Case Studies
Representative engagements showing how we've helped organizations build data platforms and practical automation.
Logistics
Shipment Exception Detection & AI Dispatch Summaries
Client: Northbridge Logistics
Regional logistics provider spent 40+ hours per week manually reviewing shipment exceptions and writing operational summaries.
Impact
78% reduction in manual review time; real-time exception detection enables faster operational response.
Retail
Inventory, Margin & Replenishment Data Platform
Client: Cornerstone Retail
Multi-location specialty retailer operated with siloed inventory, margin, and replenishment data across locations and business units.
Impact
Unified data platform eliminated manual reconciliation; 15% reduction in excess inventory through optimized replenishment.
Healthcare
Compliant Internal Document Routing & Knowledge System
Client: Meridian Health
Healthcare administration organization needed secure, compliant document routing and internal knowledge retrieval for clinical and administrative staff.
Impact
Implemented RAG-based knowledge system; 60% reduction in time-to-resolution for routine inquiries while maintaining compliance.
Northbridge Logistics
Logistics Industry
Shipment Exception Detection & AI Dispatch Summaries
The Challenge
Northbridge Logistics operates across 45 locations and processes 8,000+ shipments daily. Their operations team was spending 40+ hours per week manually reviewing exception reports (delays, missing scans, damaged shipments) and writing hand-summarized daily updates for dispatch and operations leadership.
This created delays in operational response and consumed time that should have been spent on strategy and customer relationships.
Our Approach
We built a real-time shipment data platform that ingested from their TMS, WMS, and scan-tracking systems into Snowflake. We implemented rule-based exception detection using dbt, and an AI summarization layer using LLM retrieval grounded in actual shipment data.
The system generates exception reports and daily dispatch summaries automatically, with human review controls and audit logging for compliance.
Technologies
Snowflake, dbt, Airflow, Fivetran, Python, OpenAI API, DBT test suite
Timeline
16 weeks from discovery to production
Impact
- 78% reduction in manual review time (32 hours/week saved)
- 95% improvement in exception detection accuracy
- Real-time alerting enables faster operational response
"The system identified a critical shipment delay before our customers even knew about it. That's the kind of visibility we needed but thought was impossible. Emberline made it real."
— VP Operations, Northbridge Logistics
Cornerstone Retail
Retail Industry
Inventory, Margin & Replenishment Data Platform
The Challenge
Cornerstone Retail operates 28 specialty stores across six states. Inventory, margin, and replenishment data lived in disconnected systems—POS, inventory management, accounting, vendor systems—each with its own version of truth.
Store managers couldn't see real-time inventory across locations. Replenishment was reactive and inefficient. Margin analysis required manual monthly reconciliation across four systems.
Our Approach
We designed a unified retail data platform on Snowflake, integrating point-of-sale, inventory, accounting, and vendor data via modern APIs and scheduled batch ingestion. We built a dimensional schema in dbt focused on product, location, and time dimensions.
Store managers got a Tableau dashboard showing real-time inventory, sales velocity, and margin by location and category. Inventory planners got automated replenishment recommendations.
Technologies
Snowflake, dbt, Fivetran, Tableau, Jupyter notebooks, Python
Timeline
20 weeks from discovery to production dashboards
Impact
- 15% reduction in excess inventory through optimized replenishment
- $520K in inventory working capital freed in year one
- Zero manual reconciliation hours (formerly 120/month)
"We went from making inventory decisions based on hunches to having real data. The dashboards show us exactly where the problems are. We're already planning where to expand based on this visibility."
— CFO, Cornerstone Retail
Meridian Health
Healthcare Industry
Compliant Internal Document Routing & Knowledge System
The Challenge
Meridian Health administers benefits, eligibility, and compliance operations for member organizations. Clinical and administrative staff needed quick answers to routine questions about policies, procedures, and compliance requirements—but answers were buried across 500+ PDFs and shared drives.
Staff spent significant time searching for documents or asking colleagues. HIPAA compliance required document access controls and audit logging.
Our Approach
We built a retrieval-augmented generation (RAG) system grounded in Meridian's actual policy and procedure documents. The system ingests PDFs with document versioning and ownership metadata, embeds them into a vector database, and provides an AI assistant interface with strict role-based access controls.
Every query is logged with user identity, response is grounded in actual documents, and staff can see the source documents. No AI hallucinations—only answers derived from Meridian's actual policies.
Technologies
LangChain, Pinecone, OpenAI API, Python, FastAPI, PostgreSQL, Role-based access controls
Timeline
12 weeks from discovery to internal beta
Impact
- 60% reduction in time-to-resolution for routine inquiries
- 100% HIPAA-compliant audit logging maintained
- 92% user satisfaction with answer accuracy
"We're skeptical of AI, but this system actually works. It pulls from our real policies, shows us the source documents, and staff can rely on it. This is AI built the right way for healthcare."
— Compliance Officer, Meridian Health
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