Fleak acts as an In-Motion Data Orchestrator, automatically standardizing streams, enriching them, and routing them reliably to analytics, enabling zero-friction system integration.
Global Air Cargo Leader Accelerates Data Integration
The Pipeline Complexity Tax
For a mission-critical logistics platform, the path to building AI-native applications requiresd consolidating their diverse data assets. However, the manual, complex process of managing data pipelines created a massive operational drag and financial liabilities.
This complexity created three critical constraints:
AI Blockage: The most time-consuming and difficult step was achieving a normalized form for the data store. This is the necessary foundation for building AI applications.
Talent Divergence: Engineering capacity was stuck performing low-value work, manually managing approximately 200 individual data pipelines (modules) and troubleshooting issues (SEV1 issues require resolution within a couple of hours).
Future Roadblock: Reliance on existing infrastructure like IBM MQ limits connectivity, requiring a migration to open-source alternatives like Kafka to prevent vendor lock-in.
AI-Native Data Fabric
Fleak deployed an AI-Native Data Fabric—an Intelligence Upgrade—that automates the entire data integration and semantic translation layer. This eliminated the operational bottlenecks, allowing client engineers to focus entirely on advanced analytics and AI.
Fleak delivered Hyperspeed Automation through core components:
Zero-Friction Engine (AI-Powered Logic): Fleak automates all data integration, handling connections, data formats, and complex mapping logic. This allows client engineers to rapidly implement and enrich new data streams.
Production Management: Pipelines are "set and forget" , with self-healing mechanisms and automated notifications for any detected errors.
Data Velocity & Cost Consolidation: Consolidating disparate data processes into a single automated fabric removed a major operational liability and reduced manual labor costs.
The Multiplier Effect
By shifting the integration burden to Fleak, the client immediately unlocked engineering capacity for its strategic goals:
Strategic KPI | Resulting Impact |
Talent Shift | Engineering efforts shifted from low-value data integrations and maintenance to high-value AI/Data Science applications. |
AI Data Foundation | Data is immediately normalized, accelerating the timeline to build AI-native applications on Databricks Delta Lake. |
Pipeline Acceleration | Time spent on core data enrichment (finding source, building logic) is reduced to < 1 week. |
Reduced Outsourcing | Automating integration logic removes the need for costly external contractors and manual labor. |
Turn Infrastructure into a Revenue Engine
"The core challenge is identifying all the data sources and getting them into a normalized form for our human analysts and AI agents. If a solution can automate this process, allowing us to implement this really quickly, then that is definitely a no-brainer."
— Chief Data Officer, Global Air Freight Services (Attribution withheld per confidentiality agreement)
