We are building something new.
Professional property actors deserve a valuation tool that meets the same standard as their business.
Nezto is a platform for automated property analysis. We serve broker chains and property developers who need well-founded, explainable valuation reports — quickly, consistently, and integrated into existing workflows.
Traditional AVM solutions deliver a number without context. That is not enough when you need to justify a price to a seller, credit committee, or board. Nezto combines traditional price modelling with image-based machine learning and SHAP-driven explainability — so every valuation can be backed by clear, auditable reasoning.
Beyond the professional core, we make the same analytical capability available to sellers and buyers who want to understand market value in depth — not to replace the broker, but to make meetings with the broker more informed for both sides.
- 01
Broker chains
Nezto integrates into broker workflows as an intelligence platform for the housing market and image-based valuations — faster, better-supported valuation reports, stronger client trust, and advice grounded in data rather than intuition.
- 02
Property developers
Developers need ongoing market valuations for upcoming and existing projects. Nezto delivers portfolio valuations in an enterprise format with API access for automated flows in larger organisations.
- 03
Sellers & buyers
Individuals selling or buying a home get access to the same analytical capability as professionals — not to replace the broker, but to make conversations with the broker more well-founded for both parties.
Explainability is not an add-on — it is the architecture.
Most automated valuation models give you a number. Nezto gives you an answer. Every valuation produces a SHAP-based explanation that breaks down how each factor — square metres, location, condition, light, renovation, view — contributes to the final value.
Computer vision on listing photos is an area most actors overlook. Nezto extracts qualitative signals from images and turns them into quantifiable value factors that traditional hedonic models could never capture.
The model is grounded in established valuation theory and strengthened with modern machine learning and computer vision.
Co-founder
Karim Sayyad
Background in finance with a master’s degree from Lund University. Karim leads Nezto’s commercial strategy, partnerships, and funding.
Co-founder
Gustaf Tegnér
Technical co-founder with experience in machine learning and computer vision, and PhD studies at KTH. Gustaf leads product development and modelling.
Software engineer
Erik Hedlund
Engineering director
George William Amalan
Engineering leader with over 2 decades of experience across digital platforms, AI-enabled products, and large-scale web applications. George leads engineering strategy, architecture, and scalable platform delivery.
Software engineer
Daniel Danho
Methodology advisor
Mats Wilhelmsson
Professor at KTH and one of the architects behind the Swedish HOX index. Mats reviews and validates Nezto’s model methodology and ensures the model is scientifically robust.
KTH Royal Institute of Technology


