AWS Startups Blog

Modern communication compliance conundrums: How Theta Lake uses cloud-based AI and ML to address compliance risks within audio and video communication

Guest post by Anthony Cresci, VP Business Development and Operations, Theta Lake

ThetaLake Portal w-Co-Founder

For the average person, the idea of compliance and regulation technology doesn’t elicit much enthusiasm. But for Devin Redmond and Rich Sutton, co-founders of the RegTech startup Theta Lake, the concept is downright sexy—especially as startups and enterprises alike have increased spending on compliance following the last financial meltdown.

Redmond and Sutton, serial entrepreneurs who sold their last RegTech startup, Nexgate, to Proofpoint, founded Theta Lake in 2017 with the goal of solving enterprise compliance surveillance for modern-based video communication. Theta Lake’s solution aims to help organizations adopt video technologies—like video marketing, video chat, video conferencing, and more—without losing the supervision controls that companies need to remain compliant with increasingly complex regulations.

Redmond and Sutton decided to focus specifically on video communication solutions because companies are finding countless uses for video in their daily operations, whether it’s using sales and marketing videos to increase revenue or relying on improved video conferencing solutions to drive higher customer and employee retention rates as well as improved productivity. But with the use of video marketing, video calls, and audio calls skyrocketing along with the intersecting increase in MiFID II, GDPR, FINRA, FFIEC, and similar regulatory requirements, companies are finding efficient communication compliance monitoring an extremely daunting challenge.

Compliance solutions have been developed to identify compliance risks for text-based communication; however, the complexity of video creates multiple challenges for legacy solutions. The difficulty of video monitoring lies within identifying not only risks within the separate streams of audio content and shared content, but also whether there was risk from the combination of what was said and shown. This complexity, however, does not alleviate an organizations’ responsibility to supervise and monitor audio and video content—the same that is required with any text-based form of communication. Therefore, the review and supervision process for video monitoring and audio surveillance has remained a very manual and time-intensive process for compliance teams, unable to scale with organization’s use of video marketing, video calls, and audio calls.

Creating a technology to alleviate this bottleneck typically would have required years of developing tools for automated speech recognition, image recognition, content transcription, WORM compliant storage, and others. But because AWS enables us to take advantage of transcription and image recognition solutions, and well as compliant storage like Glacier, we at Theta Lake have been able to focus on the “last mile AI”—extracting meaning from the data to identify potential compliance risks.

Theta Lake provides a purpose-built product suite for automatic policy detection of regulatory risks, compliance workflow, and retention for digital content. Using patent-pending technology to normalize relevance in transcription, extract scene content, perform OCR, and do entity analysis, the product suite uses built-in machine learning classifiers to detect regulatory and corporate compliance risks in digital content. Instead of taking disparate pieces of data like raw transcripts that have basic contextual errors that can add to review time while putting a manual burden of workflow and actual incident logging on staff, Theta Lake automates compliance. Risks in audio, visual, spoken, shown, and shared content is surfaced in an AI-assisted workflow for compliance personnel to move more quickly and effectively through digital content review and supervision.

This provides a faster and more efficient review process for compliant videos while improving consistency in the approval and post review supervision of videos. The added benefit of AI-based policy detection and AI-based automation in workflow helps reviewers focus on accurate identification of risks while reducing the time spent on large volumes non-risky video content. Essentially, compliance teams can do better review on more video without dramatically increasing staffing, training, and oversight costs. This means more compliant video for the business to use to achieve better top and bottom-line results.

Learn more about Theta Lake here.

Michelle Kung

Michelle Kung

Michelle Kung currently works in startup content at AWS and was previously the head of content at Index Ventures. Prior to joining the corporate world, Michelle was a reporter and editor at The Wall Street Journal, the founding Business Editor at the Huffington Post, a correspondent for The Boston Globe, a columnist for Publisher’s Weekly and a writer at Entertainment Weekly.