Mosaic Relay Labs

Case Studies

Real work, real outcomes. Here's what we accomplished with teams across different industries.

Northline Freight Desk

A regional LTL carrier managing shipments across 12 states was losing operational visibility. Exception handling was manual and slow. Customer queries bounced between systems.

The Challenge

Northline's operations team tracked shipment events across three disconnected systems: a legacy TMS, a carrier network portal, and email. When exceptions occurred (missed pickups, delivery delays, damaged shipments), the team had no unified view. They'd spend 20-30 minutes per incident searching emails and logging into different portals to understand what happened and route to the right person.

What We Built

  • • Unified event data warehouse ingesting from TMS, carrier APIs, and email
  • • Automated exception detection and triage workflow
  • • Assignment rules routing exceptions to specialists
  • • Operations dashboard showing real-time status

Outcomes

  • ✓ 70% reduction in time spent on manual status chasing
  • ✓ 3x faster initial exception response and assignment
  • ✓ 92% accuracy in automated triage (down to 8% requiring manual review)
  • ✓ Improved customer satisfaction: Resolution time dropped from 6 hours to 2 hours average
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Project snapshot

Industry

Logistics & Transportation

Team Size

12 operations, 2 IT

Systems

TMS, 3PL APIs, email

Timeline

12 weeks design & build

Focus

Data Foundations, Operational Analytics, Automation

Hearth & Field Supply Co.

A regional B2B distributor struggled with fragmented inventory visibility, spreadsheet-based demand planning, and frequent stockouts on high-volume items.

The Challenge

Hearth & Field tracked inventory in a legacy ERP system, but purchasing decisions lived in spreadsheets maintained by different people. Sales data updated with a 24-hour lag. When demand surged, the team had no way to see it coming. They over-ordered slow movers and constantly ran out of fast movers. Finance spent 2-3 days every month just reconciling inventory counts.

What We Built

  • • Consolidated warehouse pulling inventory, sales, and purchasing data
  • • Demand-planning dashboard with 4-week forecasts
  • • Automated low-stock alerts and replenishment recommendations
  • • Daily inventory reconciliation reports

Outcomes

  • ✓ Eliminated 12 hours/week of manual spreadsheet work
  • ✓ 45% improvement in replenishment accuracy
  • ✓ Stockout rate cut in half on fast movers
  • ✓ $180K annual savings from reduced overstock and emergency orders
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Project snapshot

Industry

Wholesale Distribution

Team Size

8 purchasing, 4 finance

Systems

Legacy ERP, spreadsheets

Timeline

10 weeks design & build

Focus

Data Foundations, Operational Analytics

Cedar Point Advisory

A 50-person management consulting firm wanted to improve client delivery speed and consistency without adding headcount.

The Challenge

Every client engagement started with research: reviewing past work, compiling relevant case studies, building historical context. Consultants spent 8-12 hours per project doing detective work. Client documents (emails, RFPs, contracts) scattered across drives. There was no single source of truth about what the firm had learned from similar engagements.

What We Built

  • • Knowledge warehouse indexing past projects, proposals, and research
  • • AI-assisted document handler for client materials
  • • Retrieval system surfacing relevant precedents and insights
  • • Human-in-the-loop first-draft preparation with mandatory expert review

Outcomes

  • ✓ 65% reduction in research and first-draft preparation time
  • ✓ Faster project kickoff: Client meetings happening 5 days earlier on average
  • ✓ Better knowledge reuse: Consultants discovering relevant past work they didn't know existed
  • ✓ Consistent quality: Every project now has structured context and precedent review
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Project snapshot

Industry

Professional Services

Team Size

50 consultants, 2 operations

Systems

Google Workspace, various file stores

Timeline

16 weeks design & build

Focus

Data Foundations, AI Workflow Automation

Illustrative Project Outcomes: Results shown reflect specific project conditions including team engagement level, data quality, and implementation timeline. Your outcomes will depend on your unique operational context, data maturity, and implementation approach. We measure progress and adjust strategy based on evidence.

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Every industry has a "messy middle" where data lives nowhere and decisions are left to chance. Let's talk about what's possible for yours.

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