Can your AVM value a New Build?

Using Machine Learning Houseprice.AI can

Unlike 95% of traditional AVMs, our estimates and predictive values are not solely based on linear regression and extrapolation of historic sales prices.

Our Machine learning process uses hedonic drivers which means that you can even vary these drivers to predict the effect of these factors on current and future value on residential property; a new build or a complete development with no sales history, or even one that has not even yet been built!

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The methodology that we use is based on hedonic factors. This is a revealed-preference method which determines the relative importance of the variables which affect the value. We have over 50 different drivers of these variables drawn from the most comprehensive and proprietary datasets in the industry. We take into account Idiosyncratic, Geospatial and Macroeconomic variables to create one of the most accurate automated valuation models available on the market.

If you want to be at the cutting edge of residential valuation, getting fast, accurate values, we can save you time and money, with transparency, clarity and consistency.

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Please contact us if you have questions about Houseprice.AI , our AI data analytics app, want access to our API, or would like to schedule a demo.

* info@houseprice.ai


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Houseprice.AI is a RICS Tech Affiliate

Houseprice.AI - our data, your knowledge

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Houseprice.AI

  • Market leading ML technology
  • Incredibly accurate valuations
  • Reactive value reports
  • Proprietary API

Houseprice.AI is a data company specialising in identifying real value. We have the most comprehensive and proprietary data sets in the industry and have developed industry leading Machine Learning algorithms.

Applications across a range of markets

Our clients include: surveyors, banks, developers, buyers, vendors, investors and agents.

A disruptor in the value of Real Estate
  • Saves time and cuts costs
  • Raises standards and simple to use
  • Superior market intelligence
Information packed reactive value report

Including: comparables, historicals, forecasts, sales values, listings, rental values, greenspace, neighbourhood, transport, economics, EPC and much more.

Project Management

From one property to an entire portfolio. Revalue at any time. Change property specs and obtain the value of the property after the improvements. Revalue an individual property or the entire portfolio at any time.

Out of the box valuation widget

A valuable lead generator that can be embedded in your website

Superior market intelligence

The HP.AI Risk/Reward index, is a proprietary index that further enhances residential real estate data knowledge and improve decision making and profitability.

Need More Information?

Please contact us if you have questions about Houseprice.AI , our AI data analytics app, want access to our API, or would like to schedule a demo.

* info@houseprice.ai


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Houseprice.AI is a RICS Tech Affiliate

Eldred Buck interview, RICS Modus magazine

Eldred has been featured in the October issue of the Royal Institute of Chartered Surveyors monthly publication, Modus.

The article came out on the 10th, so it is "fresh off the press". You can read it here, or click the link to download a pdf copy.


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Eldred Buck is CEO and Co-Founder of Houseprice.AI Ltd and a Non Executive Director at Sequant Capital. He has over 25 years experience in capital markets and banking, specialising in quantitative models and derivatives trading across all major asset classes. Previously he founded Eiger Trading Advisors, a leading fintech company.



If you would like to know more information about Houseprice.AI , Horizon, or access to our proprietary API please feel free to contact us at info@houseprice.ai.


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Mad about Metrics

Houseprice.AI Value

We have introduced 5 different metrics to suit all of our property clients. As a company we are mad about metrics and passionate about using AI data analytics.
A core part of this is to interpret and predict the fairest and most accurate value.

We realise that each sector of the property market has different needs. As an example, an agent wants sales regression for an accurate appraisal, a consumer wants our fair value to protect their investment, whilst a vendor the guided listing price to get the the maximum return on the property.

We give you the tools to help you to make the right decisions for your property interests.

Current estimated value This value is what we call the fair price, property can go higher or lower but this is our AI deduced benchmark value based on over 40 drivers.

Range Includes variables relating to changes in factors such as, aspect, environmental factors, fittings and improvements.

Sales Regression Method used by traditional AVMs. Deriving a value by fitting a line between the recent sales of comparable properties factored for PSQM/PSQF .

Weighted Average A weighted average of sale prices over the past 6 months

Guided Listing price Recommended listing price based on analytics of time on the market and supply demand measures for the area.

Confidence level Statistical measure that is based on how many observations there are for the specific area/property type and deviation from the mean.

Adjusted Value
Gain more precision by adjusting property details and watch the value adjust instantly. The more details you are able to provide, the more precise our adjusted value will be.

Vivienne Brooks is the CCO of Houseprice.AI She has a long history as a Technical Software Support Guru, is a graphic artist and also has a strong background in Marketing.
Need More Information?

Please contact us if you have questions about Houseprice.AI , our AI data analytics app, want access to our API, or would like to schedule a demo.

* info@houseprice.ai


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