Industry: Marketing Technology / Advertising
Location: United States
Snowflake Product Categories Used: [Analytics, AI, Data Engineering]
Turning Consumer Signals into Privacy-Safe Intelligence at Scale
Intuizi is a secure foundation model for human derived signals and audience intelligence platform that transforms consented, de-identified consumer signals into actionable insights for marketers, brands, and AI-driven analytics teams. The platform powers segmentation, measurement, and real-time activation—all while maintaining strict privacy compliance.
"Intuizi processes 680 billion de-identified consumer signals monthly" or "The platform serves hundreds brands and agencies globally" - Ron Donaire, CEO, Intuizi
As demand for privacy-safe marketing intelligence grew, so did Intuizi's data. The company's Parquet-based data lake expanded to multi-petabyte scale, and with that growth came a familiar challenge: how to keep analytics fast, costs predictable, and infrastructure flexible—without rebuilding everything from scratch.
The Challenge: Scaling Analytics Without Scaling Costs
Intuizi built its data lake on Snowflake, which served as the analytical engine powering marketing AI and audience intelligence workloads. But as datasets grew larger and more complex, cracks started to show in the underlying storage infrastructure.
The problems compounding:
- Query costs were rising as datasets scaled into petabytes
- Managing metadata across multiple systems (including AWS Glue) added operational overhead and introduced inconsistencies
- The team wanted to adopt modern table formats like Apache Iceberg but couldn't justify a disruptive migration
- Data engineering resources were increasingly spent on infrastructure maintenance rather than building new capabilities
"The partnership with Akave/Snowflake is a game-changer for our customers. By leveraging this modern, high-performance architecture, we've removed friction and accelerated our Core Storage for AI training. This means Intuizi can now deliver the actionable insights our clients need to power their segmentation, measurement, and AI initiatives with greater value.”
Ron Donaire, CEO, Intuizi
Intuizi needed a way to modernize its data lake architecture, specifically for Snowflake workloads, without disrupting the pipelines, catalogs, and downstream models already in production.
The Solution: Snowflake + Akave's Iceberg-Optimized Storage Layer
Intuizi integrated Snowflake with Akave Cloud, an enterprise-grade, S3-compatible storage platform with native support for Apache Iceberg and Snowflake external tables.
The integration gave Intuizi an immediate path to modernization:
- Snowflake remained the core analytical platform, powering all marketing AI and audience intelligence workloads
- Akave provided the storage layer, delivering Iceberg-optimized infrastructure with predictable economics and zero egress fees
- Existing pipelines stayed intact—Parquet layouts, bucket structures, and catalogs worked without changes
Because Akave's API is S3-compatible and Snowflake-qualified, the transition required no reformatting, no pipeline redesign, and no changes to how data was ingested or queried.
How It Works: Iceberg on Akave, Queried by Snowflake
A key benefit for Intuizi was the combination of Snowflake's external table capabilities with Akave's native Apache Iceberg support.
The architecture:
- Intuizi's existing Parquet data was copied into Akave using standard S3 tooling (Rclone, AWS CLI)
- Akave converted large Parquet collections into Iceberg tables without rewriting files
- Snowflake external tables were pointed at Iceberg datasets stored on Akave
- Snowflake queries gained access to modern Iceberg metadata—enabling faster query planning and better partition pruning
This gave Intuizi a modern lakehouse architecture with Snowflake as the compute layer and Akave as the Iceberg-optimized storage layer—without a disruptive migration.
What this enabled:
- Preserved existing bucket structure and Parquet partitioning (country, day, provider)
- Snowflake external tables over Iceberg datasets stored on Akave
- Faster metadata access for improved query planning
- Partition pruning on large, highly partitioned datasets
- Reduced unnecessary scans during analytics workloads
"Analytics turnaround time improved by 60%” - Ron Donaire, CEO, Intuizi
“Intelligence platforms, such as Intuizi benefit from Snowflake’s unique architecture that combines analytics and AI capabilities in the cloud and support for externally hosted Iceberg tables on Akave. That gave Snowflake customers the Iceberg metadata benefits without changing how their Parquet data is organized”. Stefaan Vervaet, CEO & Cofounder, Akave
Results: 50% Cost Reduction, 50% Faster Analytics
With Snowflake querying Iceberg-organized data stored on Akave, Intuizi achieved measurable improvements across cost, performance, and flexibility.
Cost Efficiency
- >50% reduction in storage costs compared to previous cloud infrastructure
- Zero egress fees for sharing data with downstream systems and customers
- Ability to align compute spend with the most appropriate engine
Performance
- ~50% faster analytics on Iceberg-backed datasets vs. non-Iceberg equivalents
- Improved metadata and partition handling for Snowflake queries
- Consistent, reliable performance on large datasets—aligned with Intuizi's internal benchmarks
Flexibility
- Snowflake continues as the core analytics and AI platform
- Akave provides a unified Iceberg-based storage layer that can also serve other engines if needed
- Modernized architecture achieved with no rearchitecture of existing pipelines
By leveraging this modern, high-performance architecture, this translates directly into quicker time-to-product, more immediate decision-making, and the ability to drive business outcomes at a speed that simply wasn't possible before." - Ron Donaire, CEO, Intuizi
What's Next: Expanding AI Workloads on Snowflake + Akave
With a modernized data lake architecture in place, Intuizi is positioned to expand its use of Snowflake for AI-driven analytics and new data products.
- Expanding AI/ML workloads on Snowflake Cortex
- Building new data products for customers
- Enabling multi-engine access for specific workloads
- Scaling to new data sources or geographies
'Now that our storage layer is a competitive advantage, we can focus on what matters—building better frontier models and products for our customers. Snowflake and Akave give us the foundation to scale.' Ron Donaire, CEO, Intuizi
About Intuizi
Intuizi is a U.S.-based foundation model for human derived signals data and audience intelligence platform. It ingests consented, de-identified consumer signals and transforms them into privacy-safe insights for financial teams, marketers, brands, and AI-driven analytics teams. Intuizi does not store raw PII and focuses on compliant, high-value use of data for activation and measurement.
About Akave
Akave Cloud is an enterprise-grade, distributed and scalable object storage designed for large-scale datasets in AI, analytics, and enterprise pipelines. It offers S3 object compatibility, cryptographic verifiability, immutable audit trails, and SDKs for agentic agents; all with zero egress fees and no vendor lock-in saving up to 80% on storage costs vs. hyperscalers.