Extract key information from Real Estate documentation using Artificial Intelligence

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Law firms and corporations today take on a significant volume of data extraction tasks within and behalf of the Real Estate industry. These organisations are now looking to improve efficiencies, margins and accuracy of data handling through automation.
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Data extraction from Real Estate documentation often has to be done manually, which can lead to several disadvantages:

  • Extremely time consuming and with results having to be manually crosschecked due to inconsistencies and/or human error.
  • Lengthy processes mean that some firms need to hire additional temporary staff or pay employees overtime in order to meet tight deadlines, which can be costly.
  • Humans tend to find the task uninteresting, leading to low morale and high staff turnover within teams.
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The RAVN Extract for Real Estate Solution

RAVN Extract, an application built on the RAVN ACE platform, can automatically extract requested data from huge stacks of documents (including scanned PDFs) such as leases, tenancy agreements or Land Registry documents etc. For example, data points including names, addresses, length and expiry of lease. A summary of this key data is then automatically exported into a desired business output.

Commercial Real Estate Data Extraction

Schermafbeelding 2017-03-25 om 08.46.08RAVN Extract for Real Estate can extract data from very different/unstructured data sets and apply absolute structure to that data set, extract key data points and populate those data points into a desired output, for example a CRM system.

In a recent example, the solution automatically reads through thousands of competitors property PDF marketing brochures and extracts key data points including names of tenants, dates when the tenancy agreements end, price per square foot etc. This data is pulled out of the brochures and automatically populated into a CRM system to drive business growth. RAVN Extract for Real Estate can also automatically extract the market code and show the location of the property on a map. This clearly shows which territory the building is in and which sales person is responsible for this territory. The sales person can use the system to contact the tenants ahead of time to move them into their own property.

RAVN Extract for Real Estate allows you to preview your results and perform in document searches. The technology also informs users when it is unable to locate a data point. This is usually due to a badly scanned document or if the information is not actually present in the document. RAVN Extract can also extract data from tables present in brochures as well as extracting images, such as signatures.

Sale of Shopping Centres

Schermafbeelding 2017-03-25 om 08.49.28Typically, shopping centres have two large retail outlets on either end. For example, John Lewis on one end and House of Fraser on the other. The terms of their leases are very different from the smaller businesses in between. For example, Carphone Warehouse or McDonalds, which are usually centred in the middle of the shopping centre.

When shopping centres are being bought or sold there is a huge amount of effort that goes into understanding what the most standard lease is and what are the standard lease terms.

As shown below, RAVN Extract for Real Estate can produce a cluster map representing leases. The larger the ‘lease circle’ the higher the financial value. The cluster map clearly identifies which is the most standard lease in the centre and how far other leases differ from this standard that you can work from moving forward.

RAVN Extract for Real Estate can identify and extract desired key points of interest from leases. These data points can be completely customisable depending on what data points the organisation wants to extract. Once the information has been extracted it can be exported to a range of outputs e.g. Excel spreadsheet, CRM, HighQ iSheets and other third party solutions.

Title Deed Extraction

Lease AbstractionThere are often lengthy manual processes of going through Land Registry documents to extract data. These documents are very structured, allowing RAVN to create a fully automated process with RAVN Extract for Real Estate to read, interpret and extract data.

BLP used this technology to aid them in serving Light Obstruction Notices. These are notices that need to be served to the residents surrounding the territory of proposed new constructions. The taller the building the wider the radius of people that need to be notified. This notices gives them the right to oppose building plans due to quality of light. For example, when The Shard was being built thousands of businesses and private landowners were notified. This would be an extremely lengthy and costly manual task to read through these and extract information.

RAVN Extract for Real Estate automatically reads through these documents and extracts the requested data points. If there’s information missing the system will automatically cross check with companies house and populate the missing fields. This data is then pulled out into a desired output such as an Excel spread sheet or third party solution for the next stage in the process. 

Benefits & Results of RAVN Extract for Real Estate

Results from a recent deployment in a Real Estate related practice area show that RAVN Extract can now finish a typical extraction task in less than two seconds with a very high degree of accuracy. This task had traditionally taken a team of people 100 days to complete, with an error rate of at least 10%.

  • Eradicates human error
  • Staff can now be re-deployed to more productive and rewarding tasks, leading to improved morale within the team.
  • No longer any call for temporary staff as RAVN Extract is far more efficient
  • Reduces the department’s cost, delivering improved margins and/or enabling more competitive pricing.

Berwin Leighton Paisner recently deployed RAVN Extract within their Real Estate Disputes practice. Watch the case study here.

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What is RAVN Extract?

RAVN Extract is built on top of the RAVN Applied Cognitive Engine (ACE). RAVN ACE brings together different technologies from the fields on Information Processing and AI (Artificial Intelligence) in a coherent, enterprise-ready solution stack. Beyond the foundations of a powerful document search engine, the Applied Cognitive Engine focuses on extracting and distilling the information within documents.

Clients chose to work with RAVN as our ‘Applied‘ Cognitive Engine is thoroughly applied to the business. We listen to the firm’s issues and create a robot that specifically handles those issues within that domain. Our technology can be deployed as standalone solutions or some organisations chose to combine our products to complement each other ensuring all needs are met.

There are various payment options – the technology can be delivered as a service, pay per document model or enterprise license.

Ace Cognitive Computing

Watch our Case Study on BLP’s use of RAVN ACE

See how RAVN ACE has benefited Berwin Leighton Paisner in terms of increasing efficiencies, mitigating risk, cutting costs as well as increasing staff morale.


Need more information?

Read our Extract for Real Estate Brochure


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    As a trusted adviser and negotiation partner, we wanted to have first hand experience of a leading AI technology so we can advise on how it will change the workplace over the coming years to ensure we’re offering the most appropriate advice to our clients. 
    Ole Møller, Vice President at Djøf
    This technology will bring us a flexible environment that is dedicated to our firm so we can ensure we can look after our clients as efficiently as possible. We chose to collaborate with RAVN as we recognised them as a leading AI provider and wanted their product to be part of the firm’s portfolio. 
    Santiago Gómez Sancha, ICT Director at Uría Menéndez
    For our lawyers, time is very precious and we needed a fast, reliable and accurate search engine that was easily integrated into our existing systems. The team at RAVN proved they could tick all the boxes we required. 
    Flavio Romerio, Partner at Homburger
    The software will read, interpret and extract key provisions from a client’s property lease agreements. This approach is a great supplement to manually laborious processes, and a stand-alone device in relation to certain standardized agreements and will mitigate risk from human errors and inconsistencies. SVW is happy to continue the collaboration with RAVN to further improve the SVW real estate robot. 
    Peter Van Dam, Knowledge and IT Manager at Simonsen Vogt Wiig
    Garrigues are always looking for innovative ways to ensure we are providing the most efficient service to our clients. We chose to work with RAVN as they are leaders in the industry and able to deliver on both our current and future plans. 
    César Mejias, IT Director at Garrigues
    RAVN's platform has allowed us to implement our vision of providing integrated, secure and effective access to our knowledge resources. 
    Robin Hall, Head of Knowledge Management at Howard Kennedy
    RAVN is one of a number of innovative solutions that the business is implementing as part of IT's 2020 vision aligned to improve efficiencies and productivity benefits across the firm
    Clive Knott, IT Director at Howard Kennedy
    Our primary goal here is to leverage knowledge to accelerate business and deal decision-making and to harness the collaborative power of a multi-geography growth markets organisation. RAVN Connect is an important component in a differentiation we bring to our investors around how we share knowledge and get to more dynamic decisions on deal flow. Additionally, it helps us harness macro-economic, sectoral and functional knowledge flows seamlessly and is ultimately a major competitive advantage for us.
    Ovais Naqvi, Managing Director – Head of Market Engagement at Abraaj
    It's likely to save us tens of millions of pounds in lost revenue.
    Horia Selegean, Head of Revenue & Margin Assurance at BT
    Sky are committed to using the latest innovations to ensure our customers receive the best possible viewing experience. RAVN’s AI component has allowed us to successfully automate the EPG review process which has dramatically reduced the review time as well as ensuring we maintain robust and compliant information">
    Angus Gairdner, Head of Content Planning Operations at Sky
    By adopting this innovative platform we are able to quickly focus on the high value and high risk contracts within large data sets, simply categorise and divide up tasks and ultimately provide a more responsive service to our clients. We are now looking to roll out the RAVN solution to live client matters within the firm
    Lucy Dillon, Chief Knowledge Officer at Reed Smith
    The RAVN solution effortlessly made all of our operational content, valuable precedent and knowledge content discoverable within the firm’s chosen collaboration and Search platform, Microsoft SharePoint. As such, the disruption for users was negligible, yet the benefits from efficient search, preview and expertise location across a geographically distributed organisation have been significant.
    Jeremy Rooth, Director of Business Transformation & Knowledge Management