Build Governed AI Agents for Lease Workflows with Python and FastAPI
Group: Capstone Project
Product Category: AI Engineering
Sub Category: AI Agent Engineer
Solution Available
Source code, datasets, and other related files for the solution will be provided.
Prerequisites
About this Product
A property team gets hundreds of tenant messages a month, and an AI agent that acts on them without controls can approve rent changes or leak tenant data.
What you build
- Supervisor and specialist agents: a supervisor routes each tenant message to application, lease, rent and service request agents.
- Tool registry: every agent tool has a risk tier, JSON schema, scope, budget and kill switch.
- Approval queue: consequential actions such as renewal offers wait for a different staff member to approve, with expiry and rejection handling.
- Guardrails and traces: untrusted text is ignored, PII is masked, and every run is checkpointed and traced.
- Evaluation gate: a golden set decides whether a change to the agents may ship.
Skills you practise
- Multi-Agent Orchestration: routing, run state machines, budgets and resume after failure.
- Tool Governance: scopes, schema validation, idempotency keys and bounded retries.
- Human-in-the-Loop: four-eyes approval, expiry and idempotent decisions.
- Observability: structured logs, spans, Prometheus metrics and an audit log.
Outcome
- Production ready agent system: a tested FastAPI service with an approver console, a PostgreSQL store and a written production design.
Resources
Topics
Skills
Languages
English
Level
Advance
Business Domain
Real Estate and Tenant Management
Project Mentors
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