Real Estate & Construction Tech

RAG & Knowledge Retrieval for Real Estate & Construction Tech

RAG & Knowledge Retrieval for real estate & construction tech, built around the constraint that defines the sector: transactions are document-heavy and slow, and lead quality varies enormously.

Regulations in scope
4
Systems we integrate
4
Typical first release
6 weeks

What changes when it is real estate & construction tech

Orqent Labs builds RAG systems where accuracy is measured against a labelled question set, so you know the number rather than trusting a vibe.

In real estate & construction tech, transactions are document-heavy and slow, and lead quality varies enormously. That single fact reshapes how rag & knowledge retrieval has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is title and agreement document review, usually integrated against CRM. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Multi-model by default, so a provider outage is a routing decision rather than an incident. You own the code, the models where they are open-weight, and the documentation to run it without us.

The sector constraints we design around

Defining constraint
transactions are document-heavy and slow, and lead quality varies enormously
Regulations in scope
RERA compliance · DPDP Act 2023 · stamp duty and registration requirements · building approvals
Systems of record
CRM · property management · ERP · document management
Where we usually start
lead qualification and routing

RAG & Knowledge Retrieval workloads in real estate & construction tech

  • lead qualification and routing
  • title and agreement document review
  • site progress from imagery
  • customer service automation
  • RERA documentation

What is included

  • Ingestion pipeline for your real document formats
  • Chunking and embedding strategy tuned to your corpus
  • Hybrid keyword plus vector retrieval with reranking
  • Citations on every answer, traceable to the source page
  • Permission-aware retrieval that respects existing access rules
  • Retrieval quality benchmarked against a labelled question set

Questions from this sector

Can it qualify leads reliably?

Yes, scored on your actual conversion history rather than a generic model, with conversational qualification before a site visit is scheduled.

What about title documents?

Extraction and consistency checking flag discrepancies for legal review. It accelerates review. It does not replace the lawyer's opinion.

RAG or fine-tuning?

RAG for knowledge that changes and must be cited; fine-tuning for style, format and task behaviour. Most production systems use RAG for the facts and light fine-tuning or few-shot prompting for the form.

How accurate will it be?

We build a labelled question set from your domain and report retrieval precision and answer accuracy against it. That number is the deliverable. We do not ship a system whose quality nobody has measured.

Can it respect our existing permissions?

Yes. Retrieval is filtered by the user's actual entitlements, so the assistant can never surface a document the user could not already open.

RAG & Knowledge Retrieval for real estate & construction tech, worth a conversation?

Tell us the workload and the regulation it sits under. We will tell you what is realistic.

Or email bd@dtrasglobal.com · call +91 74118 77878