Manufacturing sales teams are drowning in data while starving for insights—Supplyco built an AI sales intelligence platform that transforms 100,000+ heterogeneous data streams into real-time buyer intent alerts that save reps 10 hours per week.
Manufacturing sales teams are drowning in data while starving for insights. Supplyco cracked this challenge by building an AI sales intelligence platform that processes over 100,000 manufacturing data streams from government contracts to social media signals, delivering real-time buyer intent alerts that save sales reps 10 hours per week.
In this deep dive, Supplyco's CTO Claudia Richoux, will show how they use Dagster to transform heterogeneous data chaos into reliable AI insights. We'll explore their DAG architecture, discuss how they maintain 99.99% uptime while processing everything from UCC liens to building permits, and demonstrate why treating data like code enabled them to ship with confidence while scaling their platform.
Key Takeaways:
- See Supplyco's actual DAG processing 100K+ manufacturing intelligence streams
- Learn how asset-centric architecture simplified their complex data transformations
- Discover how built-in observability prevents outages in business-critical AI pipelines
- Understand how modern developer experience accelerated their time-to-market
Perfect for data engineers supporting AI/ML workloads, platform teams managing complex data sources, and anyone building real-time intelligence systems.
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Manufacturing sales teams are drowning in data while starving for insights—Supplyco built an AI sales intelligence platform that transforms 100,000+ heterogeneous data streams into real-time buyer intent alerts that save reps 10 hours per week.
Manufacturing sales teams are drowning in data while starving for insights. Supplyco cracked this challenge by building an AI sales intelligence platform that processes over 100,000 manufacturing data streams from government contracts to social media signals, delivering real-time buyer intent alerts that save sales reps 10 hours per week.
In this deep dive, Supplyco's CTO Claudia Richoux, will show how they use Dagster to transform heterogeneous data chaos into reliable AI insights. We'll explore their DAG architecture, discuss how they maintain 99.99% uptime while processing everything from UCC liens to building permits, and demonstrate why treating data like code enabled them to ship with confidence while scaling their platform.
Key Takeaways:
- See Supplyco's actual DAG processing 100K+ manufacturing intelligence streams
- Learn how asset-centric architecture simplified their complex data transformations
- Discover how built-in observability prevents outages in business-critical AI pipelines
- Understand how modern developer experience accelerated their time-to-market
Perfect for data engineers supporting AI/ML workloads, platform teams managing complex data sources, and anyone building real-time intelligence systems.
