Datalinx AI Unveils Founding Team Including Amazon and Intuit Alumni, Joins Databricks AI Accelerator

Former Amazon and Intuit Executives Join Datalinx AI's Founding Team to Make Consumer Data Product-Ready

Datalinx AI unveiled its founding team, bringing in leaders from Amazon, Intuit, Oracle, and Unity to solve a familiar product problem: messy consumer data that slows delivery and blurs impact. Co-founders Nicole Landis Ferragonio (Chief Product Officer) and Alek Liskov (Chief AI Officer) join CEO Joe Luchs and CTO Jeff Collins to turn fragmented datasets into intelligence that products can actually use.

The focus is simple: remove data readiness bottlenecks so product, engineering, analytics, and marketing teams can ship faster with less risk and clearer outcomes.

Why this matters for product development

• Faster iteration: Cut the drag from data prep by automating exploration, transformation, enrichment, activation, and quality checks.
• Safer analytics: Build on privacy-safe patterns and clean-room workflows that expand access beyond data scientists without exposing raw data.
• Closer to the customer: Activate unified data across use cases-targeting, measurement, personalization-without retooling pipelines every sprint.
• Operational clarity: Treat data like a product with defined contracts, SLAs, and quality metrics aligned to product outcomes.

Who's joining-and what they bring

Nicole Landis Ferragonio, Chief Product Officer: Former Amazon product leader with a pivotal role in building Amazon Marketing Cloud. She expanded access beyond data teams, advanced privacy-safe analytics, and reshaped how advertisers use clean room tech-earning a U.S. patent. She started in strategy and operations and holds an MBA from NYU Stern.

Alek Liskov, Chief AI Officer: Former Director of AI and Data Product at Intuit, where he led AI-powered products and agents. Previously spent eight years at Verizon building enterprise data platforms and AI solutions across marketing, customer experience, and retail.

Both are based in New York and will scale the company alongside CEO Joe Luchs and CTO Jeff Collins.

Leadership perspective

"After a successful launch, we're thrilled to announce Nicole and Alek as co-founders to accelerate our vision. Their deep expertise in product, engineering, and AI, particularly within the adtech and martech space, will be invaluable as we continue to empower our customers to get the most value out of their data," said Luchs. "Our founding team is committed to helping customers move faster, compete smarter, and win in the AI era."

"I've seen firsthand how companies struggle to unlock the full potential of their data," said Ferragonio. "At Datalinx AI, we're tackling this challenge head-on with a product that makes data readiness simple and scalable. I'm excited to partner with Joe, Jeff, and Alek to enable businesses to transform their data into actionable intelligence that drives smarter decisions and measurable results."

Momentum: Databricks AI Accelerator selection

Datalinx AI was selected as one of five startups in the inaugural Databricks AI Accelerator Program, gaining access to up to $250,000 in investment capital and product/service credits, go-to-market support, technical advisors, executive sponsorship, and the Databricks VC Network. Learn more about Databricks here.

What Datalinx AI offers

Datalinx AI positions itself as an AI Data Refinery-turning raw consumer data into ready-to-use fuel for models and applications. The platform automates:

• Data exploration and profiling to reveal gaps, drift, and duplication
• Transformation and enrichment to standardize and add context
• Activation to push trusted data into downstream tools and workflows
• Quality management with ongoing monitoring and governance

For product teams, this means fewer custom pipelines, fewer data firefights, and a clearer line between data work and shipped value.

Practical next steps for PMs and tech leads

• Inventory your data sources and define "ready-to-use" criteria per use case (fields, freshness, latency, privacy level).
• Set data contracts for critical entities (customer, device, event) and track quality as you would uptime.
• Pilot one high-ROI flow (e.g., audience building or attribution) and measure cycle time, model lift, and issue rate.
• Adopt clean-room patterns for joint analytics while keeping raw data protected.
• Loop in Security and Legal early; standardize approvals so experiments don't stall.

About Datalinx AI

Datalinx AI is an AI Data Refinery that transforms raw consumer data into ready-to-use fuel for AI models and applications. By automating data exploration, transformation, enrichment, activation, and quality management, the company removes data readiness bottlenecks so marketing, analytics, data science, and engineering teams can move at the pace of AI innovation.

If you're equipping your product org for AI-first development, explore role-based learning paths at Complete AI Training.