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Enterprise AI for Real Estate

Enterprise AI for Real Estate

Real estate firms manage thousands of leases, property records, and tenant relationships across large portfolios. Most of this work still runs on spreadsheets, manual document review, and email chains. We build AI systems that give your asset management and operations teams the speed and accuracy they need to manage at scale.

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Up to 92%
faster lease abstraction per document
Up to 58%
of tenant inquiries resolved by AI
3-6 wks
from kickoff to production pilot

What We See in Enterprise AI for Real Estate

1

Lease abstraction at large commercial brokers takes 6 to 12 hours per lease because analysts manually extract 80+ data points from 60-page documents into ProLease, Visual Lease, or Yardi, and the same work gets redone every time a lease is acquired into a new portfolio.

2

Property valuation analysts manually pull comps from CoStar, Real Capital Analytics, and public records, adjust for local factors, and build models in Excel that take 4 to 8 hours per property in a workflow that repeats thousands of times a year across a portfolio.

3

Lease administration teams in Yardi or MRI track critical dates, rent escalations, CAM reconciliations, and renewal options across hundreds of leases in Excel trackers that are one turnover away from a missed option that costs the asset's NOI for the year.

4

Tenant communications (maintenance requests, renewal notices, billing inquiries, access issues) consume 30 to 45% of property management staff time with repetitive email back-and-forth that AppFolio, Yardi Maintenance, or Building Engines never fully automated.

How We Help

AI Lease Abstraction

The agent reads commercial lease documents (master leases, amendments, side letters, guarantees) and extracts 80+ standard fields into structured data that writes back to Yardi, MRI, ProLease, or Visual Lease. The system handles scanned PDFs and legacy formats. Analysts review low-confidence extractions and sign off rather than typing fields from a 60-page document. Post-abstract, the agent tracks critical dates, options, and escalations automatically.

✓ Lease abstraction time from 6-12 hrs to under 45 min per lease with 95%+ field accuracy

Automated Property Valuation

Our AI pulls comp sales from CoStar, Real Capital Analytics, and your internal deal history, adjusts for property characteristics and local market factors, and generates valuation estimates with supporting analysis and confidence intervals. Analysts review AI-generated valuations and adjust for factors the model cannot observe (property condition, off-market deal context, unique tenancy).

✓ Valuation cycle from 6 hrs to under 45 min with estimates within 5% of appraised value

AI Tenant Communications and Maintenance Triage

AI agents handle routine tenant inquiries across email, chat, and SMS (maintenance requests, billing questions, access issues, renewal inquiries), create work orders in Yardi Maintenance or Building Engines, dispatch the right service provider, and close the loop with the tenant automatically. Complex issues route to a property manager with full context and tenant history attached.

✓ 58% of tenant inquiries resolved without human touch and 36% faster work-order closure

Deal Screening and Market Intelligence

We deploy agents that aggregate data from listing services, CoStar, public records, demographic databases, and your internal deal history to score potential acquisitions against your investment criteria (IRR targets, yield thresholds, geographic strategy, tenancy mix). Acquisitions teams work from a ranked pipeline with supporting data rather than spending days on manual screening.

✓ Deal screening time down 72% with 3.4x more opportunities reviewed per week

Portfolio Performance Reporting

AI pulls data from Yardi, MRI, or RealPage, accounting systems, and market feeds to generate NOI summaries, occupancy reports, leasing activity dashboards, and portfolio-level investor reports. Asset managers and IR teams get weekly dashboards and quarterly investor reports that previously took analysts 2 to 4 days to assemble manually.

✓ Reporting cycle from 2-4 days to under 3 hours with data traced to source

Our Services for This Industry

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Engagement shape

Timeline

A typical real estate engagement runs five to eight weeks to first production. Weeks one and two are discovery: interviews with asset management, portfolio services, and operations leadership, plus a written integration pattern for Yardi, MRI, RealPage, or your property management platform and the relevant data providers. We build an eval set in week two using 200 to 1,000 of your own leases, prior valuations, or deal screens labeled by senior analysts.

Weeks three and four are build. The agent runs daily against the eval set and we share a weekly accuracy scorecard with the sponsor. Weeks five and six cover shadow mode against a paired human queue. Weeks seven and eight are production cutover on one asset class or one portfolio with hypercare for 30 days. Expansion to additional asset classes or portfolios follows the same pattern in two- to four-week waves.

Cost model

Most real estate engagements fall between $75k and $200k for the first production use case. The main drivers are portfolio scale, property management system integration depth, number of asset classes in scope, and whether third-party data subscriptions (CoStar, Real Capital Analytics) are included in scope. A single-portfolio lease abstraction pilot sits near the bottom of the range. A multi-asset-class rollout covering abstraction, valuation, and tenant communications with deep Yardi or MRI write-back lands at the top. Ongoing platform and inference costs typically run $5k to $20k per month in production.

Frequently Asked Questions

Can your AI read lease documents that are scanned PDFs or have handwritten amendments?+
Yes. Our multimodal models handle scanned PDFs, handwritten amendments, side letters, and legacy document formats. For documents with poor scan quality, the system flags low-confidence extractions for analyst review rather than guessing. On typical commercial lease portfolios we achieve 95%+ field-level extraction accuracy including on 20+ year-old leases that went through several photocopiers. For highly degraded documents the agent surfaces exactly which fields it couldn't confidently read so the analyst targets review effort where it matters.
How does the property valuation AI handle different asset classes?+
We train separate models for each asset class: multifamily, office, retail, industrial, self-storage, and mixed-use. Each model uses the relevant comp sources, cap-rate conventions, and valuation factors for that asset class. During the pilot, we calibrate against your team's recent appraisals and closed deals to ensure the model fits your market footprint and deal conventions. For specialty assets (medical office, data centers, life science) we scope additional training data and validation during discovery rather than claiming out-of-the-box accuracy.
Can you integrate with Yardi, MRI, RealPage, AppFolio, or our property management platform?+
Yes. We integrate with Yardi (Voyager, Genesis), MRI Software, RealPage, AppFolio, and Entrata via their APIs and SDKs. For CoStar, REIS, and Real Capital Analytics we integrate through their data subscription APIs. For lease admin platforms we connect to ProLease, Visual Lease, and Yardi Lease Abstraction. Integration approach depends on your specific platform version and configuration, and we map the pattern during discovery. Write-back to the property management system is gated by your approval workflow and we don't bypass existing controls.
What does a pilot cost and how long does it take?+
A focused pilot on one use case (lease abstraction for one portfolio, tenant communications for one property type, or deal screening for one asset class) runs 5 to 7 weeks from kickoff to production. Pricing typically lands between $75k and $180k depending on integration count, portfolio scale, and how many asset classes are in scope. A full rollout across abstraction, valuation, tenant communications, and reporting runs 3 to 6 months in parallel waves. We quote a fixed SOW before kickoff so asset management, operations, and finance leadership all see the same number.
What data stays on our infrastructure vs. with the AI vendor?+
Lease documents, tenant PII, rent rolls, deal-level financials, and proprietary valuation models stay inside your tenant. We deploy the application layer in your AWS or Azure tenant and run inference against models hosted in your own account with zero retention. Lease content and tenant correspondence never transit a public AI API. For public market data (CoStar, RCA, public records), the agent pulls that through the ordinary data subscription APIs under your existing licenses. We hand you the complete egress map before go-live so your IT team can restrict outbound traffic to exactly the required endpoints.
Who's accountable when the AI abstracts a lease wrong or values a deal wrong?+
The analyst, asset manager, or acquisitions officer remains accountable for the decision that downstream systems and investment committee rely on. Our agent surfaces extractions with confidence scores, citations back to the specific lease page and line, and flags low-confidence fields. For valuation, the agent produces an estimate with a confidence interval and driver decomposition, and the analyst signs off. For deal screening, the acquisitions team still makes the pursue/no-pursue call. We design the workflow so the human who owns the decision today continues to own it. The MSA spells out liability allocation and we carry tech and professional E&O coverage.
How is this different from CoStar, Blackstone-style in-house tech builds, or a big consulting firm, and how do we measure ROI?+
CoStar and similar platforms ship data and generic tools. Large institutional investors build in-house tech for their own stack. Big consulting firms deliver a 12-month digital program and a deck. We tune agents to your specific portfolio, your lease conventions, your investment criteria, and your property management stack, and we deliver running code in weeks. ROI is measured against a baseline captured in discovery: lease abstraction cost per lease, valuation throughput, tenant maintenance closure time, deal screening velocity, reporting cycle time. Most real estate deployments see payback inside 9 months on labor cost, with separate NOI impact from faster action on leases and maintenance.
What's the hand-off between AI and our team, and how do we test accuracy before go-live?+
Every workflow has an explicit hand-off. Lease abstractions go to an analyst queue with confidence-scored fields. Valuations produce estimates for an analyst to review before committee. Tenant communications resolve within a confidence threshold and escalate anything ambiguous to a property manager. Deal screens produce a ranked pipeline for the acquisitions team. Pre-production, we build an eval set using your own leases, prior valuations, prior tenant tickets, and historical deal screens, and we agree accuracy targets in writing (typically 95%+ on lease field extraction, appraised-value parity within 5% on standard asset classes). The system does not move to production until it hits those thresholds.

Let's build your AI system.

Production-grade AI for Enterprise AI for Real Estate. We deploy in weeks, not quarters.

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