Industries Real Estate & PropTech
AI Engineering and software development for real estate companies.
Property data that holds up in diligence.
Property data is fragmented by design: a valuation leans on a handful of transactions, a lease sits in a scanned PDF, and the same building carries three different addresses across your systems. We build the valuation models, diligence automation, and asset infrastructure that make a portfolio legible enough to act on.
Five DegreesCore Banking Loan Management
We helped build the loan management platform behind a Dutch core banking provider whose software ran at 40+ banks across Europe and North America. Five Degrees is now Akkuro by Topicus.
- $45B
- Annual loan volume
- $13B
- Deposits managed
- 133B+
- Assets under management
Why real estate companiestrust us with delivery.
A break clause found after the review date, or a valuation built on comps nobody would defend, can cost a renewal or a quarter of NOI. This is why we pay special attention to the most sensitive parts of the system.
An address is not an identifier
The same building sits in the land registry, a listing feed, a tax record, and your own portfolio system under four different names. Entity resolution has to come first, because every valuation stands on it.
Every valuation rests on a handful of comps
Transactions are sparse, lagging, and negotiated in private, and whole segments trade too rarely to model at all. A point estimate with no confidence attached invites exactly the decision it cannot support.
The lease is the asset
If a portfolio-level question costs your team a month of reading, the leases are why. Rent reviews, break clauses, and old amendments live in scanned PDFs and have to become facts you can query.
Transactions are slow for structural reasons
Title, planning, searches, and a chain of parties who each need to sign will not be hurried by software. The document and coordination layers can be compressed, and that is where the build has to aim.
What real estate demandsfrom engineering and AI.
Property decisions are made on documents, comparables and judgement, and most of that sits outside any system. These four are where engineering makes a valuation, a diligence pack or a search result something you can defend.
01Valuation you can defend in a meeting
An unexplained figure gets overridden once and then ignored, however accurate it was. A defensible valuation exposes its comparable selection, makes its adjustments explicit, and reports its uncertainty, so a surveyor can follow the reasoning all the way to the number.
02Diligence that reads the documents
Deal timelines are made of document review, and it is the one part of the process a buyer controls entirely. Meeting it means turning leases, title documents, searches, and management packs into structured facts, each with a link back to the page it came from.
03Portfolio operations and energy
Capex, energy, and reporting all draw on the same underlying record of how each asset actually performs. Consumption, occupancy, and maintenance history have to sit against the asset register, so the annual reporting cycle falls out of the data instead of becoming its own project.
04Search that matches how people choose
Nobody chooses a home by filter combination; they choose by commute, light, noise, schools, and the feel of a street. Turning that into retrieval means enriching listings with location intelligence and reading the images, not adding another dropdown to the sidebar.
Real-life stories of triumph.
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Real estate data deserves the same care as banking data, as executives make big financial decisions based on both. After years of building for banks, we bring the same approach to the real estate niche.
Nortik’s Impact
Core banking loan management for Five Degrees, the platform behind lending at 40+ banks, and the valuation, diligence, and asset data engineering this page describes.
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Document intelligence, research, and contract automation.
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Route optimization, forecasting, and supply chain visibility.
Frequently asked questions
Everything property teams usually want to know before modelling an asset base. Not here? Ask us directly.
It depends entirely on transaction density. In liquid residential markets with good comparable data, close enough to be useful for screening and monitoring; in thin or specialised segments, wide enough that the interval is the answer and a point estimate would mislead.
We report error by segment rather than a single headline accuracy figure, because one number across a mixed portfolio hides exactly the cases where it fails.
Registries, listing feeds, geospatial and mobility datasets, planning records, and your own transaction history, which is usually the most valuable and least exploited source in the building.
Licensing terms differ sharply by source and country, including whether derived models may be commercialised. We check that before designing a product on top of a feed you can't actually use that way.
Yes, along with the accounting system and the asset register. Realistically, that also includes the spreadsheets that hold the parts those systems never captured.
The goal is one resolved view of each asset that reconciles to those systems, not a parallel database that disagrees with them by the second quarter.
Where the underlying consumption data exists or can be metered, yes. The same pipeline that produces the report supports the retrofit case, which is the part with money attached.
Where data is missing, we're explicit about what's estimated and by what method, since a reported figure built on undisclosed assumptions is a liability in this area specifically.
Vision models handle room classification, condition assessment, feature extraction, and floorplan parsing well enough to enrich a catalogue at scale, which materially improves search and valuation inputs alike.
Anything generated for a listing needs an accuracy boundary and human review, because misdescription is a regulated risk in most markets, not a copy quality issue.
You do. Code, trained models, pipelines, and documentation are yours, along with the infrastructure access to run them without us.
We hand over a codebase your own team can pick up. Nothing we build is designed to keep you dependent on us.
Let's shape your nextAI initiative, together.
Nortik helps you scale your business with AI Engineering.