Matters.AI Secures ₹55 Cr to Build Self-Learning ‘AI Security Engineer’
Matters.AI, the AI-native data security start-up, just wrapped up a ₹55 crore financing round. The cash is earmarked for what the team calls an “AI Security Engineer” - a self-learning system that aims to spot, forecast and neutralise data-risk threats without a human hand. In theory it should run on cloud services, SaaS endpoints and even on-premises gear.
Most of the money - about ₹42 crore - arrived as a seed investment, which hints at early-stage faith in the idea. The pitch leans heavily on autonomy: the engineer watches the data it protects, then tweaks its own defenses. It sounds bold, perhaps a bit too bold, but that’s the angle they’re pushing.
Enterprises today juggle a mess of workloads, so a single tool that hops between them could make risk management a bit easier. Still, the real test will be in the field. The round was announced without a firm date, yet investors seem to think there’s enough upside to back what might become a new slice of enterprise defence.
Whether the AI Security Engineer lives up to the hype? That’s still an open question.
AI-native data security company Matters.AI has raised ₹55 crore to pioneer a new category of enterprise defence, the “AI Security Engineer”, a self-learning system that autonomously detects, predicts, and mitigates data risks across cloud, SaaS endpoints, and on-prem environments. The ₹42 crore Seed round was co-led by Kalaari Capital and Endiya Partners, with participation from Better Capital, Carya Venture Partners, and leading cybersecurity angels. An earlier ₹13 crore Pre-Seed round was led by Better Capital and Carya Venture Partners.
“The world doesn’t need another dashboard screaming alerts; it needs a system that can think,” Keshava Murthy, co-founder and CEO of Matters.AI, said. “That’s the AI Security Engineer, one that never sleeps.” The funding will accelerate product R&D in predictive detection, expand go-to-market operations in India and the US, and scale engineering and customer success teams serving highly regulated sectors under the Digital Personal Data Protection (DPDP) Act. With over 90% of enterprise data remaining invisible to security teams, Matters.AI aims to unify visibility and protection.
Its self-learning engine leverages semantic graphs and predictive models to understand data behavior, intent, and context, shifting from reactive alerts to autonomous prevention.
Matters.AI just announced a ₹55 crore raise - ₹42 crore seed led by Kalaari Capital and Endiya Partners, plus a ₹13 crore pre-seed that came earlier. Better Capital, Carya Venture Partners and a handful of cybersecurity angels also jumped in. The money is earmarked for a self-learning platform that says it can spot, forecast and curb data risks in cloud, SaaS and on-premise setups, all on its own.
The team markets it as a brand-new kind of enterprise defence. I haven’t seen any public proof that it can run at scale without a human watching over it. Integration with the security tools companies already use could be a headache, which might slow uptake.
The backing does signal optimism, yet it’s still fuzzy whether the AI Security Engineer will consistently protect the wide variety of environments out there. We’ll probably need real-world rollouts and third-party tests to see how it performs. Their promise of autonomous mitigation also begs questions about false positives and how often the model will need fresh training.
Covering on-premise gear may call for heavy customization, and I’m not sure the accuracy will hold up as threat tactics shift.
Further Reading
- Matters.AI Raises Rs 55 Cr Seed Funding - Rediff Money
- Matters.AI - Your AI Security Engineer for Data - Matters.AI
- Papers with Code - Latest NLP Research - Papers with Code
- Hugging Face Daily Papers - Hugging Face
- ArXiv CS.CL (Computation and Language) - ArXiv
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Common Questions Answered
What specific functions will the 'AI Security Engineer' perform according to Matters.AI?
The AI Security Engineer is designed as a self-learning system that autonomously detects, predicts, and mitigates data-risk threats. It operates without human intervention across various environments, including cloud platforms, SaaS endpoints, and on-premises infrastructure.
Which investors co-led the ₹42 crore seed round for Matters.AI?
The ₹42 crore seed investment was co-led by Kalaari Capital and Endiya Partners. This round also included participation from Better Capital, Carya Venture Partners, and several leading cybersecurity angels.
Across which environments does Matters.AI claim its AI Security Engineer technology works?
Matters.AI states that its technology functions across cloud platforms, SaaS endpoints, and on-premises environments. This comprehensive coverage is intended to provide enterprise-wide data security.
What is the total financing amount raised by Matters.AI and how was it structured?
Matters.AI secured a total of ₹55 crore in financing. This amount was split between a ₹42 crore seed round and an earlier ₹13 crore pre-seed round.