Founded 2009 | HQ Chicago, IL | 200 employees (approx.) | $100M revenue (est.)
Reveal-Brainspace certainly has an opportunity to separate itself from the crowd and stake out a leadership position of sorts in the legal sector as discovery requests become more complex and voluminous. The company has gone all-in with AI and is forging a strong, individual, and well-funded path to advance the sector.
Reveal was founded in 2009 and is headquartered in Chicago, IL. Led by founder Wendell Jisa (CEO), the firm employs nearly 200 people and has annual revenue estimated at around $100 million. The company is owned by Los Angeles-based private equity firm K1, which invested more than $200 million to merge Reveal with Brainspace in a January 2021 deal with Gallant Capital Partners. Reveal had previously acquired Mindseye in 2019 and NexLP in 2020.
On the surface, Reveal-Brainspace is simply another eDiscovery player in an already crowded market space. But a deeper dive reveals (pun intended) some interesting AI advances that separate the company from many of its traditional competitors. First to note is that Reveal is a broad platform underpinned by proprietary AI models and methods. On top of this platform are several use cases utilizing that core functionality, such as document review, eDiscovery, early case assessment, investigations, and cyber incident response, among others.
The platform itself utilizes many natural language processing (NLP) and machine learning (ML) technologies and thus can analyze, sort, and provide insights into various data sources, bringing some structure to what are typically highly unstructured situations (see Figure 1). In practical terms, Reveal does more than search data and put holds on relevant files. It provides a means to manage, govern, and understand the corpus of data. This is another differentiator. By taking this approach, Reveal can undertake sophisticated analysis, identifying complex connections between people and data and even going as far as to provide emotional intelligence analysis by detecting writing styles based on the firm’s extensive linguistics research work. It recognizes positive or negative sentiments within and between messages and files, potentially helping to detect if somebody is under pressure.
Another thing that sets Reveal apart is its “connect and build” approach to client projects. Once a client has finished a specific project, the knowledge captured in the project from the reviewed documents, and now encoded, can be reused to create new models to fast-track future reviews. Though Reveal provides over 30 generic, out-of-the-box review models, it encourages its clients to essentially build out their own custom models and connect them together to build out complete solutions. It’s also worth noting that the platform detects and can translate 160 languages by leveraging AWS Translate services. In addition to its audio and video transcription services, another differentiator is Reveal’s automated image detection and labeling functionality, which identifies thousands of objects including personally identifiable information (PII) such as driver’s licenses or passports. It also detects scenes within an image, such as a sunset or beach, making it easy to search, filter, and curate large image libraries. And probably its most significant differentiator is high-precision classification (HPC). This is the platform’s ability to look at and analyze snippets or paragraphs within documents (for example, the sentiment or syntactic structure) rather than having to parse and process an entire document. Such an approach allows for much more efficient and speedy review processes, eliminating the need to process mountains of irrelevant information.
Though a lot of complex technology is at work here, thankfully Reveal has focused efforts on simplifying the user experience. Though this is an AI-based system, it has been designed to ensure Humans in the Loop (HITL) throughout the process. The AI is used to suggest outcomes and connections but always requires a qualified human to verify its analysis. In turn, continually feeding the system through an active learning process improves its accuracy over time. The system also provides a high degree of transparency, ensuring that any decisions it makes are explainable and defensible. Reveal can scale quickly and efficiently to handle huge volumes but remains easy to use and manage.
From an IT architecture perspective, Reveal supports on-premises, hybrid, and cloud environments. It leverages AWS services such as S3 to provide scalability, and it has a storage layer that runs concurrently across traditional Windows file shares and the cloud.
Though the legal sector has traditionally been wary of change and innovation, it has recently shifted toward embracing new technologies. Reveal-Brainspace certainly has an opportunity to separate itself from the crowd and stake out a leadership position of sorts as discovery requests become more complex and voluminous. The company has undoubtedly gone all-in with AI and is forging a strong, individual, and well-funded path to advance the sector.
Advice to Buyers
Reveal-Brainspace has advanced and easy-to-use AI legal review technology and should be on your shortlist when considering providers. However, its true value comes into focus when you leverage its functionality and insights to reduce and mitigate future discovery requests. In our estimation, despite its advanced technology underpinnings, it is simple to use and can scale and adapt to meet almost any legal review situation.
- Proprietary advanced ML & AI models
- Easy-to-use platform
- To become the leading document review and discovery platform
- To expand beyond traditional legal document review
- Global expansion via multilingual review capabilities
- Growth within the broader compliance and governance market
- Major investment from private equity firm K1
- Multiple patents for its technology
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