Case Studies

Real projects. Real results. From startups to Fortune 500 companies.

Concrete examples of data challenges solved, from quick wins to multi-month transformations

Quick Wins1 month

Sales Can't Find Contacts, Emails Keep Bouncing

Marketing

Sales can't find contacts. Emails bounce. Same customer shows up 5 times. We cleaned 60% duplicates and ended the data entry chaos.

Key Results:

  • Can actually trust your CRM data again
  • Email campaigns reach real people (35% better deliverability)
  • Sales team stops wasting time hunting for info
Data QualityCRMQuick Win
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Quick Wins1 month planning

Can't Tell Which Projects Are Profitable Until They're Done

Construction

Don't know which projects make money until they're done. Can't forecast capacity. Estimates are guesswork. We created a clear 18-month roadmap.

Key Results:

  • Clear plan from $50M to $100M revenue
  • Started tracking profitability immediately
  • Identified quick wins generating ROI in first 90 days
StrategyRoadmapPhased Implementation
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Core Builds6 weeks

Stripe Says One Number, Dashboard Says Another

SaaS

Leadership meetings start with arguing about which metrics are right. Stripe says one thing, your dashboard another. We unified 8 tools.

Key Results:

  • Everyone finally looks at the same numbers
  • Stopped wasting 15 hrs/week compiling reports
  • Leadership makes decisions with confidence
Data IntegrationAnalyticsSaaS Metrics
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Core Builds2 months

Don't Track NPS, Don't Know Who the Detractors Are

Professional Services

You send one-off surveys that no one responds to. Don't know your Promoters from your Detractors. Customer sentiment is a black box. We built automated NPS tracking.

Key Results:

  • NPS Score: 42 → 58 in 6 months
  • Identify Detractors before they churn
  • Promoters now give referrals proactively
Customer AnalyticsNPSAutomation
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Platform Builds4 months

Processing 70M Records Takes 4+ Hours, Can't Scale

Automotive

Processing 70M+ records takes 4+ hours. Cloud costs growing faster than revenue. Can't add new data sources without breaking things.

Key Results:

  • Processing time: 4 hours → 90 minutes
  • Cut infrastructure costs 60%
  • Can actually scale without everything falling apart
Data EngineeringPerformance OptimizationCost Reduction
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Platform Builds5 months

Queries Take Hours, Business Team Waits Days for Reports

Financial Services

On-premise system can't handle data volume. Queries take hours. Only IT accesses data. Business users wait days for reports.

Key Results:

  • Queries 85% faster (hours → minutes)
  • 200+ business users now self-serve
  • Finally have a system that can scale
Cloud MigrationData WarehousingLegacy Modernization
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Platform Builds6 months

Models Sit in Notebooks for Weeks Before Production

Marketing & Advertising

Models sit in notebooks for weeks before production. Every client needs custom infrastructure. Data scientists do DevOps instead of data science.

Key Results:

  • Models deploy in hours, not weeks
  • Scaled to 20+ Fortune 500 clients
  • Data scientists actually do data science now
Machine LearningData PlatformReal-time Processing
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