As CEO and founding father of AnswerRocket, Alon leads product innovation and brings actionable analytics to business people, so that they can get their questions answered faster. Prior to founding AnswerRocket, Alon co-founded and was Chief Technology Officer of Radiant Systems for 25 years. He served as Radiant’s Chairman from 2004 to 2011, when the corporate was sold to NCR for $1.3 billion. Alon has a B.S. in Computer Systems Engineering from Rensselaer Polytechnic Institute.
Could you share the genesis story behind AnswerRocket?
We began AnswerRocket with the vision that anyone should give you the option to get easy answers from their data, identical to interacting with a private assistant. The thought stemmed from our frustration sitting in management and board meetings, where questions on business performance metrics couldn’t be answered on the spot. We’d then should go off and spend days or even weeks doing additional evaluation, which felt wasteful because the info was already available and needs to be quickly accessible. We desired to create an experience where anyone within the enterprise could simply ask a matter and get a direct, insightful response the moment these business questions cropped up.
How does AnswerRocket leverage AI to remodel traditional analytics?
AnswerRocket has been leveraging AI to make data analytics accessible and approachable to analysts and business users alike for over 10 years. Most recently, we’re applying generative AI technology to create a conversational AI assistant called Max. Business users can chat with Max to explore and analyze their data – they don’t have to know SQL or how the info is organized to get an excellent, meaningful answer. Max is connected to AnswerRocket’s suite of analytical applications–or Skills, as we call them–which enables it to perform advanced analyses starting from statistical, diagnostic, and even predictive evaluation. For analysts and data scientists, we’re transforming their workflows by giving them the tools to create reusable, AI-powered Skills in our Skill Studio. It’s about capturing their expertise and analytical know-how in specialized AI analytics agents that their users can successfully interact with.
What are a few of the key advantages your clients experience with Max, your AI data analyst?
Max removes the technical and data literacy barriers which have long made data analytics solutions difficult for business users to adopt. By embracing the chat paradigm, we provide users a well-known experience for engaging with Max, allowing them to explore data and ask questions in their very own words.
Speed is one other huge profit. Max automates complex analyses to deliver relevant, interactive answers and insights immediately. Plus, the outputs are tailored to match the prevailing evaluation and reports our clients are used to, eliminating the training curve and enabling users to quickly derive insights without adapting to latest formats. We’re trying very much to satisfy users where they’re and to seek out ways to suit Max into their current workflows seamlessly.
Are you able to elaborate on how integrating OpenAI’s GPT-4 LLM enhances Max’s capabilities, and what unique benefits does it offer to businesses?
Integrating OpenAI’s GPT models into Max really took its capabilities to the following level. LLMs significantly improve Max’s natural language understanding and generation. Coupled with our analytics platform and specialized DS/ML applications developed over the course of a decade, we were in a position to create an AI assistant that might handle more complex queries and deliver more nuanced answers. This was an enormous step forward in enabling an intuitive, enjoyable chat experience for users. GPT’s ability to generate human-like responses helps users feel more comfortable and assured in using the platform–as in the event that they’re chatting with a colleague.
With the rapid evolution of language models like GPT-4o and Claude 3, how does AnswerRocket plan to remain ahead of the competition and proceed innovating within the AI analytics space?
The space is moving incredibly fast and that’s been keeping us extremely busy. We’re getting our hands on every major model that’s being released, experimenting and learning all along the best way. We’ve designed AnswerRocket to be model-agnostic, with the view that customers will wish to give you the option to pick a particular model and even multiple models to support a wide range of use cases. We would like to enable that level of flexibility and guide users in choosing the most effective models for the job at hand.
How does AnswerRocket be certain that its platform is user-friendly for business users who may not have technical expertise?
Max, our AI assistant, plays a giant role here. Not only is Max designed to grasp what the user is asking for and return a solution, it also helps steer users towards useful answers. For instance, we all know ranging from a blank screen could be intimidating to users, so we give them sample prompts to leap off of. Similarly, Max can provide suggested follow-up questions alongside its answers, leading users to the following relevant insight. Max may also probe further if more detail is required to perform a requested evaluation – the aim is to maintain the conversation going and to get the user to the reply they’re in search of. Finally, users can provide feedback on Max’s responses. This is useful to tell administrators on where the experience must be tuned or improved.
Are you able to discuss the customization options available with Max and Skill Studio?
Our vision for Skill Studio is to offer data analysts the tools to create AI-powered assistants for virtually any data evaluation use case under the sun. It’s about helping them stamp their processes and best practices into reusable and composable AI agents that could make quick work of tough data evaluation tasks.
With Skill Studio, users can create custom Skills tailored to their unique analytical processes. This includes defining specific data sources, analytical methods, and visualization preferences, together with constructing and modifying reports and workflows. Max supports complex analyses using multiple data sources, each structured and unstructured, to inform more comprehensive data stories.
Skill Studio offers a full development environment with a low-code interface, making it accessible for each technical and non-technical users. You don’t have to start out from scratch: We offer pre-built components and templates for analyses, charts, and tables. Moreover, we’ve purpose-built AI assistants for specialised tasks. In fact, it’s also possible to create your individual custom blocks and integrate your individual machine-learning models.
Could you share some examples of how AnswerRocket has driven significant business outcomes in your clients, reminiscent of improving decision-making or increasing operational efficiency?
AnswerRocket has driven significant business outcomes across various industries, including fields reminiscent of consumer goods, pharma, insurance, financial services, and skilled services.
Certainly one of our standout success stories is with AB InBev, the world’s leading brewer. Like most firms, they faced challenges with the manual and time-intensive technique of turning raw data into actionable insights. By integrating AnswerRocket’s AI assistant, Max, they transformed this process.
For instance, the time required to show raw data into actionable insights was reduced from 20 days to three days, allowing their brand managers to make timely decisions. Report generation, which used to take days, now happens inside hours, delivering insights quickly across 17 markets. Business users are actually in a position to self-service answers and insights on demand by chatting with Max.
By way of productivity, our AI solutions freed up 160 working days for AB InBev’s insights team, enabling them to deal with strategic tasks. The answer has scaled from the European team to global operations, demonstrating its broad impact.
These improvements in efficiency and decision-making aren’t isolated to AB InBev. A lot of our clients have seen similar outcomes, with faster insights, more strategic use of resources, and higher business results.
Given the importance of information security and compliance, how does AnswerRocket be certain that its platform meets enterprise-grade security standards?
Data security and compliance are absolutely crucial. We’ve implemented several robust measures to make sure the protection of our users’ data.
We use advanced encryption methods to secure data each at rest and in transit. Because of this data is protected in any respect stages of processing. On top of that, we’ve strict access controls. Access to data and evaluation is restricted to authorized users only, ensuring sensitive information is kept secure.
We also adhere to industry standards and regulations like GDPR and CCPA, which is vital for compliance with data protection laws. We never make copies of the info while it’s being analyzed. This maintains data integrity and confidentiality.
We conduct regular security audits and vulnerability assessments. These help us proactively discover and mitigate potential risks, ensuring our security measures are at all times up thus far.
These steps underscore our commitment to safeguarding our users’ data and maintaining the very best standards of security and compliance. It’s about ensuring our users can trust us with their data every step of the best way.
What are your thoughts on the longer term of AI in enterprise analytics?
AI will revolutionize enterprise analytics by significantly enhancing productivity and efficiency. Today, much of the work involves manual data collection, processing, and reporting, which is time-consuming. With AI, these routine tasks might be automated, allowing teams to deal with higher-level, strategic work.
Imagine a future where an AI assistant can pull data from various sources, perform complex analyses, and generate reports almost instantaneously. This can enable analytics and business teams to spend more time interpreting data and developing strategic recommendations.
The role of analysts will evolve from being doers to orchestrators of AI-driven processes. They are going to guide AI systems to explore different hypotheses, validate results, and make sure the insights align with business objectives. AI will allow individuals to be way more powerful, meaning a small team could achieve what currently requires much larger groups.
Ultimately, firms that embrace AI early may have a competitive edge. They might be more productive and progressive, responding to market changes swiftly. As AI reshapes enterprise analytics, it opens latest possibilities for growth, making it an exciting time for businesses willing to guide the charge.
