PropTech

Smarter buildings. Happier tenants. Lower operating costs.

We build tenant portals, smart building platforms, automated leasing workflows, and IoT-integrated maintenance systems in 12 weeks. Software that cuts vacancy loss, catches HVAC failures before they happen, and keeps tenants renewing.

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13+

Proptech products

60%

Admin time saved

3x

Tenant satisfaction

Overview

Your buildings are leaking money through manual operations

Proptech software development at RaftLabs focuses on the three operational areas that most directly impact NOI - tenant experience, maintenance efficiency, and energy optimization. We bring patterns from 100+ products across adjacent industries to build tenant portals, predictive maintenance platforms, automated leasing systems, and smart building energy tools - each engineered to drive measurable cost reduction and tenant retention.

Property management is drowning in manual work. Lease administrators process renewals by hand, maintenance teams react to emergencies instead of preventing them, and tenant communication runs through a patchwork of emails, calls, and paper notices. The result - high operating costs, preventable tenant churn, and buildings that underperform their potential NOI.

Our tenant portals handle 80% of routine requests without property manager involvement. Predictive maintenance systems catch HVAC failures 2 weeks before they happen. Leasing automation cuts vacancy loss by filling units 40% faster.

Every product integrates with existing property management systems - Yardi, RealPage, AppFolio, MRI, and custom platforms. We work with your existing data and workflows. No platform migration required.

Experience Signal

13+ proptech products shipped with tenant portals, predictive maintenance platforms, automated leasing systems, and smart building energy optimization for multifamily operators, commercial REITs, and student housing providers. 12 weeks is our default, not our stretch goal.

13+

Proptech products

60%

Admin time saved

Industry Pain Points

What's broken in proptech

01

Property managers spend 60% of their time on repetitive tasks - tenant requests, lease paperwork, vendor coordination, and rent collection follow-ups

02

Maintenance is reactive - equipment breaks, tenants complain, and emergency repairs cost 3-5x more than planned maintenance

03

Lease renewal processes start too late and lack personalization, driving 25-35% annual turnover in multifamily and 15-20% in commercial

04

Building systems - HVAC, lighting, access control, elevators - operate in silos with no unified performance view or optimization

05

Tenant screening takes 3-5 days with manual verification of income, credit, and rental history across multiple sources

06

ESG and energy reporting gets compiled by hand from utility bills, BMS exports, and vendor invoices at the end of every quarter

Solutions

Problems we solve in proptech

Each solution is built from patterns we've validated across 100+ products. No experiments on your budget.

01

Tenant self-service portal and AI assistant

A single platform for rent payments, maintenance requests, lease documents, amenity booking, and community updates. AI assistant handles routine inquiries - "when is my lease up?", "can I have a package held?" - without property manager involvement.

02

Predictive maintenance with IoT integration

Connects to building sensors - HVAC, plumbing, electrical, elevators - and identifies equipment degradation patterns before failures occur. Generates work orders with diagnosed issues and recommended parts 2-3 weeks ahead of breakdown.

03

Automated leasing and tenant screening

AI-powered application processing that verifies income, credit, and rental history in minutes instead of days. Automated lease generation, e-signing, and move-in coordination. Renewal campaigns triggered by tenant satisfaction and market signals.

04

Smart building energy optimization

Analyzes occupancy patterns, weather forecasts, and utility rates to optimize HVAC, lighting, and common area systems. Cuts energy spend 15-25% while protecting tenant comfort. Generates ESG reporting data automatically.

05

Portfolio analytics and NOI optimization

Unified dashboard across properties showing occupancy, rent collection, maintenance costs, tenant satisfaction, and NOI performance. AI surfaces underperforming assets and recommends specific operational improvements.

06

Vendor and work order management

Routes work orders to qualified vendors, tracks SLA performance, and auto-approves recurring invoices within budget. Cuts coordination overhead and surfaces vendor performance patterns property managers can't see from email threads.

Use Cases

Real-world use cases

Tenant portal for a multifamily operator

Problem

A multifamily operator managing 4,200 units across 18 properties handled 8,500 tenant requests per month through phone calls and emails. Property managers spent 4+ hours daily on routine communication.

What we built

We built a tenant portal with AI-powered request routing, automated status updates, rent payment processing, and a chatbot that handles common questions. Maintenance requests include photo upload and AI-assisted categorization for faster dispatch.

Result

78% of tenant requests handled without property manager involvement. Average request resolution time dropped from 3.2 days to 14 hours. Tenant satisfaction scores improved 0.8 points. Property managers reclaimed 3.5 hours per day for leasing and retention work.

Predictive maintenance for a commercial REIT

Problem

A commercial REIT with 2.1M sq ft of Class A office space spent $3.8M annually on HVAC maintenance, with 40% going to emergency repairs. Tenant complaints about temperature averaged 120 per month.

What we built

We deployed IoT sensors across HVAC systems and built a predictive maintenance platform that monitors equipment health, detects degradation patterns, and generates proactive work orders 2-3 weeks before likely failure.

Result

Emergency HVAC repairs dropped 64%. Annual maintenance spend decreased $920K. Temperature complaints fell to 28 per month. Equipment lifespan extended an estimated 18-24 months across the portfolio.

Automated leasing for a student housing provider

Problem

A student housing provider with 6,000 beds processed 14,000 applications annually during a 90-day leasing season. Manual screening took 3-5 days per application, and they lost prospects to competitors who responded faster.

What we built

We built an automated screening system that verifies guarantor income, runs credit and background checks, and produces approval decisions in under 30 minutes. Integrated with automated lease generation, e-signing, and roommate matching.

Result

Application-to-lease conversion improved 31%. Screening time dropped from 3.5 days to 22 minutes. Pre-leasing velocity climbed 44%, reaching 95% occupancy 6 weeks earlier than the prior year. Leasing staff went from 12 to 7 during peak season.

Our Approach

How we approach proptech projects

1
Phase 1· Week 1-2

Property operations audit

We analyze your property management workflows, maintenance costs, tenant satisfaction data, and technology stack. Where you're losing NOI to vacancy, operational inefficiency, and preventable tenant churn all get quantified.

Deliverables

  • Operational cost analysis with per-unit and per-property breakdowns
  • Tenant journey map identifying friction points in leasing, living, and renewal
  • Prioritized opportunity list ranked by NOI impact and implementation speed
2
Phase 2· Week 2-4

Product design and integration planning

We design the product with your property management, maintenance, and leasing teams. Every integration point - PMS, accounting, IoT systems, payment processors - gets mapped before build.

Deliverables

  • Product design validated by property management leads
  • Integration specifications for PMS and building systems
  • Data architecture for tenant, property, and IoT data flows
3
Phase 3· Week 4-10

Build and property pilot

We build in sprints and deploy to a pilot property first. Real tenant interactions and building data validate the product before portfolio-wide rollout.

Deliverables

  • Working product deployed at pilot property
  • Performance metrics from real tenant and building data
  • Iteration backlog based on pilot learnings and team feedback
4
Phase 4· Week 10-12

Portfolio rollout and optimization

We roll out across the portfolio with property-specific configuration. AI models improve continuously as more tenant interactions and building data feed the system.

Deliverables

  • Portfolio-wide deployment with property-level customization
  • NOI impact dashboard tracking occupancy, costs, and tenant retention
  • Quarterly optimization plan tied to portfolio performance targets

Outcomes

Measurable outcomes

70-80% of routine tenant requests handled without property manager involvement
40-65% reduction in emergency maintenance costs through predictive monitoring
15-25% decrease in building energy costs through AI-optimized HVAC and lighting
25-40% faster lease-up through automated screening, application processing, and e-signing
4-6 week jump in renewal decisions through earlier, personalized renewal campaigns

Free Tools

Free tools for proptech

Calculators and assessments built from real project data. No signup required.

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Pattern Transfer

RaftLabs built IoT-connected monitoring systems for logistics warehouse operations before applying the same sensor-to-insight pattern to smart building management. Both problems need real-time data from distributed devices, anomaly detection, and automated work order generation. The building is just a different kind of warehouse.

Services

Services for proptech

Frequently asked questions

Projects range from $45K-$180K. A tenant portal with AI assistant starts around $45K. A full smart building platform with IoT integration and predictive maintenance runs $120K-$180K. Fixed estimate after a strategy session.

Next Step

Every month of reactive maintenance costs you 3-5x what prevention would.

One call with a founder. No sales team, no follow-up sequence. If we can't help, we'll say so.

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