We have a really, really great session for your Friday today. We have Ayman ready for MarketLogic. Without any further ado, Ayman, go ahead and take it away. Alright. Thank you, Kat, and thank you everyone for tuning in to this session. My name is Ayman Chalhoub. I’m the senior director of growth and product experience at MarketLogic and excited to share with you some of what we’ve been building today. So at MarketLogic, we work with some of the largest companies in the world, helping them get insights out of their data much faster. We provide them with a market intelligence and an insights management platform. And we’re talking here about massive libraries of consumer research, intelligence, and surveys, whether it’s their own primary proprietary studies or paid and unpaid syndicated sources. In short, we help them squeeze as much value out of those assets. And as you can see, many of our operate globally, which means their data has all kind of regional and local nuances, but they still need a centralized, standardized, and secure way to find, connect, and use insights within their teams. We serve a huge range of industries, from pharma to FMCG, retail to telco, finance to automotive. So we see every day firsthand, what analysts and insight teams across every sector need and where they also struggle. And what we see across every industry today, one thing is certain that AI has really changed the game. It’s no longer enough to just, surface insights. The real challenge is how do we do insights into a growth engine for business impact, to grow your business, your product, your brand, and do it fast. Our research shows that as businesses are moving faster and noise is increasing, the stakes are higher, still, a lot of those organizations are not able to get to their insights faster, which makes more than forty percent of product and innovation and marketing teams making decisions purely based on gut feel, and millions are lost in terms of research. So you know the challenge. The challenge is that, the complication is more data is coming at us, and it’s coming at you faster than ever in more formats from more places. Structured data like sales figures, product adoption rates, customer demographics are usually living in databases and excel sheets or trackers. It’s like one side of the world. And unstructured data like customer reviews, social posts, call transcripts, analyst reports, they sit somewhere else entirely, often buried in PDFs, PowerPoints, video, and audio transcripts. So today, I want to show you how DeepSights, our flagship GenAI product, connects those two worlds. And if you take just one thing from today’s session, I hope it would be this, that with DeepSights, you can confidently handle bigger, more varied datasets, integrate and synthesize them in a seamless flow, and generate compelling insights in minutes Joe you can spend your time really driving the business rather than wrestling with your data. So what is DeepSights? DeepSights is your always on insights partner. It’s designed to help you get the right answers faster and to put them in the hands of everyone in the organization. One, it democratizes. So it makes your organizational knowledge accessible to everyone and not just the few people who know how to get to it. Two, it synthesizes. It connects all your different data sources, research reports, syndicated feeds, structured databases, and turns into clear, actionable insight. And third, it automates. It continuously scans, organizes, and surfaces what matters Joe you can scale your understanding across teams and even uncover opportunities for innovation. Now under the hood, it’s powered by your own market logic, which means it unifies and connects your whole inside ecosystem and grounds the platform with your own context, providing this deep evidence analysis, removing risks of misinterpretations or AI hallucinations. And it centralizes all those assets into one trusted hub. DeepSights can connect to any source and bring it into your workflow. And importantly, it’s operating within your secure environment, respecting your privacy, governance, and compliance requirements at every step. Let’s quickly jump into a demo of each sites. So I moved to our demo environment, and what you see here is a typical, a customer interface. This is a mimicked, type of FMCG sort of organization. And what you see is your Joe page. You see some of the, let’s say, assets available to this organization, syndicated resources like Syllysm, Intel, and some of their primary reports. And and the way you access deep sites is via this unified, let’s say, search interface. It activates three different modes. But today, we’re gonna get into and talk about answers. So answers allows you to answer any business question. Let’s pick up a question that I’ve asked a little bit earlier. Alright. So what DeepSights has done here is it went into the background and, looked into all of our research assets. And if you look at the structure of the question here, which plant based foods are showing declining growth, Which means it needs to look into a, a sales database. It needs to look into our performance as a company and what’s happening there. But, also, I’m asking it to look into what trends are driving that in APAC during twenty twenty four. So data that could come from unstructured surveys or research reports. What I see here on my right is the evidence based trusted sources. For example, I see all the sources that are structured, unstructured data that’s coming in from primary reports such as this, state of the industry, plant based trends. But what’s interesting here is that it’s showing me exactly in each market, the drop. So sixteen percent in Vietnam, for example, and Singapore, percentage wise and value wise. And what’s cool here is that it’s actually also looking at if you look at this source number six, it’s looking at my market data. It’s looking at a connected database of my performances of my sales performance. So if I dive deeper a little bit here, I can look and understand a little bit more about the database. So where’s that table coming from? What is the query that, at DeepSights has generated? So it calculates the the average negative growth rate and total value for FMCG subcategory. So it’s doing that on the fly, connected to the database, and it can even show me the SQL code done for this. So for data analysts, this is great because it shows full transparency of what, DeepSights is doing in the background. So what it did here is pretty cool. It’s connected to an actual live database to surface, the trends of sales, where the declines are happening. But it also looked into my unstructured reports showing the trends driving this decline. Usually, this type of question in a traditional workflow would take hours, days to get to it. You need to connect your market, get the sales data, sift through all the sales reports, all your primary reports, and try to generate a meaningful insight. Now what we’ve done here is we’ve done this in a few minutes. We were able to surface, a good narrative based on, solid trusted data that’s living in my, living in our in our home. So and and the cool part here is that in just a few clicks, we’re able to do that. And that’s the core message I wanna share with you today. DeepSights doesn’t just help you find insights faster. It connects to every kind of data, structured, unstructured in its one seamless flow. Now now that we’ve seen how structured and unstructured data can finally live in one place, financial metrics side by side with market chatter, you’re looking at a complete living picture of your market. But here is where it gets really interesting. So I’m gonna go back to the slides and Alright. So once those walls has fallen between those two worlds, you cannot just look at the past and see what happened. It it can actually help us look into the future and find emerging trends that can probably, detected from patterns that you wouldn’t might never spot manually. Gaps in competitor coverage, untapped customer segments, what we can call white space opportunities. And that’s where our DeepSights agents come in. So you’re not just reacting faster. You’re discovering what’s the next big move before everyone else. So on that, I wanna share a video we’ve built on our DeepSights agent, and I will share that next. Innovation is one of the biggest challenges facing businesses today. It’s not just about having a few good ideas. It’s about generating a high volume of quality ideas to find the ones that truly move the need because innovation is a key driver of incremental revenue and long term growth. That’s why we created the Innovation Studio, a project based environment designed to help teams fill the innovation funnel faster with better ideas. It brings structure, speed and intelligence to the front end of innovation where the pressure to deliver is highest. The journey begins with a clear briefing that describes what the objective of the innovation is. From there, AI recommends the most relevant insights that shall be used to inform the innovation journey. This can be from research you already have, it could be data from connected partner systems, or it could be from using the wealth of data generated by our AI agents, such as pre consolidated consumer trends. These agents continuously scan your knowledge ecosystem, whether it’s primary research, syndicated content or public sources to detect emerging market signals and profile them automatically. They’re not just searching, they’re interpreting, connecting and building insight. Here you see the agents have analysed the data to identify trends such as minimalist and multifunctional haircare routines. They then build rich, evolving profiles that go far beyond summaries. Each profile includes a trend definition, a quantitative landscape, commercial execution and more structured into chapters that reflect your organization’s best practices. As new information becomes available, the agents update these profiles highlighting what’s new, what’s changed, and what’s worth paying attention to. This ensures that your teams are always working with the most current, most relevant insights without needing to manually reprocess or recompile information. Let’s go back to our innovation studio. Joe this insights step ensures that every innovation journey starts with a strong foundation of relevant data and then the real work begins. Teams explore white spaces, generate ideas and shape early concepts. AI agents support each step, scouting opportunity areas, evaluating ideas and suggesting refinements. For example, when identifying white spaces the AI doesn’t just surface broad themes, it presents detailed opportunity candidates complete with visuals and structured descriptions based on your templates including consumer frustrations, attractiveness and opportunity scope. And the process is dynamic. Human experts remain in control, guiding the AI, reviewing outputs and refining direction. Just like we did with the white spaces, review all of the ideas and engage with AI to sharpen and consolidate them. And ultimately Innovation Studio will build concepts to bring those ideas to life. We can then further evaluate by engaging agents to do concept testing or first concept appraisals. Together, the Innovation Studio and Always on Agents offer a powerful combination: a structured AI supported environment for innovation, a continuous intelligence layer that keeps your insights fresh and actionable. The result? A smarter, faster, insights driven innovation journey, designed to help you generate more ideas, better ideas, and ultimately, the ideas that drive growth. Amazing. So, what we’ve seen here is DeepSights now is able to provide a collaborative intelligence framework, which means it can reimagine your processes, combining the best of human and agent intelligence to supercharge really the creativity of the organization. What makes those agents special is that they’re unique to you, which means our agents are adopting your best practices and your data, customizing them to your own innovation process so that it can constantly draw differentiated insights from your own proprietary datasets. And always on intelligence foundation, which means around the clock, insights discovery, powering your processes, and guiding your decisions. Those agents are can be goal centric, so skilled on demand agents, which means you’re creating a specialized agent to share the data and the work as a digital team to support your end to end processes at scale. And they are purpose built for insights, which means their superior contextual understanding makes sense of your data accurately. This deep evidence analysis we mentioned before removes any risk of misinterpretations and AI hallucinations. So it connects also to a comprehensive ecosystem of, third party insights, data providers, proprietary research, in house databases as we’ve seen, business apps, and other special purpose AIs. So, looking forward, what what we’ve seen, this is also as a from a third party, company, Forrester has done this total economic impact study on how deepness and market logic, drive results within these organizations. And, we’re excited to share some of those numbers with you today. For example, there’s a four hundred percent return on investment once DeepSights is implemented with a payback of six, of six months. Ninety seven percent speed to answer efficiency. Twenty seven percent, reduction, on research cost savings, fifty percent reduction on legacy solutions. So great numbers really to show, from a third party the real business impact that DeepSights can have in helping all these organizations and data analysts and teams surface the right, insights from connecting their existing datasets. So what’s needed really is not more AI. What’s needed is a system of intelligence, that connects the human and AI intelligence together. And that’s what DeepSights provides. If you’d like to know more, please connect and download some of our content, from this, QR code that I’m sharing on the screen right now. Give you a second or two for that. So this this document describes a lot of how our AI agents are applied to the insights industry. And if you’d like to try DeepSights as well, we provide a two week trial where you can connect and down and, subscribe, to our demo and see how that works with your own dataset. Thank you so much for listening in today and, excited to hear more about, about this from if you have any q and a, questions and answers. And, yeah. Amazing. Thank you, Eamon. I think we have time for one question really quick. I know we’re a little over time. We will not button to the other sessions, but we do have one really good question. In allowing sources to be changed and answers regenerated, how do you ensure that you don’t receive conflicting results? Yeah. Thanks, Kat. I think this is a great question. So we’re not really concerned with any untrue statements since deep science is really built from the ground up not to hallucinate. But by managing those sources and giving user control over what documents are used to generate an answer, we we can let the user, for example, say, like, I think these couple of studies don’t make sense or they are outdated, so don’t include them in your answer. So we intentionally enable this human expertise to come in and oversight with AI because we really believe that human and artificial intelligence together is what’s gonna drive, the value. Incredible. But on behalf of everyone from Greenbook, thank you so much for being here, and we will see you in the next session.
Pulling insights from surveys, interviews, social media, and sales data can be overwhelming—each source is tedious on its own and even more complex together. Thanks to AI and integrated analytics platforms, the path from collection to decision is now faster, smarter, and more accessible.
On Friday, 15 August, we partnered with Greenbook for a live demo showcasing how DeepSights accelerates the use of insights and drives innovation across diverse data sources.
As highlighted in Greenbook’s latest GRIT Report, we’re well into a new era of “data enlightenment,” where the urgent need to activate available data meets powerful new analysis tools—momentum that’s only increased with commercially viable AI.
The session demonstrated practical ways to break down knowledge silos, eliminate duplicated research spend, and spark product innovation and competitive advantage through insights—offering a clear view of a more efficient, insight-driven future.
