Real Estate & PropTech AI solutions.

Real estate AI solutions for valuation, listing search and resident service, on one platform for listings, tenants and building operations, down to the sensors inside each property.

Start an AI project ↳ AI use cases

What makes real estate AI hard.

The real estate AI challenges we design for before any code is written, so the AI holds up with real users, real data and real auditors.

Fragmented data

Listings feeds, CRMs and property management systems rarely agree. We build the source of truth that valuation and search depend on.

Tenant experience

Payments, maintenance and an assistant that answers resident questions, in one app people actually use.

Building systems

Access control, metering and IoT devices integrated securely at the edge, feeding clean data to dashboards and models.

Real estate AI solutions we build

The AI use cases we build for real estate teams, and the software platforms they run on. Each starts from a measurable goal, passes an eval gate before launch and reaches users through a gradual rollout.

The model work comes from our LLM and AI agent development team, tested by QA and AI evaluation. For results in production, browse our AI case studies.

Compliance we plan for

PCI DSS
SOC 2 Type II
GDPR

✓Valuation and market analytics models
✓AI listing search and descriptions
✓Resident service and maintenance agents
✓Tenant and resident apps
✓Rent collection and payments
✓Smart-building and IoT dashboards

Real estate AI development services.

The WAMO Labs services most real estate AI engagements draw on, from LLM integration to the platform around it.

AI integration

Our AI integration services put LLM applications, AI agents and RAG systems into the products and workflows you already run. Measured by evals, guarded in production, with a cost per request you can predict.

Custom web

Custom web application development for fast, AI-ready platforms that scale with traffic, data and your team. Copilots, smart search and clean APIs are part of the architecture, not a bolt-on.

Mobile apps

Mobile app development for iOS and Android, with native polish and AI features users actually use: on-device ML, LLM assistants, voice and camera intelligence, all backed by solid APIs.

Questions about real estate AI projects.

Timelines, cost drivers and compliance, answered plainly. More on how we build and evaluate AI in our AI engineering insights.

Which real estate AI use cases do you build?

Real estate AI projects we build include valuation and market analytics models; AI listing search and descriptions; and resident service and maintenance agents. Each one ships with a versioned eval set, guardrails and a gradual rollout, on the platform work listed above.

How long do real estate AI projects take?

Most engagements start with a four-week immersion. By week 3 a first slice is live behind a feature flag for a small share of users, evaluated and instrumented. By week 4 you have a quarter-by-quarter roadmap with named owners. Full timelines depend on scope, integrations and compliance review.

What drives the cost of real estate AI solutions?

Four things: the systems we integrate with (listings feeds, CRMs and property management systems), the compliance scope (PCI DSS, SOC 2 Type II and GDPR), how much evaluation and human review the use case needs, and inference volume, because cost per request compounds with usage. We size all four during the four-week immersion, so you know what it costs to keep going before you commit to a roadmap.

How do you handle compliance and data privacy in real estate AI?

We plan for PCI DSS, SOC 2 Type II and GDPR from the first sprint and decide which data may ever reach a model provider before anything is built. Every AI feature ships with access controls, an audit trail and human review wherever a wrong answer carries real risk.

Building AI in Real Estate & PropTech?

Tell us the AI use case or product you're working on. We respond within one business day, with a real human and a real opinion.

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