Byzfunder: A Second Opinion on Every Classification with Jev on MotherDuck
- Cross-checked rule-labeled bank transactions with AI, inside MotherDuck
- Flagged the gaps for analysts to fix in the rules
- Running on day one, with no new pipeline to build
Case Studies
Ducks That Lead the Way
Explore all case studies
Hazel: Building an AI Co-Worker for E-Commerce on MotherDuck
- Hundreds of dbt models on a central MotherDuck warehouse
- Hypertenant per-customer databases via CTAS for isolation
- Local DuckDB for dev, MotherDuck for prod
GoodShip: Building an Analytics Agent for Global Logistics
- Analytics agent built on MotherDuck's remote MCP in under a week
- Hypertenancy model for full data isolation
- Sub-second queries where Postgres timed out
Building a Data Platform for the Agent Era at AheadComputing
- 74% of engineers onboarded onto MotherDuck within the first weeks of rollout
- 3 months → 1.5 hours for dashboard requests, replaced by self-service Dives
- 1 week to production
Together AI: Scaling a Data Platform while Scaling the Company
- 128 unique Hex users across product teams, C-suite, and board
- 40 read scaling replicas supporting concurrent analytics
- AI agent workloads run freely without cost spikes or rate-limiting
Cut dbt runtime from 2 hours to 7 minutes and found top-notch support
- Deployed customer-facing embedded analytics with Omni
- Replaced Snowflake evaluation with simpler auth and managed infrastructure
Gets sub-second insights enabling same-day claims filing & 95%+ acceptance
- Sub-second query performance on healthcare data that other warehouses took multiple seconds to process
- Same-day claims filing for 80-90% of appointments (previously took up to a month)
- 95%+ claims acceptance rate through rapid iteration on rejection patterns
Saves $20k per month with hypertenancy architecture on MotherDuck
- Saves $20k on Amazon Athena and Glue spend
- Achieves per-customer compute isolation and granular scaling
- Runs 14x faster queries on customer-facing datasets
Gets answers for business users with the MotherDuck MCP
- Cut batch CSV processing times from 6 hours to 6 minutes
- Built 20x faster rule generation for coding medical procedures
Cuts analytics costs by 65% while gaining SQL expressibility
- Moved analytics off of SingleStore, saving 65% on analytics costs
- Transformed analytics workflow and ML model development with MotherDuck
Accelerates retail analytics while avoiding expensive BI tools
- Moved analytics off production Postgres, enabling customer-facing reports
- Deferred thousands monthly on Tableau by improving data architecture
Reduced costs while empowering users to find their own answers
- Migrated from Postgres to MotherDuck, eliminating overnight analytics queries
- Empowered non-technical colleagues to explore data independently with the MotherDuck UI
Turns costly analytics blocker into go-to-market enabler
- Cut data pipeline processing time from 24+ hours to under 1 hour
- Enabled per-tenant data retention flexibility, letting customers choose 5-180 days without infrastructure changes
Accelerates same-day delivery analysis and decisions
- Replaced costly, high-maintenance Redshift setup with a serverless architecture
- Transformed daily operations via instant drill-downs in Looker for faster issue resolution and deeper analysis
Improved analytics query performance from minutes to seconds
- Chose MotherDuck after finding ClickHouse, Snowflake, Databricks, BigQuery too complex and expensive
- Enabled lifetime course analytics for 16,000+ courses after MongoDB queries proved impossible
Built a Data-First Investment Platform with MotherDuck and Omni
- Migrated from local DuckDB files to cloud infrastructure instantly with zero configuration changes
- Empowered non-technical investment analysts to explore complex data models without engineering bottlenecks
Reduced Analytics Pipeline from 24+ Hours to Under One Hour
- Unified analytics across MySQL, Postgres, and MongoDB data sources in one efficient warehouse
- Enabled complex time-series analysis on 150+ columns of IoT data at 10x lower cost
Transformed 8-Hour Financial Data Pipelines into 8-Minute Workflows
- Launched AI-powered financial agents using MotherDuck's performance to enable real-time data exploration
- Migrated from Postgres to achieve 60x faster pipeline execution for complex financial data
Achieved Interactive Browser Visualization of 18 Million Data Points
- Built a fully interactive data exploration app in just one hour
- Delivered sub-second query responses through hybrid local-cloud execution without managing any servers
Unlocked Lightning-Fast Analytics and New Customer Capabilities
- Reduced analytical query times from minutes to seconds while eliminating traditional data warehouse costs
- Enabled new browser-based data experiences impossible with Postgres or Snowflake alternatives