Mitigate risk and storage costs with semantic Enterprise information governance

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Control the relentless growth of Enterprise data

RAVN Refine allows organisations to automatically categorise data into clear scopes and refinements and to apply appropriate policies for retention, disposal of dark data and duplicates as well as other controls for such considerations as sensitivity control.
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Cost Saving – Reduce the amount of data retained

By identifying exact or near duplicated, expired or trivial data and removing it from the estate, overall data volumes are reduced with associated savings in storage costs, energy costs, licences and data maintenance overheads.

Risk Mitigation

The risk of not retaining data for compliance reasons often results in overly extended policies. Retaining data beyond expiry policy can equally hold risk to an organisation. By applying consistent policies across multiple datasets, RAVN Refine can help minimise the risk of secure or sensitive data leaking.


Aside from the obvious cost savings when applying good housekeeping to datasets, RAVN Refine cleanses the resulting datasets of noise, resulting in improved search results and more performant systems due to smaller data volumes to process.


Take control of exponential data growth within your organisation. Whether simply to minimise the cost of storage or mitigate the risks associated with the correct retention of data, it is fundamental to identify whether content across the Enterprise is inactive, duplicated or unwanted.

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Having identified the different types of content, RAVN Refine employs a range of techniques ranging from conventional rules-based through to powerful semantic analysis to understand the nature of the content and to correctly classify it accordingly. This is essential for implementing correct policies for retention and data cleansing with the benefit and assurance that you are only paying to store or retain information truly necessary to the business.

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RAVN Refine sits on the RAVN Applied Cognitive Engine platform, which provides the capability to tag, comment and otherwise enrich data sets. Retaining enriched information relating to the categorised data saves time and provides an audit trail for subsequent data management exercises, even through the data itself is ‘managed in place’.

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RAVN Refine can potentially reach into any content source in the Enterprise and provide a single interface for the management of data by leveraging the RAVN Pipeline connectivity layer. This tried and tested generic framework unifies access to the entire data corpus and powers enterprise-wide perspectives of your information estate, allowing to the entire data corpus and powers enterprise-wide perspectives of your information estate, allowing you to plan infrastructures in line with demands and policy.

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HIPAA compliance rules

RAVN Refine is capable of identifying documents that fall under the HIPAA (Health Insurance Portability and Accountability Act) compliance rules. It is not only capable of identifying personal information like Credit Card numbers, Social Security Numbers, National Insurrance numbers, Dates of birth etc, but also personal health care information. This makes it possible for organisation to see where documents are located that need to be treated differently in order to comply with the rules of HIPAA.

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Dark Data

Every Enterprise has to deal with the vast and exponentially expanding volumes of unstructured information stored in different locations, including file shares, local hard drives and of course myriad line of business solutions. This unstructured, uncategorised and potentially unmanaged and untapped data could contain confidential or sensitive information and as such may pose significant risk to the organisation. This data is known as Dark Data and left unstructured and unmanaged, could be more of a liability to the business than a potential asset.

The challenge, of course, is in identifying Dark Data, classifying it and ensuring that it has correct retention policies applied and where required to be retained, is stored in the correct location and cost effective storage medium. When this Dark Data remains in the organisation untouched, several potential risks are exposed:

Legal and Regulatory risk: Some compliance rules require sensitive data, where it has to be retained, to have access controlled or only made accessible in redacted form, such as content containing personal records, credit card details, social security numbers and so on.

In the US, for example, organisations are compelled to comply with rules set out in the HIPAA legislation, pertaining to the retention and management of personally identifiable information. Failure to comply with these rules can result in significant legal and financial penalties.

Intelligence Risk: Dark Data may contain useful information and hard won experience, and if not properly managed, may not be exposed, reused or leveraged by other corporate users. Such information may be relevant for better understanding current clients and relationships, promoting efficient best operational practices and ensuring competitive advantage.

Reputation Risk: Not knowing what information is contained within your organisation could reflect badly on the firm’s reputation.

RAVN Refine is the ideal platform to identify, analyse, categorise and classify sensitive and useful information contained within an organisation’s Dark Data and enable management in place of the content. As an example, as well as facilitating good housekeeping practice across the enterprise data corpus, RAVN Refine could be used to analyse client related information that is not currently filed in a document management system (DMS), practice management system (PMS) or other structured system or storage regime and intelligently identify it for correct filing, potentially mitigating risk to the organisation.

    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
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Latest Case Study

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