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Home News Bengaluru’s Deevia Software Wins Toshiba GridDB IoT Hackathon. Bengaluru teams dominate the...

Bengaluru’s Deevia Software Wins Toshiba GridDB IoT Hackathon. Bengaluru teams dominate the leaderboard, with Wimera finishing second and RichieRich securing fourth place

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Toshiba Announces Winners of GridDB Cloud IoT Hackathon, Highlighting Industry-Ready Real-Time Solutions from Across India

Toshiba Digital Solutions Corporation, in collaboration with Toshiba Software India Private Limited, successfully concluded the GridDB Cloud IoT Hackathon, an innovation initiative aimed at enabling students, developers, and startup companies to build real-time IoT applications using Toshiba’s GridDB® Cloud Database Service for Big Data and IoT.

The hackathon received strong participation from October 29 to December 14 2025, with over 250 applications from across India, addressing use cases including Healthcare, Finance, IoT, and Knowledge Management, demonstrating the versatility of GridDB® database service.

After an intensive evaluation process, five finalist teams advanced to the in‑person final rounds held in Bengaluru from January 31 to February 1, 2026. During the onsite sessions, they received direct technical support and mentorship from the GridDB® technical team, helping them further refine their proof‑of‑concept (PoC) solutions. Following the final PoC presentations to a panel of judges, the results were announced as follows and all the finalists shared a total cash prize of USD 5,000.

Toshiba GridDB Cloud IoT Hackathon Finalist Results

RankTeamPoC ThemeLocation
1Deevia SoftwareGenAI based Enterprise Document Management PlatformBengaluru
2WimeraIoT PoC for Industrial MachinesBengaluru
3VitalWatchPreventive Risk Disease PoCMaharashtra
4Richie RichFinancial Analytics PoCBengaluru
5GooRoo Mobility IndiaLow-cost remote Healthcare Solution PoCGujarat

The GridDB Cloud IoT Hackathon helped create a community of innovators who are eager to use real-time data to solve real-world problems. Toshiba will continue to engage with participants through the GridDB® community and future initiatives in India, strengthening its contribution to the country’s digital transformation and IoT ecosystem.

Commenting on the initiative, Mr. Hiroshi Tsukino, Director and Vice President of Toshiba Digital Solutions Corporation said, “Toshiba is committed to making a better world through the power of data by utilizing various kinds of data generated by businesses related to social infrastructure and turning them into platforms. The Toshiba Group is pursuing a strategy of transformation toward Digital Evolution (DE), Digital Transformation (DX), and Quantum Transformation (QX) to develop the digital economy, and India is a key innovation hub in Toshiba’s global digital strategy. Through initiatives like the GridDB Cloud IoT Hackathon, we are empowering developers with advanced data platforms to create scalable, real-time solutions that address complex industrial and societal challenges.”

Addressing the participants and judges, Mr. Ramdas Baliga, Managing Director, Toshiba Software India Private Limited added, “Toshiba Software India’s key strategic direction is to evolve into a digitally agile Centre of Excellence, embedding digital thinking and speed across everything we do, and translating advanced technologies into real-world IoT solutions. Initiatives such as the GridDB Cloud IoT Hackathon reflect this commitment by bringing together Toshiba’s experts and engineers with next-generation innovators to showcase technologies that will shape the future. I am pleased to see the event attract many such ideas, and proud that Toshiba could support these innovators in advancing their vision.”

Sharing their experience, Mr. Nitin Mangalashankar, hackathon participant of the winner teamDeevia Software India Private Limited said, “From a hands-on perspective, the hackathon was a great opportunity to quickly prototype and validate a GenAI-driven use case on top of real-time operational data using GridDB Cloud. The platform allowed us to ingest and query time-series data efficiently under tight timelines, making it easy to focus on experimentation and solution design rather than infrastructure challenges.”

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