Some projects we can talk about publicly. Client names changed where they prefer it. Results include the caveats.
Unified patient data across 12 legacy systems. Reduced duplicate records by 73%—not the 89% we projected, but enough to materially reduce medication errors.
Built an ML-powered routing system that reduced fleet fuel costs by 18%. Took longer than planned because integrating with their dispatch system was harder than scoped.
Migrated a legacy insurance platform to AWS. Zero customer-facing downtime, though we had three internal incidents during the parallel-running period.
Built a custom e-commerce platform for a beverage distributor cooperative. Revenue grew 8x in 14 months—slower than projected, partly due to shipping complexity we underestimated.
Added AI-powered candidate matching to an existing staffing platform. Cut time-to-match from 12 days to 5.4 days. The hard part was getting recruiters to trust the recommendations.
Implemented an IoT sensor network and ML pipeline that reduced unplanned downtime by 62%. Getting sensor data reliable was harder than the actual ML.
Tell us what you're building. If it seems like a fit, we'll send over some relevant experience and set up a call.
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