The system helps enterprises comply with India’s Digital Personal Data Protection (DPDP) Act by providing real-time insights into data movement and security, making it particularly suitable for regulated industries.

Matters.AI’s platform addresses growing privacy regulations and AI adoption challenges, aiding compliance with the DPDP Act and reducing data security risks.

Matters.AI, an AI-native data security company, has raised ₹55 crore to develop an autonomous 'AI Security Engineer' system that detects, predicts, and mitigates data risks across various environments.

Designed to unify visibility and protection, the system addresses the fact that over 90% of enterprise data remains invisible to security teams, thus enhancing proactive security measures.

The platform offers features like endpoint visibility through eBPF tracing, data lineage, fingerprinting, and supports both on-premises and SaaS deployments, aiming to prevent data exfiltration and misuse in real-time.

Clients include Groww, Credit Saison India, Indian International Insurance, and Nokia, with operations in India and the US, competing with firms like Cyera.

Industry experts emphasize the importance of such solutions, as data breaches cost companies millions and most sensitive data remains unprotected and invisible within enterprises.

The platform integrates seamlessly with major cloud and SaaS platforms including Zoho, Snowflake, Salesforce, AWS, Azure, GCP, and Databricks, enabling comprehensive control over AI-driven data landscapes.

The funding comes at a time when India’s evolving data privacy regulations, including draft rules for the DPDP Act, emphasize data security, though some ambiguities pose compliance challenges for startups.

The funds will be used to accelerate R&D in predictive threat detection, expand operations in India and the US, and strengthen engineering and customer success teams, especially for regulated industries.

Matters.AI aims to scale its presence, enhance reasoning and integration capabilities, and pursue go-to-market strategies in North America, targeting a fivefold increase in annual returns and consistent growth.

The company’s AI system addresses high costs of data breaches, visibility gaps, and alert fatigue by unifying discovery, lineage, and control in a single intelligent platform.

The platform uses multimodal large language models and eBPF technology to trace data movement and automate investigation and remediation with a copilot feature.