Build a Real Estate Compliance Agent with Tool Calling and RAG
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
Real estate coordinators track contingency deadlines, required documents and regulatory compliance manually across spreadsheets and email, risking missed disclosures, incomplete HOA packages and legal or financial exposure.
What you build
- Agent orchestrator: A six-stage deal workflow (offer → contract → documents → due diligence → regulatory review → cleared-to-close) with hard stage-gating invariants enforced in code, not left to LLM discretion.
- Tool-calling planner: LLM-driven or deterministic mock planner selecting and invoking five domain tools: offer validation, contract generation, document tracking, due diligence checklist, and regulatory compliance checking.
- RAG compliance layer: Ingest, chunk and embed Northbridge's rulebook, contract clauses and HOA guides; answer regulatory questions with grounded citations and a "no match" fallback.
- State and memory store: SQLite persists all deals, offers, contracts, documents, tasks and tool calls; a rolling per-deal memory summary survives restarts and provides auditable history.
- FastAPI service and CLI: Create and advance deals, query status, ask compliance questions; run with real or mock LLM for zero-cost development and testing.
Skills you practise
- Agent workflows: Design stage-gated workflows with hard gating invariants that prevent skipping required checks.
- Tool calling: Build tool schemas, parse LLM tool-calling decisions and invoke domain tools reliably. structured fallback.
- RAG for compliance: Chunk and retrieve regulatory documents; ground answers in citations with
- State persistence: Design and query SQLite schema for deal lifecycle, tasks and memory summaries.
- Deterministic business logic: Implement earnest money, contingency dates, document completeness and AML checks as rules, not LLM judgment.
Outcome
- Portfolio-ready AI agent: A complete end-to-end workflow agent from ingestion through compliance-gated deal completion, deployable on your machine with zero API costs.
Interview Q&A Included
1 practice set bundled with this lab
-
Real Estate Compliance Agent Assessment
Category: AI Engineering Subcategory: AI Agent Engineer 93 questionsThis assessment checks what you learned while building a real estate transaction compliance agent. Questions follow the lab and are split into six groups: Business Scenario and Scope, Business Rules …
Resources
The complete brief for the real estate compliance agent you build: the problem, the users, the rules and how success is measured.
- Business scenario: coordinators tracking deadlines, documents and disclosures by hand across spreadsheets and email
- 28 functional requirements and 8 business rules, from earnest money and deadlines to AML review and stage gating
- Grounding and fallback rule for compliance answers, with worked numeric examples for every rule
- Data model, the six API endpoints and five use cases, including a regulatory check that blocks a deal
- 28 acceptance criteria, learner deliverables and the minimum completion criteria for the lab
- Technology stack, project structure, failure scenarios, security notes and a glossary of domain terms
Topics
Skills
Languages
English
Level
Intermediate
Business Domain
Real Estate and Transaction Compliance
Project Mentors
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