Gibran raises $2.6 million to build nature-inspired, adaptive AI systems

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Gibran raises $2.6 million to build nature-inspired, adaptive AI systems

Gibran raises $2.6 million to build nature-inspired, adaptive AI systems (Representative AI image)

BENGALURU: AI research startup Gibran has raised $2.6 million in a seed round led by Together Fund to develop a new class of adaptive, scale-free systems that augment human creativity and decision-making.

The company draws on principles from evolutionary biology and complex adaptive systems to rethink how artificial intelligence collaborates with people in open-ended, non-linear ways, as per a statement.Co-founded by Govind Balakrishnan, Edgar, Srikant Chakravarti, and Suzanne Sadedin, Gibran aims to move beyond conventional automation by fusing large language models with nature-inspired approaches. Its core thesis is that AI should evolve with humans, not replace them.“AI shouldn’t replace people, it should expand how they think, create, and decide,” said Balakrishnan. The team’s research is focused on building systems that adapt and grow with user needs, emphasising creativity, autonomy, and ethical alignment over brute-force scale.The founding team combines experience across science, engineering, and product design. Sadedin is an evolutionary biologist and complexity theorist.

Chakravarti has worked on distributed AI infrastructure. Edgar brings deep generative systems expertise and Balakrishnan leads product vision and go-to-market efforts.Together Fund, which backs AI-native startups across the India-US corridor, said Gibran’s approach stood out for its originality. “This is not just about productivity, it’s about human flourishing,” said Manav Garg, founding partner at the firm.The funding will be used to expand Gibran’s research team, develop its core platform and explore early applications in domains that require adaptive, human-aligned AI systems. As AI tooling increasingly converges around commoditised LLM wrappers, Gibran is positioning itself at the frontier of systems that evolve, self-organise, and respond to context in ways more akin to biological intelligence than programmed logic.

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