Read how Stravito Assistant, the next-gen GenAI tool, empowers users with a conversational approach, boosting efficiency and uncovering hidden trends in market research.
Generative AI is transforming data exploration and insights generation. Stravito, a leader in this field, has unveiled Stravito Assistant, its next-generation AI tool. In this interview, Vignesh Swaminathan, Stravito‘s VP of Products, discusses how the Assistant surpasses its previous offering and empowers users.
Stravito Assistant ushers in a conversational, user-friendly era of generative AI. Swaminathan explains that it fosters an intuitive dialogue-like experience for delving into company research and replacing data queries.
The interview explores Stravito Assistant’s key features and workflow enhancements and how it empowers secure and transparent insight discovery. It also details Stravito’s collaboration with Fortune 500 companies like Heineken to tailor the Assistant for real-world needs.
Curious about the future of generative AI, its implementation, and its safeguards? This interview comprehensively examines Stravito’s cutting-edge solutions that are shaping the industry. Learn how Stravito Assistant can revolutionize data exploration and bring insights to life.
Full interview;
How does Stravito Assistant differ from Stravito’s first generative AI tool, launched last year?
Following on from Stravito’s first generative AI offering, answers, where users could ask a question and get an answer based on a company’s research housed in the platform, Stravito Assistant is a trusted insights companion that stands out because of its conversational approach, ease of use, and customization.
Using Assistant, individuals can collaborate and engage in meaningful conversations using the technology, allowing for deeper exploration of their research queries. For example, questions asked at a beverage company might include “How do European millennials feel about non-alcoholic beers?”, “What are consumer barriers/motivations for buying cider?” or “What are some trends in sustainable packaging in 2024?” The Assistant can delve deeper into users’ research through prompts and clarifying questions, allowing employees to easily navigate a knowledge space and reduce time-to-insight securely and transparently.
Users can ask broad, general population questions or narrow their search by specifying based on location or time. Each response is properly footnoted throughout, so users can fully trust the answer provided and easily click through to the source material for more details.
In what ways will users benefit from Stravito Assistant?
The main benefits of using Stravito Assistant include improved workflows and discovery, which increase efficiency and productivity.
Stravito Assistant’s ability to search, analyze, and summarize large data sets saves users countless hours that would have previously been spent manually doing the work. This benefit is twofold: It reduces time to insight so that insights professionals and business stakeholders can make more informed decisions faster while providing users with increased bandwidth to focus on other tasks.
Assistant was built hand-in-hand with Fortune 500 customers, and iconic multinational brewer Heineken has already started using the tool. Global Head of Strategy and Insights Lalo Luna comments:
“Generative AI offers significant benefits in processing large volumes of qualitative and quantitative data, and we’re excited to integrate generative AI into our operations further using Stravito Assistant. Stravito’s human-centric approach to innovative technology positions them perfectly to assist us in boosting productivity and improving workflows that deliver the right insight at the right time to the right people, helping us re-use insights and reduce the time to market.”
How do you recommend that users best implement the technology in their day-to-day processes?
Stravito Assistant is part of the Stravito enterprise insights platform, which helps the world’s largest enterprises easily store, discover, and integrate market and consumer insights.
By using the Assistant tool, insights professionals and business stakeholders can collaborate with generative AI technology to find answers faster, ask better questions, and immediately leverage a wealth of insights to inform real-world business decisions. In short, Assistant can be implemented by insights professionals and other business stakeholders who need a quick, easy, and inspiring way to discover accurate consumer insights.
In what ways does Stravito Assistant guide users in identifying the insights they’re searching for?
Individuals can ask Stravito Assistant many questions that will allow them to navigate a knowledge space easily. Users can ask broad, general-population questions or narrow their search by specifying based on location or time.
Assistant will gently prompt users to ask follow-up and clarifying questions, drilling deeper into their research so that users can receive the most useful and applicable information for their context.
If a user’s inquiry can’t be answered using information from their owned data, Stravito Assistant will let them know. This crucial feature allows users to trust that they receive factual information and identify any potential research gaps, empowering users to refine their data strategy and seek out additional sources or insights if and when needed.
With so much discourse around generative AI tools, how can business leaders ensure they efficiently utilize their generative AI solutions?
To determine the optimal use of generative AI, business leaders should analyze tasks that consume significant employee time and consider how AI can increase employee bandwidth to focus on alternative tasks. By addressing these questions, leaders can gain insights into some areas where generative AI can maximize productivity and efficiency.
A critical aspect of this assessment involves leaders gaining a full understanding of both their business needs and the capabilities of generative AI. Educating themselves about the technology enables them to grasp its functionalities, benefits, and potential drawbacks. Combining this understanding with company needs analysis, leaders can effectively define how generative AI should be integrated into their operations.
What level of trust should leaders put in their generative AI solution? What safeguards should they look for to protect against generative AI hallucinations?
Implementing generative AI solutions gives companies incredible power and speed to parse large volumes of data, delivering a great productivity boost and promoting exploration and inspiration through a seamless interface. However, the challenges of incorporating generative AI into systems are multi-dimensional: Enterprises need to ensure they only work with trusted vendors for their AI solutions and that the data they use in AI-enabled systems is handled securely and compliant.
Of course, there is also the risk of hallucinations from some generative AI tools, which have received much media attention over the past year. For enterprises reliant on market and consumer research to make business decisions, it’s pivotal that any tool they implement only uses vetted data to generate AI-enabled answers – unlike open AI apps that pull from the public domain. Furthermore, when it comes time to integrate, ensure that a human-run service layer complements the generative AI tool. Implementing generative AI necessitates a human component to ensure its effectiveness.
In Stravito’s case, Assistant has been built with the utmost focus on reliability, privacy, and security. Stravito Assistant draws information only from each client’s owned data, which is never shared with third-party providers, not even for training purposes. Stravito is an ISO 27001-certified organization adhering to the highest standards of trust and confidentiality.
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In what ways has generative AI grown and evolved over the past few years?
Generative AI has evolved in technology over the past few years, particularly in the speed and accuracy of generating answers to different questions. However, one of the biggest milestones has been the evolution of the user experience.
Generative AI technology has been around for a while and is progressing quickly. But the point at which it suddenly became accessible and usable to everybody was when the ease of usage complemented the quality of responses. Moving to a seamless conversational chat experience did two main things: 1) it revealed the complex workings of the underlying technology only when required; 2) it did so in a way that gave the user agency into how that complexity could be controlled.
This interaction is now teaching GenAI development teams how to evolve the technology to go hand-in-hand with the conversational experience so it stays usable.
Moving forward, one of the new developments we’ll see will be new versions of that user experience for specific knowledge bases. That should reflect how the technology is being adapted for different knowledge types and the user experience for the specialists and niche users of that knowledge.
