Artificial intelligence is rapidly reshaping the global property and built-environment sector. From automated valuations and predictive analytics to digital twins, conversational AI, and smart-city optimisation, the next generation of PropTech innovators is focusing on real commercial impact, not just novelty. As we step into 2026, AI is moving from pilot projects to essential infrastructure for real estate investors, developers, operators, and consumers.
Here are the top five AI-powered PropTech startups to watch closely in 2026 companies that are redefining how data, automation, and intelligence power the future of real estate.
1) Skyline AI — AI for Intelligent CRE Investments
AI has dramatically changed how commercial real-estate (CRE) investors evaluate assets, and Skyline AI is one of the pioneers leading this shift.
What they do
Skyline AI uses machine learning models trained on decades of CRE transactions, asset-level information, market cycles, demographic variables, and financial indicators. The platform conducts:
- Automated asset valuations
- Investment risk analytics
- Predicted rent trajectories
- Portfolio optimisation
- Deal scoring
The result is a performance-driven system that helps investors analyse opportunities in minutes rather than weeks.
Why follow in 2026
CRE investors operate in a data-dense yet opaque environment. Skyline’s significance lies in its ability to:
- Uncover undervalued assets
- Predict future performance
- Replace manual underwriting with model-driven precision
- Reduce decision bias
- Speed up transaction cycles
As global markets become more volatile, investors are looking for transparent, machine-generated insights to reduce risk. Skyline’s technological depth and growing institutional adoption place it firmly on the 2026 watchlist.
What to watch for
- Enhanced explainability of valuation models
- New products for mid-market investors
- Partnerships with fund managers for integrated AI underwriting
2) Cherre — The AI Data Fabric for Real Estate
Data fragmentation is one of the biggest barriers to digital transformation in real estate. Cherre has emerged as a category leader by solving this foundational problem.
What they do
Cherre provides a unified data infrastructure that connects disparate datasets leases, transactions, building documents, market feeds, demographic information, and financial records into a single structured environment. Layered on this is Cherre’s AI engine, which enables:
- Document intelligence
- Automated extraction and classification
- Natural-language querying
- Portfolio-wide insights
The platform turns raw, inconsistent data into an AI-ready ecosystem.
Why follow in 2026
Most AI innovation in real estate fails not because of weak algorithms, but because of messy data. Cherre’s importance lies in enabling enterprises to actually operationalize AI. By giving teams access to connected, high-quality datasets, Cherre empowers:
- Accurate underwriting
- Asset-management automation
- Streamlined reporting
- Risk identification
- Faster decision cycles
As the industry shifts from isolated tools to fully integrated intelligence platforms, Cherre will be a critical enabler.
What to watch for
- More connectors for ESG, local-government, and utilities data
- Growth in AI-driven reporting capabilities
- Data benchmarking products for large portfolio owners
3) CityBldr — AI for Zoning, Redevelopment, and Site Selection
Urban land use is becoming more complex, and developers are under pressure to identify viable opportunities quicker. CityBldr uses AI to decode the complexities of property, zoning, and financial models at a citywide scale.
What they do
CityBldr’s platform processes zoning rules, parcel-level data, demographics, comparable developments, market signals, and financial assumptions to generate:
- Highest-and-best-use analyses
- Redevelopment opportunity scoring
- Feasibility models
- Automated site intelligence
In simple terms, it tells developers exactly what can be built, where, and whether it makes financial sense.
Why follow in 2026
As housing demand rises and cities encourage densification, the speed at which developers can evaluate potential sites becomes a competitive advantage. CityBldr’s AI solves three major pain points:
- Manual zoning analysis
- Slow feasibility modeling
- Missed redevelopment opportunities
The platform democratizes access to intelligence that was once limited to expensive consultants. Mid-market developers, municipalities, and investors can now run site-selection processes with unprecedented accuracy and speed.
What to watch for
- Expansion into more international markets
- Deeper integration with planning and municipal databases
- Tools that link feasibility analysis directly to project workflow
4) Digs — AI for Construction Handover and Home Lifecycle Management
Residential construction is plagued by inefficiencies, miscommunication, and a lack of digital continuity between builder, subcontractors, and homeowner. Digs aims to solve this with AI-enabled workflow tools and digital twins.
What they do
Digs builds an AI ecosystem that supports homebuilders across preconstruction, construction, and handover. Key features include:
- Smart collaboration during preconstruction
- Automated document and plan extraction
- Digital twin creation for each home
- Warranty support using AI agents
- Homeowner experience management
The platform offers a single source of truth for the entire home lifecycle.
Why follow in 2026
Construction and post-delivery operations are still largely manual. Builders face major challenges:
- Lost documents
- Misaligned expectations
- Warranty claims chaos
- High customer-service workload
Digs’ AI helps builders deliver homes with better transparency and fewer errors, while giving homeowners intuitive digital access to everything about their property.
What to watch for
- Growth in number of homes supported
- Integration with national builders
- Enhancements to digital-twin capabilities for long-term maintenance
5) eVoost AI — Conversational AI for Real-Estate Sales & Customer Journeys
Modern property buyers expect instant responses across WhatsApp, web, CRM, social media, and email. eVoost AI is filling this gap with emotionally responsive AI agents built specifically for the real-estate sales funnel.
What they do
eVoost AI offers conversational agents that can:
- Qualify leads
- Respond to property inquiries
- Schedule viewings
- Guide customers through buying processes
- Understand emotional tone
- Integrate directly with CRM systems
It functions like a digital sales executive that operates 24/7.
Why follow in 2026
The shift to omnichannel property buying has pushed real-estate companies to adopt scalable communication systems. eVoost is gaining traction because it:
- Reduces human workload
- Accelerates conversions
- Ensures instant, consistent responses
- Improves customer satisfaction
- Works seamlessly across devices and channels
AI-driven engagement will become one of the biggest growth drivers for brokerages and developers in 2026.
What to watch for
- New languages for global markets
- Automation of more stages of the sales lifecycle
- Partnerships with large developers and CRM platforms
How These Startups Reflect the Future of PropTech
Across these five companies, several clear themes define where PropTech is headed:
1. AI as a decision-accelerator
Underwriting, feasibility modeling, and asset selection are shifting from intuition to model-driven intelligence.
2. Data unification as a prerequisite for AI
Platforms like Cherre show that AI is only as strong as the data infrastructure behind it.
3. Automation across the entire lifecycle
From land identification to construction handover to customer sales, AI is becoming embedded at every stage.
4. Operational efficiency as the real ROI
The winning solutions are not flashy; they save time, reduce errors, and create measurable business value.
5. Human-AI partnerships
Tools like eVoost AI demonstrate that AI isn’t replacing real-estate professionals, it’s enhancing them.
Final Thoughts
The AI revolution in PropTech is well underway, and these five startups Skyline AI, Cherre, CityBldr, Digs, and eVoost AI represent the next wave of innovation. They are not just automating tasks; they are re-engineering how real-estate organizations operate, make decisions, and interact with customers.
In 2026, the most successful property companies will be the ones that leverage AI not as a tool, but as a strategic advantage. Following and learning from these startups offers a powerful glimpse into the future of a more intelligent, efficient, and data-driven real-estate ecosystem.
