agents in production with monitoring, rollback and clear ownership.
AgentOps & MLOps
Deployment pipelines, versioning, rollback and incident response for agents and models in production.
AI Performance Monitoring
Tracking of cost, latency, accuracy and agent behavior against the measured baseline, with alerts and regular reporting.