Case study, 2025
Crewline: a platform that provisions digital employees
Businesses wanted AI that finishes tasks inside their own tools, not another chat window.
What I built
- Architected the multi-agent orchestration layer, the agent runtime and the platform connectors.
- Designed a tool and skill registry so new agents deploy fast, with access control and observability built in.
- The core idea: not a chatbot, a provisioned digital worker with tools, permissions and accountability.
This is confidential client work, so the product name is a stand-in and there are no product screenshots. The architecture and the sample run show how it works.
- Python
- FastAPI
- OpenAI SDK
- Multi-agent systems
- Next.js
- PostgreSQL
How it works
Select any node to see what it does.
- 00.00orchestratortask received: reconcile March invoices
- 00.41plannerplan: fetch ledger, match invoices, flag gaps
- 02.10executortool call: erp.fetch_ledger(month=3)
- 04.52reviewer3 mismatches flagged for a human
The architecture, step by step
Each part of the diagram, in the order a run moves through it.
- Business requestWhere every run starts.
- OrchestratorRoutes every task to the right agent and keeps the shared context.
- PlannerBreaks the request into steps and picks the tools for each one.
- ResearcherCollects the facts and documents the plan needs.
- ExecutorRuns the tool calls inside your own systems.
- ReviewerChecks each result and flags anything a human should see.
- ToolsThe agents act through the skill registry, CRM, email, docs, access control and tracing.
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