Real Estate · Generative AI & RAG
Ask the lease, get the clause.
Retrieval across leases, society bye-laws, title documents and listing packs — returning the clause, the document and the date rather than a summary you can't verify.
- Retrieval pipelines
- Fine-tuned domain models
- Multimodal (text · image · voice)
- Eval + guardrails
What we build
Generative AI & RAG for real estate, specifically.
- 01
Lease clause lookup
Break clauses, escalation terms, sublet permissions and maintenance obligations retrieved with the exact wording and its page.
- 02
Society and building rules
Pet policies, renovation approvals and parking rights answered from the actual bye-laws, so an agent stops promising things the committee will refuse.
- 03
Portfolio-wide term search
Which leases expire this year, which carry escalation caps — answerable across the portfolio without a spreadsheet somebody maintains by hand.
What we measure
- Accuracy on an agent-graded question set
- Citation correctness against the source document
- Time to answer a tenant or buyer query
Instrumented in week one and reported weekly. These are the numbers the engagement is judged on — not a forecast of what they'll be.
Constraints
What has to be true in real estate.
- 01
The agent qualifies; a human sells
It captures requirements, answers factual questions from the listing, and books the viewing. Negotiation and advice stay with a licensed agent — in most markets that's a legal boundary as well as a good idea.
- 02
Listing data is read live
Availability, price and status come from your CRM at query time. Advertising a property that went under offer yesterday is a complaint, not a lead.
- 03
Consent and channel rules are built in
Opt-outs are honoured across channels and quiet hours are respected — WhatsApp and telecom rules in India and the EU both make this a compliance matter, not a courtesy.
How it runs
The Generative AI & RAG engagement, step by step.
- 1
Data inventory
What docs / databases / APIs / feeds matter? What's PII vs public? What changes daily vs quarterly? We map it before writing code.
- 2
Retrieval architecture
Hybrid (BM25 + vector) retrieval, chunking strategy, reranking, citations. Tuned for your domain not a generic benchmark.
- 3
Eval suite
Real-world question set with golden answers. Faithfulness, context precision, latency. So you know when changes ship a regression.
- 4
Guardrails
Prompt-injection defense, PII scrubbing, refusal patterns, output schemas. Especially critical for customer-facing deployments.
- 5
Production + iterate
Cost-effective inference (caching, fallback models), monitoring, weekly eval reports. Fine-tune when the data justifies it.
Integrations
Systems we wire into for real estate.
- Salesforce & HubSpot
- Zoho CRM
- MagicBricks, 99acres & Housing feeds
- WhatsApp Business API
- Twilio voice
- Calendly & Google Calendar
- DocuSign
FAQ
RAG for leases and property documents: your questions.
Our leases are scans of signed originals. Will this work?
Yes, with OCR and layout-aware extraction — and handwritten amendments in the margin are the honest failure case. We report accuracy per document type before you rely on it.
Can tenants use it directly?
Yes, scoped to their own lease and the building's public rules. Retrieval permissions are per-document, so a tenant cannot reach another unit's agreement.
Should I use RAG or fine-tuning?
RAG for facts that change. Fine-tuning for style, format, or domain reasoning. Most production systems use both — and we'll tell you which mix is right after a 1-week discovery.
Can I use my own LLM (open-weights)?
Yes. We work with Llama, Mistral, Qwen, and similar — useful for data residency, cost predictability, and air-gapped environments.
Contact
Talk to us about generative ai & rag for real estate.
Two or three sentences about the workflow you'd start with. We reply within one business day.
Or skip the form — book a Calendly slot directlyadmin@neuroxai.com · +91 70149 99768
Remote-first team across India · US · EU · HQ in Udaipur, India
More for Real Estate
Other work we do in this vertical.
- AI agents for real estate lead responseAgents that respond to portal and website leads instantly across WhatsApp, voice and email — qualifying against your criteria and booking the viewing into a real calendar.Read
- AI growth marketing for real estateListing content at portfolio scale, paid and lifecycle automation, and attribution that follows a lead through to a booked viewing and a closed deal.Read
Same service, other industries
Generative AI & RAG elsewhere.
- RAG for banking and financial servicesRetrieval over circulars, product terms and internal procedure — returning the clause, the revision date, and a link to the page it came from.Read
- RAG for healthcare and clinical documentsRetrieval over clinical guidelines, payer policy and internal SOPs — with the citation, the version, and an explicit refusal when the library doesn't cover the question.Read
- AI product search and catalogue RAGSemantic search and grounded product Q&A over your catalogue, reviews and size guides — with stock and price read live rather than remembered.Read