Databricks has made a strategic investment in US-based cybersecurity startup ziggiz, one of only five companies selected for the inaugural cohort of its new AI Accelerator Program. The program backs high-potential early-stage startups building AI-native products on the Databricks platform. Financial terms were not disclosed.

Why Databricks Invested

ziggiz is a category-defining Cyber Data Platform to collect, store, semantically transform, analyze, and share. The ziggiz architecture fundamentally shifts decision-making from limited visibility in point solutions to the open architecture Cyber Lakehouse.

The investment underscores Databricks' recognition of cybersecurity as a critical growth area for data-intensive applications. ziggiz's founding team brings elite expertise from DoD cyber operations, large-scale data engineering, and detection engineering. Dr. George Webster, CEO and co-founder, previously ran missions before transitioning to banking security. Co-founder and CTO Zoe von Pentz and Head of Product Ryan Faircloth specialize in data platform architecture and detection engineering at scale.

When ziggiz demonstrated how their platform could solve fundamental security failures within the security industry itself; such as presenting a semantic view of network communication data across vendors and versions—the strategic rationale became clear.

The Industry Problem

"Data infrastructure is hard," Ryan explained. "Our legacy competitors leave solving those problems to the end user and often speak as if it's a solved problem while knowing it's just a problem they don't want to invest in."

Today's security data stack is built on infrastructure designed two decades ago. It simply can't keep up with the volume and complexity of modern environments. As a result, essential services such as hospitals are compromised, business operations are disrupted, and a single attack can lead to billions of dollars of losses. AI is only making the problem worse with more data, more feeds, and more complexity.

Legacy tooling takes 2-5 hours to detect activity when attackers can complete their objectives, including full data exfiltration, in as little as 25 minutes. Onboarding every new data source is a 3-6 month manual exercise, then ongoing usage and maintenance is difficult and labor-intensive. Because data processing and management is fragmented, no tool currently delivers a unified service with fast detection customers actually need. Instead, the onus is on the customer to stitch together existing solutions and hope it covers their bases.

The problems don’t stop there. Content to assist users in understanding data, dashboards, notebooks, detection, and more are left to end users and third-party professional services. Legacy solutions leave each customer discovering, inventing, and refining the wheel.

ziggiz's Advantage

ziggiz's consumption-based model aligns the company's success directly with customer usage. Because ziggiz only succeeds when customers actually use the platform, the pricing model drives two critical advantages:

• Speed: ziggiz' batteries-included approach allows customers to see data flowing within days, limited only by their internal approval processes.

• Affordability: ziggiz disconnects spend on ingest, storage, and compute, making previously unaffordable data sets accessible.

• Endurance: ziggiz knows today’s problems are just the beginning. Starting with a platform to develop solutions rather than a point solution to develop a platform. 

The company's strategy of end-to-end ownership creates its competitive moat. By making easy what competitors let remain someone else's problem, ziggiz positions itself as cheaper for customers while unlocking opportunities faster. Customers who have reached peak spend and can't achieve their objectives can redeploy budgets to start big rather than start over.

For security teams that have built careers around data infrastructure problems, ziggiz offers upskilling into more valuable tasks focused on threat detection, visualizations, and documentation—redeploying knowledge equity rather than eliminating it.

What This Unlocks

The partnership creates what George describes as "an ecosystem within an ecosystem." Application vendors like Alpha Level can build products on ziggiz's semantic layer without rebuilding foundational data pipelines, transformations, or conceptual models.

"They can start with the semantic meaning," Zoe said. "Application partners can start with their idea instead of building a bespoke data platform."

Our ecosystem partners can analyze data in place through the open platform or we can forward data to legacy solutions.

This semantic layer approach eliminates duplicated infrastructure work across the industry. Reducing friction in use case exploration drives the roadmap, allowing the team to focus on customer requirements and provide a more complete solution than legacy competitors can justify investing in.

Founder Perspective

"We are building a true end-to-end solution," Zoe said. "We actually partner with other vendors also working with Databricks. We are a force multiplier."

George's offensive cyber background shapes the company's defensive platform philosophy. "We know cybersecurity is about the offensive—if we didn't have adversaries we wouldn't need to defend. By building a Cyber Lakehouse and data-centric security solutions on Databricks, we have created an ecosystem within an ecosystem."

About the Databricks AI Accelerator Program

The investment signals Databricks' commitment to investing in accomplished technical founders working to solve some of the most complex issues in the enterprise. By supporting startups that extend core platform capabilities into specialized use cases, Databricks demonstrates vertical integration within the data ecosystem and increased interest in security solutions built on their infrastructure.

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About ziggiz

ziggiz is a UK-based cybersecurity startup building end-to-end Cyber Lakehouse solutions on the Databricks platform. Founded by experts in offensive cyber operations, data engineering, and detection engineering, the company aims to commoditize security data infrastructure and establish industry-standard semantic layers for security operations. ziggiz serves cybersecurity teams, SOC operations, hunt teams, investigation units, and security architecture organizations.

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, MLflow, and Unity Catalog.