Case Studies
Real analytics and AI consulting outcomes across healthcare, financial services, manufacturing, education, and government. See what changed when we shipped it.
Data cleaning and labeling: 22 engagements
- We recovered $4.8M a year in misrouted claims by lifting member match accuracy from 75 to 94 of every 100 records, restarting three stalled ML pilots. , Express Scripts, Healthcare
- We improved patient data quality from 58 to 91 in 12 weeks, enabling a $3.2M population health management platform to move forward. , St. David's Medical Center, Healthcare
- We identified inconsistencies across six revenue metrics and created one certified ARR definition, resolving a $1.4M reporting gap between finance and sales. , Enterprise SaaS Company, Technology & SaaS
- Improved data accuracy in 12 city departments to recover $4.1M in federal grants lost to reporting errors. , City of San Antonio, Government
- We evaluated AI readiness in 8 program areas, uncovered $7.3M in automation potential, and created a detailed 24-month AI rollout plan. , Texas Health and Human Services, Government
- Implemented a data governance framework in 6 regional offices that cut FOIA response time from 34 to 8 days and stopped $1.2M in yearly compliance penalties. , U.S. Department of Transportation, Government
- Built a data governance framework for ticketing and fan records at 8 venues, stopping $940K in yearly revenue loss caused by duplicate entries. , Live Nation Regional Division, Gaming & Hospitality
- Automated call report preparation cut compliance labor from three weeks to two days and eliminated $680K in annual costs, resulting in zero MRAs in the next exam cycle. , Frost Bank, Financial Services
- We improved policy data quality from 61 to 94, unlocking $8.4M in AI underwriting projects that were stalled. , Employers Holdings Inc., Financial Services
- We built a deal pipeline data system in 12 weeks that cut report preparation from two days to 90 minutes and saved $420K in analyst costs annually. , Stephens Inc., Financial Services
- We merged 11 campus data warehouses into a single system, cutting infrastructure costs by $2.3 million annually and speeding report delivery from five days to same-day. , Texas A&M University System, Higher Education
- Built a unified customer data system across 8 channels to drive $4.2M in personalized sales revenue. , National Specialty Retailer, Retail & E-Commerce
- We cut 220 store reports down to 14 certified dashboards, saving $890K a year. , Regional Grocery Chain, Retail & E-Commerce
- We developed R&D portfolio analytics covering 8 programs to give the board a clear, consolidated view of pipeline value. , Clinical-Stage Biotech, Life Sciences
- We automated the pharmacovigilance data pipeline, cutting adverse event processing from 18 days to 4 hours. , Specialty Pharmaceutical Company, Life Sciences
- Built a reliable ESG data system that cut sustainability report prep time from 18 weeks to 3 weeks. , Investor-Owned Utility, Energy & Utilities
- Aligned ARR, NRR, and churn data across finance, product, and sales to resolve a $2.1M reporting gap for the board , Growth-Stage SaaS Platform, Technology & SaaS
- We cut duplicate vendor and material data and unblocked a stalled S/4HANA migration in 9 weeks, with the go-live date held. , Mid-Market Industrial Manufacturer (representative), Manufacturing
- We made inventory and customer data migration-ready in 7 weeks, before a go-live date was ever set. , Regional Wholesale Distributor (representative), Distribution & Logistics
- We made finance and supply chain master data audit-ready for S/4HANA in 12 weeks, with the first close on time. , Regional Healthcare System (representative), Healthcare
- We carried asset and reporting data through an S/4HANA migration with zero reporting blackout, in 16 weeks. , Mid-Market Energy & Utilities Company (representative), Energy & Utilities
- We rescued a stalled S/4HANA migration and brought it to a clean go-live in 5 months, with zero downtime. , Technology Hardware Company (representative), Technology & SaaS
Where the work sat
Work by capability
Sixty-four engagements, each recorded with the question it existed to answer, the situation it arrived in, and what the work produced. Filter by stage, industry or question type.
Sixty-four engagements and the question each one was answering.
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Every entry records the question the work existed to answer, the situation it arrived in, the roadmap that answered it, and what that produced. Filter by the stage the work sat in, by industry, or by the kind of question.
A question rarely turns into one kind of work, and the stage an engagement started in is usually not the stage the client expected it to. Select one to narrow the library.
Build is the largest of these because it is where clients arrive. Seven of sixty-four started at Assess, and every one of those seven cost less than the engagement the client came in asking for.
That ratio is the thing the first movement exists to change.
If one of those engagements reads like the situation you are in right now,
An hour, no charge, usually enough to say whether the thing you are about to commission is the thing you need.