Team Startupcity

• Secured $2.4M pre-seed funding led by 8X Ventures with multiple strategic investors.
• Developing no-code AI agents and Robot-as-a-Service (RaaS) for high-value industries.
• Expanding into North America and Europe with focus on multi-agent autonomy and vision-based navigation.

Bengaluru deeptech startup Neuralzome Cybernetic raised $2.4 million in a pre-seed funding round that was led by 8X Ventures, with participation by Turbostart on a strategic basis, along with Avinya Ventures, Saka Ventures, Appreciate Capital, Astir Ventures, IIM Ahmedabad's CIIE, SIDBI, and angel investor Heston Castelino.

The new influx of funds will be used to boost research and development in important areas including multi-agent autonomy and vision-based navigation, manufacturing capacity ramps, and expansion into the North American and European markets.

Established in 2023, Neuralzome Cybernetic is shaping the future of intelligent, autonomous systems with its learnable, no-code AI agents. These agents enable instant deployment in the physical world, without companies having to invest in maintaining deep robotics expertise in-house. The Robot-as-a-Service (RaaS) approach of the startup allows businesses to tap into leading-edge robotics solutions on a variable basis, cutting down on initial investment and operational complexity.

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Neuralzome's offerings are now aimed at high-value, labour-intensive sectors where automation can provide instant efficiency and cost benefit, such as orchard management, commercial landscaping, and other large-scale outdoor operations.

At the core of its tech stack is NeuralPilot, a general-purpose AI-driven control platform that interacts with the startup's RedPill simulation environment. This convergence enables the development of photorealistic digital twins, which allow robots to be trained in very realistic and complex situations prior to ever being deployed in the field. By emulating thousands of potential scenarios, Neuralzome significantly cuts down on both time and field training costs, while enhancing reliability and responsiveness in actual deployments.