Nebulock, a cybersecurity startup reinventing data protection in AI-native architectures, has raised $8.5 million in seed funding to accelerate its mission to make sensitive data defense-first, not reactive. The round was led by Bain Capital Ventures, Decibel Partners, Zetta Venture Partners, and In-Q-Tel, with support from Aviso Ventures, Step Function, and prominent angel investors. The startup is led by founder and CEO Damien Lewke, a former Palantir and Google security engineer.

With enterprises rapidly adopting LLMs and automated agents across internal stacks, data access patterns have shifted - leaving traditional perimeter-based security models obsolete. Nebulock addresses this shift by providing data-layer security that travels with the data itself, powered by policy-aware wrappers, ML-driven activity monitoring, and agent-aware access control.

Rather than patching vulnerabilities downstream, Nebulock embeds compliance and control directly at the file, field, and application layer - creating guardrails that anticipate risk, not just log it.

Why Security Must Evolve for the AI-First Enterprise

The generative AI wave has introduced unprecedented surface area for data leakage. Autonomous agents can query, write, and distribute internal data faster than legacy tools can observe it. Traditional DLP (data loss prevention) solutions, built around known channels and static policy enforcement, are now too slow, too brittle, and too noisy.

Nebulock’s insight is clear: the age of policy-bound endpoints is ending. What’s needed is a context-aware, real-time control layer that governs how structured and unstructured data flows through applications, APIs, and autonomous logic - especially in regulated sectors like finance, health, and defense.

Their architecture delivers exactly that - tightly scoped policies enforced in real time, deeply embedded into developer workflows and infrastructure primitives. The result is a product that doesn’t just detect misuse - it prevents it.

And this is where founders can take a critical cue. Nebulock didn’t try to chase every potential AI opportunity; they drew a sharp line around the one thing that would be universally necessary in the AI transition: trust at the data layer. In volatile infrastructure shifts, the best position isn’t always the most exciting - it’s the most inevitable. Products that work invisibly under disruption become irreplaceable. By building control into the substrate of data itself, Nebulock ensured that their value scales with risk, not with vanity metrics. Founders building in AI should consider this: defensibility isn’t always about doing more - it’s about making your solution the last thing anyone would dare replace.

How the Platform Works

Nebulock’s platform operates across three layers:

• Data Guardrails: Policy-as-code wrappers embedded directly into files, DB tables, and structured objects.
• Real-Time Access Monitoring: ML models that detect abnormal access sequences and lateral movement.
• Agent-Aware Controls: Context-sensitive gating for LLM queries, internal AI agents, and third-party automation tools.

Everything is developer-friendly and integrates with existing CI/CD, identity management, and observability tooling. Teams can deploy protection without changing how they code.

Already deployed in stealth with several AI-native SaaS firms, Nebulock has helped reduce false positives by 90%, block risky queries at runtime, and eliminate the need for human review in over 70% of low-sensitivity data access.

The Founder’s Deep Security Pedigree

CEO Damien Lewke brings extensive background from his time leading security teams at Google and Palantir, where he specialized in secure infrastructure and data exfiltration prevention. His approach at Nebulock is grounded in a belief that data should be protected not at the edges, but at the core. His prior work on scalable policy enforcement systems for state and federal clients positioned him uniquely to understand how both compliance and AI can be reconciled at speed.

Backers Betting on AI-Safe Infrastructure

Investors in the round include some of the most forward-looking firms in enterprise tech:

• Bain Capital Ventures, known for backing early enterprise leaders
• Zetta Venture Partners, focused on AI-first infrastructure
• In-Q-Tel, with deep ties to federal intelligence and defense sectors

Their support reflects a growing recognition: AI-native architectures require security-native layers - not retrofits. With privacy mandates tightening and AI agents becoming the default interface, Nebulock is positioned to become a critical component of next-gen infrastructure stacks.

What's Next for Nebulock

With the seed funding, Nebulock plans to:

• Expand engineering across New York and San Francisco
• Launch SOC 2 and FedRAMP-ready packages for compliance-driven buyers
• Deepen LLM-aware enforcement tooling
• Build integrations with leading observability and API gateway solutions

The company is actively hiring engineers, customer success managers, and go-to-market leads to meet growing enterprise demand. Longer-term, they plan to explore partnerships with foundation model providers to inject fine-grained access control into embeddings and vector stores.