Uncovering the "Diwa" of Market Research: Diwa AI's Latest Feature Unlocks Deeper, Smarter Analysis

Previously featured for its groundbreaking launch, Diwa AI has once again taken the spotlight, but this time for its latest updates that push the boundaries of AI-powered research. Known for its ability to conduct in-depth, voice-based interviews and generate real-time follow-up questions, Diwa AI goes beyond the standard chatbot, blending qualitative and quantitative research at scale. Its advanced automation tools streamline data collection and analysis, helping organizations interpret complex qualitative data with greater speed and clarity.

Now, Diwa AI is introducing new features that elevate its capabilities even further. These include thematic summarization, sentiment analysis, and soon-to-launch innovations like network-call interviews and chat-to-dashboard querying. Together, these updates transform Diwa AI into a truly end-to-end research solution—one that uncovers not just data, but the deeper essence behind every response.

In this exclusive conversation, Jose Lorenzo Villabroza, CEO and Co-Founder of Diwa AI, shares how these innovations continue to revolutionize market research and empower organizations to tap on actionable insights like never before.

From Raw Data to Real Meaning

When asked about the newest features Diwa AI has rolled out, CEO and Co-Founder Jose Lorenzo Villabroza was quick to point out how these innovations directly address one of the biggest pain points in qualitative research: overwhelm.

“We’ve always been about depth and scale,” Villabroza said. “But the next big challenge was: how do we make sense of thousands of open-ended answers, without compromising insight?”

To solve this, Diwa AI recently launched a thematic summarization and sentiment analysis tool, capable of processing raw qualitative data in real time. The tool identifies recurring themes and classifies emotional tone across responses, whether positive, negative, or neutral. It even provides breakdowns by any captured variable such as age, gender, and location, helping researchers quickly pinpoint how different groups respond. The update is like going from a wall of noise to a clear map of what people are really saying.

“We wanted users to move beyond the ‘what’ and into the ‘why’ because that’s where the real insight lives,” Villabroza added. 

Why These Updates Matter Now

Villabroza shared that these features were part of a long-term roadmap, but became a priority as users, especially those in fast-paced industries like marketing, UX, and academia, began collecting more data than they could manage.

“Everyone wants to hear from their market, but no one has time to read through 500 detailed responses,” he said. “That’s where our new analysis feature comes in, it helps users uncover the essence of their data at scale.”

The name Diwa AI itself is drawn from the Filipino word diwa, meaning “spirit” or “essence”—a nod to the startup’s core mission of understanding the human side of data. These latest updates further embody that mission, turning unstructured text into actionable, human-centered insights.

Responsible AI for Market Research 

As Diwa AI grows in capability, the team remains firm on one key principle: AI is a partner, not a replacement, and not about outsourcing thinking, but about accelerating it. When asked how the tool avoids the ethical pitfalls often associated with generative AI, Villabroza explained:

“Everything the system generates, every summary, every insight and answers, all are fully editable and auditable. We built it so that users stay in control.”

Diwa AI also includes features to standardize researcher criteria and reduce bias in both data collection and analysis. These design choices, Villabroza said, are part of their commitment to responsible AI development. After all, Diwa AI cannot remove all bias from data, but it can create systems that make those biases visible and help people account for them.

Elevating the User Experience: Designed for Real-World Deployments

With the new feature of Diwa AI, it becomes a more comprehensive, end-to-end research platform, from voice-based interviews to automatic data analysis. The platform supports multiple languages, recognizes regional accents, and provides a highly customizable interface for a wide range of users.

Villabroza added that one of Diwa AI’s core differentiators is its simplicity of deployment. “You can set up your questions, generate a link or QR code, and launch a study right away. That’s a big deal especially for organizations working with limited resources.”

What’s Next for Diwa AI?

The team will not stop here. Villabroza gave us a preview of the next wave of features, one of which will allow Diwa AI to conduct interviews via network calls. This will make the platform more accessible to communities in rural or low-bandwidth areas, a move that aligns with a vision of inclusive innovation.

Also in development is a chat-to-dashboard interface, which will allow users to interact with their datasets through natural language. Want to know how Gen Z respondents in Metro Manila feel about a product? You will be able to ask, and get a clear, visual answer instantly.

In a world overflowing with data, the real challenge is not collecting information but making sense of it. Diwa AI’s latest innovations do not just streamline research, but they elevate it and help researchers, brands,  companies and institutions connect more deeply with the voices behind the numbers. 

By transforming raw responses into clear, meaningful insight, Diwa AI continues to bring the essence of human thought to the forefront of decision-making proving that the future of research is not just faster, but more human.