Q&A with Richard Stevenson, Chief Executive Officer at Red Box

Richard Stevenson, Chief Executive Officer at Red Box, is a senior leader who has built a strong track record of execution, having worked in the Software and Financial Services sectors for over twenty years. An effective communicator who is customer-focused with proven leadership capabilities. Richard has a track record of achieving significant revenue growth, both organically and via acquisition, with experience in organizational strategy and the development of fundraising plans. He has worked with a variety of businesses, ranging from start-ups to an FTSE 100 company, in a number of markets including South Africa, USA, Hong Kong, and Germany.

As data center footprints grow, it is more important than ever that enterprises are fully utilizing the data they collect.



MEDIA 7: Could you please tell us a little bit about yourself and what made you choose this career path?
RICHARD STEVENSON:
I’ve worked in the Software and Financial Services sectors for over twenty years now, focusing on transformation, innovation, and an open approach to platforms and enterprise architecture. I’ve seen firsthand the challenges faced by organizations locked into legacy or proprietary technologies and dealing with data silos, and the negative impact this has on the customer journey, employee experience and in preventing organizations from innovating in an agile way. This agility is increasingly important for organizations to differentiate in rapidly changing and highly competitive marketplaces.

Throughout my career, I have been drawn to leading start-up organizations where a team can be built around a clear challenge and purpose and deliver true innovation for customers and colleagues, which in turn builds shareholder value. Whilst Red Box is not a start-up, I joined as CEO in 2016 at a time when technological advances in Automatic Speech Recognition (ASR) were starting to make it easier to extract insights from the conversations taking place across an organization, at scale, by turning audio files into structured data sets that can be reasoned over by AI and ML engines.

Whilst our core capabilities and expertise remain the same, the new opportunities for voice have expanded significantly. It has become clear that established call recording practices that had served organizations well enough over the years for compliance and quality purposes are now holding them back from fully maximizing ROI from speech analytics investments and Red Box is ideally placed to address this issue and the growing demand for voice data for AI.

My background is in enabling organizations through technology and our mission at Red Box continues that theme by empowering organizations to unlock the value of voice. Our open API philosophy ensures timely access to and control of high-quality voice recordings from across the enterprise which is now critical for any organization looking to leverage voice data as a strategic asset.  We provide customers with full control of and access to their voice data sets and the freedom to tap into that data within their applications of choice.

M7: What is the role of AI in telecommunication? How does Red Box work on voice data analytics and artificial intelligence to unlock the value in the customers’ voice data?
RS:
With each passing year, AI is becoming more mature, and in turn, more viable. When you combine the unique richness of the content of conversations your customers and colleagues are having with AI’s capability to analyze every conversation and combine these insights with other operational data, you can see why there is increasing adoption of speech analytics by organizations seeking to understand the true Voice of the Customer (VoC) and Voice of the Employee (VoE) for experience personalization and optimization. 

With voice data sets increasingly seen as a strategic asset awash with rich insights, timely access to high-quality audio and transcripts for AI engines to reason over is critical. We provide enterprises with open access to, and control of, high-quality unstructured and structured audio data and the freedom to leverage that data in any application they choose. Conversa, our new and first truly open, microservices-based enterprise voice platform, provides real-time, high-quality audio capture. Working with our partners, such as Deepgram, who provide state-of-the-art, deep learning and customizable speech recognition capabilities, we transform this real-time audio stream into highly accurate transcripts for enterprises to leverage in AI, analytics, and compliance solutions. Both the Deepgram and Red Box Conversa platforms have been engineered for flexibility and scalability and offer low compute footprints, market-leading total cost of ownership, and flexible deployment options.


The advancement of technology means opportunities to break into the world of unstructured data are rife, and organizations will be - and should be - looking for faster ways to unlock data and gain insights quickly.



M7: What are some of the barriers to AI adoption?
RS:
Traditionally, there have been significant barriers to AI adoption. Even if people recognize its importance, its complex nature when it comes to analyzing data requires an end-to-end understanding of the process in order to consolidate the customer journey into a single record. Unfortunately, a lot of businesses have installed expensive technology that hasn't been delivered and poor previous experience is certainly a factor in adopting the right AI later down the line.

To avoid disappointment, organizations must focus on specific outcomes and work with vendors that meet specific needs without assuming one provider can do everything. Critically they must also ensure they have complete control of and access to any data they wish to tap into from across the enterprise and in the highest quality possible, as data silos and data quality issues can significantly impact outcomes. Control and access to data also have significant implications for data governance across data residency, data sovereignty, and data localization - concepts particularly relevant when cloud solutions are being considered.

M7: What are your best practices for improving operational performances using voice data?
RS:
As data center footprints grow, it is more important than ever that enterprises are fully utilizing the data they collect. Voice is inherently rich given its ability to convey sentiment, context, intent, emotions, and actions. Enterprises that collect voice data but do not tap into these insights are missing out on information that can provide real organizational intelligence and drive valuable business outcomes.

Secure access to and sovereignty of data is critical in the ‘Data Economy’, as is investing in vendors with an open API approach that gives enterprises flexibility when accessing their data and the capability to leverage voice data into the tools and applications of their choice without tying them to one provider. Indeed, our own research suggests that only 8% of the voice data organizations capture is easily accessible for use in these tools, which is a missed opportunity for those looking to derive insights to help them differentiate in an increasingly competitive marketplace.


Using insights to personalize products and services on a wide scale is changing the fundamentals of competition in many sectors, including banking, education, healthcare and retail.



M7: What do you believe are the top three product challenges in the post COVID-19 era?
RS:
COVID-19 has stirred uncertainty and change for businesses globally. As a result of the pandemic, technology and IT leadership roles have been in the spotlight more so than ever before as companies scrambling to transform operations and customer engagement looks to CIOs for new ways of navigating a rapidly-changing way of working.

With data analytics identified as the number one tech initiative driving 2021 investments, CIOs are facing the challenge of unlocking data insights and incorporating AI/analytics working with a largely remote workforce and while still maintaining a human connection. In this environment, a few emerging product marketing trends can be identified to help stay ahead of the game, not just in 2021 but beyond.

With the scale of insights that can now be generated using voice - from customer journey to markets, competitors and products, as well as the use of voice biometric technology - the growing interest businesses are taking is no surprise considering the advantage the insights and operational efficiencies can provide them with against their competitors. Voice analytics, for example, has the ability to make agents responsible for more complex conversations, whilst efficiently automating more mundane processes for a better customer and agent experience.

As well as the time-saving advantage, analytics of unstructured data has the potential to reveal finer levels of distinctions, and micro-segment populations based on the characteristics of individuals. Deep learning models have significant benefits when it comes to market intelligence and enable businesses to quickly scan unstructured data sets and find patterns. Using insights to personalize products and services on a wide scale is changing the fundamentals of competition in many sectors, including banking, education, healthcare, and retail.

M7: How has the pandemic changed the perception of voice data?
RS:
Voice is fundamental in the communication of all kinds and, naturally, humans are tuned well to understanding it and deriving meaning from it. Customer experience, long a core enterprise priority, became an even greater imperative during the pandemic as companies scrambled to find alternative ways to engage clients, conduct business, and respond to changing requirements as COVID-19 forced business lockdowns and created significant socioeconomic stress.

In all of this, I believe voice is still the best alternative to connecting where face-to-face communication is not an option. IDG found that 81% of CIOs have already confirmed they are implementing new technology to enable better customer experiences and interactions, with 65% of companies now leaning on technology to provide an alternative to face-to-face communications. Even if companies do not rely solely on a call centre, they have some way of communicating with customers or clients and I believe voice is still the richest and most personal form of communication. As well as the external conversations held, recording and transcribing HR meetings can be helpful to understand the culture internally providing privacy concerns are addressed by clear policies and procedures around this.

2021 is already proving to be the year that data separates organizations from their competitors. The ability to unlock, analyze, and act on data will become foundational to growth. As the world leans towards hybrid working models and more communication via technology platforms rather than in person, I believe we will see a much greater reliance on voice continue, thanks to a greater demand for empathetic human connections.

M7: Why do you think data will be the biggest differentiator when it comes to competitors?
RS:
Currently, it’s estimated that around 90% of all data generated in the world is unstructured -  video and audio is an example of this. The small amount of data used by organizations is just the tip of the iceberg. Of the large mass of unstructured data out there, voice is far and away from the biggest opportunity in that it is sizable - but also largely untapped. In the past, the technology to tap into the data in a scalable and meaningful way just didn’t exist and that meant a large team would be required to unlock and analyze conversations to extract insights.

The good news for organizations is the potential to access this kind of data has changed drastically in the last decade. The advancement of technology means opportunities to break into the world of unstructured data are rife, and organizations will be - and should be - looking for faster ways to unlock data and gain insights quickly. According to a 2019 Deloitte Survey, 55% of the business leaders said they were using or planning to use voice. With the large scale of insights that can now be generated using voice - from customer journey to markets, competitors and products, as well as the use of voice biometric technology - the growing interest businesses are taking is no surprise considering the advantage the insights and operational efficiencies can provide them with against their competitors. Voice analytics, for example, has the ability to make agents responsible for more complex conversations, whilst efficiently automating more mundane processes for a better customer and agent experience.

As well as the time-saving advantage, analytics of unstructured data has the potential to reveal finer levels of distinctions, and micro-segment populations based on the characteristics of individuals. Deep learning models, which have hundreds of layers, have significant benefits when it comes to market intelligence and enable businesses to quickly scan unstructured data sets and find patterns. Using insights to personalize products and services on a wide scale is changing the fundamentals of competition in many sectors, including banking, education, healthcare and retail.

ABOUT RED BOX

Red Box is a leading dedicated voice specialist with over 30 years experience in empowering organizations to capture, secure, and unlock the value of enterprise-wide voice. Conversa by Red Box is the next generation and first truly open microservices- based, enterprise voice platform. It provides customers with open access to and control over captured voice and media, resilient capture of high-quality real-time data from across the enterprise, the freedom to use that data in any application, and a market-leading TCO.

Red Box is trusted by leading organizations across financial services, contact center, government, and public safety sectors and we capture and secure millions of calls daily for thousands of customers around the world.

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And this can only happen with simplicity at the core,” said Raj Verma, CEO, SingleStore. “This isn’t just a product update, it’s a quantum leap… SingleStore is offering truly transformative capabilities in a single platform for customers to build all kinds of real-time applications, AI or otherwise.” “At Adobe, we aim to change the world through digital experiences,” said Matt Newman, Principal Data Architect, Adobe. “SingleStore’s latest release is exciting as it pushes what is possible when it comes to database technology, real-time analytics and building modern applications that support AI workloads. We’re looking forward to these new features as more and more of our customers are seeking ways to take full advantage of generative Al capabilities.” Key new features launched include: Indexed vector search. SingleStore has announced support for vector search using Approximate Nearest Neighbor (ANN) vector indexing algorithms, leading to 800-1,000x faster vector search performance than precise methods (KNN). With both full-text and indexed vector search capabilities, SingleStore offers developers true hybrid search that takes advantage of the full power of SQL for queries, joins, filters and aggregations. These capabilities firmly place SingleStore above vector-only databases that require niche query languages and are not designed to meet enterprise security and resiliency needs. Free shared tier. SingleStore has announced a new cloud-based Free Shared Tier that’s designed for startups and developers to quickly bring their ideas to life — without the need to commit to a paid plan. On-demand compute service for GPUs and CPUs. SingleStore announces a compute service that works alongside SingleStore’s native Notebooks to let developers spin up GPUs and CPUs to run database-adjacent workloads including data preparation, ETL, third-party native application frameworks, etc. This capability brings compute to algorithms, rather than the other way around, enabling developers to build highly performant AI applications safely and securely using SingleStore — without unnecessary data movement. New CDC capabilities for data ingest and egress. To ease the burden and costs of moving data in and out of SingleStore, SingleStore is adding native capabilities for real-time Change Data Capture (CDC) in for MongoDB®, MySQL and ingestion from Apache Iceberg without requiring other third party CDC tools. SingleStore will also support CDC out capabilities that ease migrations and enable the use of SingleStore as a source for other applications and databases like data warehouses and lakehouses. SingleStore Kai™. Now generally available, and ready for both analytical and transactional processing for apps originally built on MongoDB. Announced in public preview in early 2023, SingleStore Kai is an API to deliver over 100x faster analytics on MongoDB® with no query changes or data transformations required. Today, SingleStore Kai supports BSON data format natively, has improved transactional performance, increased performance for arrays and offers industry-leading compatibility with MongoDB query language. Projections: To further advance as the world’s fastest HTAP database, SingleStore has added Projections. Projections allow developers to greatly speed up range filters and group by operations by introducing secondary sort and shard keys. Query performance improvements range from 2-3x or more, depending on the size of the table. With this latest release, SingleStore becomes the industry’s first and only real-time data platform designed for all applications, analytics and AI. SingleStore supports high-throughput ingest performance, ACID transactions and low-latency analytics; and structured, semi-structured (JSON, BSON, text) and unstructured data (vector embeddings of audio, video, images, PDFs, etc.). Finally, SingleStore’s data platform is designed not just with developers in mind, but also ML engineers, data engineers and data scientists. “Our new features and capabilities advance SingleStore’s mission of offering a real-time data platform for the next wave of gen AI and data applications,” said Nadeem Asghar, SVP, Product Management + Strategy at SingleStore. “New features, including vector search, Projections, Apache Iceberg, Scheduled Notebooks, autoscaling, GPU compute services, SingleStore Kai™, and the Free Shared Tier allow startups — as well as global enterprises — to quickly build and scale enterprise-grade real-time AI applications. We make data integration with third-party databases easy with both CDC in and CDC out support.” "Although generative AI, LLM, and vector search capabilities are early stage, they promise to deliver a richer data experience with translytical architecture," states the 2023 report, “Translytical Architecture 2.0 Evolves To Support Distributed, Multimodel, And AI Capabilities,” authored by Noel Yuhanna, Vice President and Principal Analyst at Forrester Research. "Generative AI and LLM can help democratize data through natural language query (NLQ), offering a ChatGPT-like interface. Also, vector storage and index can be leveraged to perform similarity searches to support data intelligence." SingleStore has been on a fast track leading innovation around generative AI. The company’s product evolution has been accompanied by high-momentum growth in customers and surpassing $100M in ARR late last year. SingleStore also recently ranked #2 in the emerging category of vector databases, and was recognized by TrustRadius as a top vector database in 2023. Finally, SingleStore was a winner of InfoWorld’s Technology of the year in the database category. To learn more about SingleStore visit here. About SingleStore SingleStore empowers the world’s leading organizations to build and scale modern applications using the only database that allows you to transact, analyze and contextualize data in real time. With streaming data ingestion, support for both transactions and analytics, horizontal scalability and hybrid vector search capabilities, SingleStore helps deliver 10-100x better performance at 1/3 the costs compared to legacy architectures. Hundreds of customers worldwide — including Fortune 500 companies and global data leaders — use SingleStore to power real-time applications and analytics. Learn more at singlestore.com. Follow us @SingleStoreDB on Twitter or visit www.singlestore.com.

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