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Case Studies

Built, shipped, and delivering value

Real projects where we have helped businesses integrate AI into their operations. Client privacy is a priority -- many of our case studies are anonymized at the client's request.

Industry
Service
LegalPythonClaude AI (Sonnet)Claude AI (Opus)+2

Automating UCC Document Extraction and Classification

Mid-size Florida Law Firm

85%reduction in manual processing time

Paralegals spent 20+ hours per week manually extracting, reviewing, and classifying hundreds of UCC filings from a state database. Error rates were climbing as volume increased, and substantive legal work was being displaced by data entry.

The Solution

Built an end-to-end automated pipeline using Python for data extraction, Claude AI (Sonnet for initial classification, Opus for complex edge cases), and a custom web interface for paralegal review -- all deployed within the firm's existing Azure infrastructure.

Key Results

96.2%

classification accuracy on standard filings

45s

per-filing processing time, down from 12 minutes

0

compliance incidents in first 3 months

Timeline

6 weeks

Phases

4

Services
Custom AI DevelopmentData EngineeringWorkflow Automation
Technologies Used
PythonClaude AI (Sonnet)Claude AI (Opus)AzureCustom Web UI
RetailPythonTensorFlowRedis+2

AI-Powered Product Recommendation Engine

Series B E-commerce Platform

34%increase in average order value

A growing e-commerce platform relied on basic rule-based recommendations that failed to personalize at scale. Conversion rates on product pages had plateaued, and the existing system could not account for real-time browsing behavior or seasonal shifts in demand.

The Solution

Designed and deployed a custom recommendation engine combining collaborative filtering with LLM-powered contextual understanding. The system processes browsing patterns, purchase history, and product metadata in real time to surface relevant products across the entire customer journey.

Key Results

2.8x

improvement in recommendation click-through rate

18%

uplift in repeat purchase rate within 30 days

<200ms

recommendation generation latency

Timeline

10 weeks

Phases

5

Services
Custom AI DevelopmentFull-Stack Web & SaaSData Engineering
Technologies Used
PythonTensorFlowRedisNext.jsAWS
HealthcarePythonAzurePostgreSQL+2

Unified Patient Data Pipeline with AI Classification

Regional Healthcare Network

60%reduction in patient intake processing time

Patient data was fragmented across three separate EHR systems, two legacy databases, and manual spreadsheet processes. Clinical teams spent hours reconciling records, and intake classification was inconsistent, causing delays in care routing.

The Solution

Built a unified data pipeline consolidating all patient data sources into a single, queryable system. Integrated an AI classification layer that automatically triages incoming patient records by urgency, specialty, and required documentation -- routing cases to the appropriate care team in real time.

Key Results

93%

accuracy in automated case classification

4hrs

saved daily across the clinical operations team

100%

HIPAA-compliant architecture

Timeline

12 weeks

Phases

6

Services
Data EngineeringCustom AI DevelopmentWorkflow Automation
Technologies Used
PythonAzurePostgreSQLNext.jsClaude AI
TechnologyNext.jsTypeScriptPostgreSQL+2

AI-Powered Analytics Dashboard for SaaS Metrics

Seed-Stage SaaS Startup

3xfaster decision-making on key metrics

A growing SaaS company lacked visibility into key business metrics. Their data lived in Stripe, Intercom, and a custom PostgreSQL database with no unified reporting. The founding team was making decisions on gut feeling rather than data.

The Solution

Designed and built a full-stack analytics dashboard that consolidates data from all business-critical sources. An AI layer surfaces anomalies, generates plain-language trend summaries, and proactively alerts the team to churn risk and expansion opportunities.

Key Results

22%

reduction in involuntary churn from early detection

$140K

in expansion revenue identified in first quarter

Real-time

unified view across all data sources

Timeline

8 weeks

Phases

4

Services
Full-Stack Web & SaaSCustom AI DevelopmentData Engineering
Technologies Used
Next.jsTypeScriptPostgreSQLStripe APIClaude AI
InsurancePythonAzureAutomation

Claims Email Routing Automation

National Insurance Provider

87%reduction in manual effort

Incoming claims emails were manually triaged by a team of adjusters who spent 15+ hours per week reading, categorizing, and forwarding messages to the correct department. Misrouted claims caused delays, duplicate work, and frustrated policyholders.

The Solution

Deployed an AI-driven classification pipeline that reads incoming claims emails, extracts key details (policy number, claim type, urgency), and automatically routes them to the appropriate claims team -- reducing the triage cycle from hours to minutes.

Key Results

94%

routing accuracy on first pass

12min

average time-to-assignment, down from 4 hours

30%

faster average claim resolution time

Timeline

5 weeks

Phases

3

Services
Workflow AutomationCustom AI Development
Technologies Used
PythonAzureAutomation

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