Consumer behaviour is shifting so rapidly that conventional research models are unable to keep pace — a gap Bengaluru-based founder Abhilash Madabhushi is intent on closing. His startup, Consuma, which recently secured ₹12 crore in seed funding, promises to compress research timelines from months to just half an hour. As Madabhushi told AIM, “A trend cycle itself is 60 to 90 days,” emphasizing that today’s consumers often discover products, evaluate options, and make purchases within moments of encountering a single Instagram or YouTube post. In a landscape where attention spans and decision windows are shrinking dramatically, he believes brands can no longer afford slow, episodic insight cycles.
Consuma’s solution is a real-time intelligence engine powered by autonomous agents capable of tracking billions of digital interactions continuously. Instead of static reports, the platform offers interactive dashboards that let users drill into raw conversations, review source trails, and even query a built-in voice agent. This fluid, multi-dimensional experience is designed to unlock the depth, volume, and speed that legacy approaches struggle to deliver. “We give you 1,000x more usage of data in one day,” Madabhushi said, pointing out that traditional outputs fall short because “reports are two dimensional. You can’t interact.” The company’s multi-agent Rapid Research Platform is built to operate like an endlessly scalable research team, surfacing patterns that human analysts would rarely spot — such as correlations between deep roast coffee drinkers and romantic novel readers.
According to Madabhushi, this capability is precisely where deep research tools hit their limits. “Deep research relies on one data source only,” he explained, noting that the most meaningful consumer discussions often emerge in digital spaces invisible to standard search engines. To overcome this, Consuma has spent years engineering a suite of adaptable scrapers that harvest publicly available conversations without bypassing paywalls or placing undue load on platforms. This careful, ethics-aligned approach allows the system to map evolving sentiment with breadth and nuance across diverse channels.
By enabling brands to interact with data dynamically and at scale, Consuma aims to redefine how consumer intelligence is gathered and applied. In a world moving at algorithmic velocity, its model suggests that research must evolve from static observation to continuous, agent-driven discovery — and do so in real time.
