Lakehouse Dispatch &
Engineering Insights.
Deep architectural breakdowns, release changelogs, and practical guides on how Data Modulus provides customized, high-velocity environments for data engineers, data scientists, and AI/ML engineers.
The AI/ML Engineer's Playbook: End-to-End RAG Pipelines from Iceberg Tables to Vector Embeddings
Convert petabyte-scale Iceberg tables into production vector datasets, orchestrate embedding jobs on ephemeral Spark clusters, and deploy low-latency semantic search with zero warehouse egress tax.
Governed Ingestion & Dynamic Airflow DAGs: Solving Data Pipeline Chaos
Data teams waste hours writing boilerplate DAGs and debugging schema drift. Learn how 204 column transform functions and declarative technical contracts eliminate ETL maintenance.
Customized Polyglot Workspaces for Data Scientists: Interactive SQL, Python & Databricks dbutils
Instant collaborative notebooks with sub-second Trino SQL queries and complete native dbutils secrets compatibility—enabling zero-refactor migrations from Databricks.
Sovereign Cloud Economics: Dynamic Spark Clusters on EC2 & K8s with Real-Time Pod Cost Metering
Eliminate 300% warehouse compute markup. Deploy sovereign compute inside your own VPC or Kubernetes cluster with granular pod-level cost telemetry and monthly forecasting.
Ready to Empower Your Data, Science & AI Teams?
Explore Tesseract LakeOS in a personalized architecture session. We will size your EC2 or Kubernetes clusters, model your ETL pipelines, and show you RAG pipelines running directly on Iceberg.