Rent setting affects cash flow, property values, financing and return. In Sweden it is governed by law, by collective bargaining on rent and by comparisons with other units – and it has long depended on spreadsheets, manual calculations and knowledge held by individuals. Hyran.ai turns fragmented information into regulatory rent intelligence.
Sweden's rental market is governed by several rent-setting models for residential units, by market-rent rules for commercial premises, and by separate benchmarks for parking and garages. For an owner or acquirer, the same four questions return in every analysis, acquisition and valuation.
Residential rents in Sweden's primary rental market are not set freely. Depending on the unit, the applicable model may be use-value rent – collectively or individually negotiated – presumption rent or block rent. Hyran.ai identifies the model that applies to each unit and compares today's rent with the applicable legal and market benchmark.
A rent that cannot withstand review is a risk to cash flow. Hyran.ai provides comparison material with source, date and method – normative rents, established rent levels and negotiated prices – so that each assumption can be followed, explained and examined.
The difference between today's rent and an assessed achievable rent level can be quantified – from use value and presumption status, including the remaining protection period, to market-rent assessment for commercial premises – with every assumption documented.
Annual collective bargaining on rent sets the rent increase for negotiated tenancies. The rent negotiation map shows the reported outcomes municipality by municipality, as soon as they are reported.
For valuers, the rent assumption is often one of the least transparent parts of a valuation. Hyran.ai makes it as well founded as the rest: unit-level rent levels, legally relevant comparables and every assumption documented with source, date and method.
New rent records are added continuously. The statistics are updated weekly and shown rounded to the nearest hundred. Last updated: 15 October 2026. See coverage per municipality on the data coverage map.
Rental income drives property cash flow, valuation and investment returns. Understanding how that income can develop requires reliable data, knowledge of the applicable rules and a clear path from analysis to action.
Hyran.ai brings these capabilities together. Starting with Sweden, we are building specialist software that connects unit-level rent data, rent-setting law and financial analysis in a single platform.
For property owners and their advisers, rent setting is a recurring, business-critical process. Yet the information needed to make decisions is often scattered across spreadsheets, agreements and individual experts.
Hyran.ai structures that information and makes it usable across rent analysis, negotiations, portfolio planning and investment decisions.
Our ambition is to become an essential part of how property professionals assess, manage and develop rental income.
Rent records become more useful when they are connected to the characteristics of each unit, the applicable rent-setting model and relevant comparisons. Hyran.ai brings these elements together to support decisions that can be explained and reviewed.
Built on years of research and practical experience in Swedish rent setting, Hyran.ai translates legal methodology into structured workflows. Professionals can analyse, compare, calculate and document within a common framework.
Annual collective bargaining on rent, lease renewals, acquisitions and portfolio reviews create repeated demand for reliable rent intelligence. Hyran.ai is designed to support these workflows across property owners, managers, negotiators and valuers.
Residential tenancies, commercial premises and parking each require different evidence and methods. Bringing them together gives property owners a more complete view of rental income across their portfolios.
Sweden is our starting market: a specialist environment in which reliable data and a detailed understanding of rent-setting rules are central to investment decisions.
Our immediate focus is to deepen data coverage, develop the product with customers and grow adoption in Sweden. Any expansion into additional markets would require local data, legal expertise and validation.
Hyran.ai is developed by Nordic Rent Intelligence Group AB, a Swedish technology company based in Stockholm. The group's products also include REGTA for intelligent contract management, Normhyra.ai for normative-rent calculations and Bostadsbolagskollen, which makes Swedish housing companies comparable with their European peers.
The founding team combines specialist expertise in rent-setting law with software engineering, privacy and secure information management. Its board and advisers bring experience from property ownership, capital markets, business development and technology law.
Doctoral research on rent setting, Stockholm University
Normhyra.ai launched
Work on Hyran.ai begins
Normhyra.ai accepted into Anthropic's directory of connectors for Claude – the third Swedish connector, after Spotify and Lovable
First beta customers onboarded
Hyran.ai combines deep specialist knowledge of rent setting with technical expertise in advanced systems development, privacy and information security – for a field where legal precision, commercial understanding and technical robustness must work together.
CEO · Founder
Doctor of Laws (civil law), with a doctoral thesis on how residential rents are set and regulated in Sweden. Experience from legislative work at the Swedish Ministry of Justice, rent-setting strategy as head of legal at a listed property company, and rent setting and legal risk at Fastighetsägarna. Founding Partner of H. Wac Legal & Business Partner; board member of the listed companies Titania and VK Mortgage Fund (publ.); international adviser to the UK company Conquer AI. Responsible for Hyran.ai's domain, methodology and regulatory intelligence.
LinkedIn →
CTO · Co-founder
M.Sc. in computer science from KTH Royal Institute of Technology, focusing on privacy and secure information management. Built an advanced risk-assessment platform at Ebie, a Swedish fintech and proptech start-up. Responsible for Hyran.ai's technical architecture, product development and secure information management.
LinkedIn →In addition to the founders:
David Dahlgren · Chair of the Board
Business leader with around 20 years in the property industry; former CEO of Amasten and co-founder and CEO of Gladsheim Fastigheter. Experience of company building, transactions, financing and capital markets.
Einar Janson · Board member
Entrepreneur, property owner and investor; CEO of the listed property company Titania since 2005.
Claes Friberg · Board member
Economist and finance executive; former interim CFO of Nobina Sverige, with senior finance roles at Scania, Dahl, Jernhusen and Bredbandsbolaget, and earlier an auditor at Öhrlings.
Pernilla Norman · Board member, Advokat
Founder of Advokatfirman LexIT, with more than 25 years in business law, including EU and competition law, IT law and data protection.
Marie Eneqvist · Commercial Advisor
Entrepreneur, investor and commercial adviser in B2B sales, business development, go-to-market and pricing strategy.
Jonas Schneider · Public Housing Sector Advisor
Former CEO of Familjebostäder and Stadsholmen and former deputy CEO of Svenska Bostäder and Stockholms Stadshus AB.
More about the company and its history on the About us page.
Founder & CEO · Nordic Rent Intelligence Group AB
For investment enquiries and a discussion of our business model, commercial progress and growth plans, please contact Haymanot directly.
This page is provided for information only and does not constitute an offer to sell or a solicitation to buy securities.
