LLM Agents in Enterprise Workflows: What Actually Works in Production
Agents that read documents, score risks and route decisions are leaving the pilot phase. The lessons from shipping agent workflows for construction, operations and compliance teams.
By David Kukharchuk
Tech Lead at Mirko
Business-first, not model-first
The agent projects that reach production start with a workflow, not a model. Which documents arrive, who approves what, which system holds the record and what a wrong answer costs. Once that is mapped, the choice of orchestration framework and model is a technical detail.
A reference architecture
The layers we use in enterprise agent systems
- Enterprise integration: ERP, CRM, document management, procurement.
- Data and workflow orchestration: queues, background workers, audit trails.
- Agent layer: LangGraph-style graphs with explicit steps and tools.
- Management intelligence: dashboards, alerts and recommendations.
- Reliability: role-based access, monitoring, recovery and backups.
Every agent action that changes data goes through the same permissions and audit log as a human action. That single rule removes most of the objections security and compliance teams raise.
Where agents add value today
Document intelligence for contracts, invoices and submittals. Risk scoring for schedules and budgets. Issue clustering and prioritisation for operations teams. Recommendations with a human approving the final step. In an AI construction management platform these turned reporting into a proactive control loop.
What to avoid
Open-ended chat interfaces with no defined task. Agents that write directly to systems of record without review. Pilots with no success criteria. A two-hour discovery workshop that maps workflows, systems, data constraints and pilot metrics prevents all three.
