Case Studies

Deep Dives Into Our Best Work

Six detailed case studies showing exactly how we tackled complex challenges and delivered measurable business outcomes.

Healthcare SaaSCase Study #01

Vitalora

From fragmented data to $2M ARR in 6 months

Next.jsNestJSPostgreSQLRedisAWSHL7 FHIRStripe

The Challenge

A regional hospital network needed to consolidate patient data from 12 legacy systems, achieve HIPAA compliance before a regulatory audit, and give care coordinators real-time visibility across departments — all within 6 months and without disrupting ongoing operations.

Our Solution

We architected a multi-tenant SaaS platform with row-level security and field-level encryption for PHI data. HL7 FHIR APIs integrated with existing EMR systems. A real-time care coordination workflow engine automated routine handoffs. HIPAA audit logging was baked in at the data layer, not bolted on.

$2M ARR
Achieved in 6 months
150
Enterprise customers
23%
Readmission reduction

ROI Summary

14x ROI in year one based on patient readmission cost savings

"Ace Code Lab delivered a HIPAA-compliant platform that passed our security audit with zero findings. The speed and quality were exceptional."

CTO, Vitalora Health Systems

FintechCase Study #02

Finsyte Analytics

Fraud detection that saved $2.4M in Q1

ReactNode.jsApache KafkaApache FlinkPythonTensorFlowPostgreSQLAWS

The Challenge

A fintech startup processing $50M+ in daily transactions was losing 3.2% to fraud. Their rule-based fraud detection had a 40% false positive rate, blocking legitimate customers. Manual transaction review was creating 2-hour hold times during peak hours.

Our Solution

We built a real-time streaming pipeline on Apache Kafka and Flink processing every transaction in under 100ms. An ML anomaly detection model trained on 18 months of transaction history reduced false positives by 85% while catching 94% of fraudulent transactions. A live analytics dashboard gave the risk team full observability.

67%
Fraud loss reduction
<100ms
Detection latency
85%
False positive reduction

ROI Summary

Platform paid for itself in 43 days based on fraud losses prevented

"The ML model outperformed our previous vendor's system on every metric within the first month of production operation."

Head of Risk, Finsyte Technologies

Education TechnologyCase Study #03

Learnova LMS

500,000 students. 42% better completion rates.

Next.jsNode.jsPostgreSQLRedisKubernetesWebRTCPythonTensorFlow

The Challenge

200 partner universities were using 15 different LMS platforms, making data consolidation impossible and preventing any consortium-wide analytics. Course completion rates averaged 41%, and the lack of adaptive learning meant high-performing students were bored while struggling students fell behind.

Our Solution

A microservices architecture on Kubernetes handles traffic spikes during exam periods (50,000 concurrent users tested). An AI recommendation engine delivers personalized learning paths based on assessment performance and engagement signals. WebRTC virtual classrooms with collaborative whiteboards replaced third-party tools at a fraction of the cost.

500K
Active students
42%
Completion rate improvement
55%
Support cost reduction

ROI Summary

$3.2M annual savings across the consortium from consolidated tooling

"We replaced 15 tools with one. Our IT team went from managing integrations to driving innovation."

CIO, Learnova Education Corp

Logistics & Supply ChainCase Study #04

Trackvex Platform

2M daily shipments. 18% cost reduction.

ReactNestJSPostgreSQLMongoDBKafkaPythonMLAWSIoT

The Challenge

Post-acquisition sprawl left a global logistics company with 12 separate tracking systems across 45 countries. On-time delivery rates had fallen to 71%. Customers were churning due to poor visibility, and manual route optimization was leaving significant cost savings on the table.

Our Solution

We implemented the Strangler Fig pattern to migrate 200,000 users from legacy systems with zero downtime over 11 months. IoT integrations brought real-time GPS tracking to every vehicle. An ML route optimization engine using historical traffic and weather data cut average delivery distances by 12%. A customer portal reduced inbound calls by 60%.

18%
Delivery cost reduction
94%
On-time delivery rate
0
Minutes of downtime during migration

ROI Summary

$18M annual savings from route optimization and reduced customer support costs

"We went from 71% on-time delivery to 94% in 4 months. Our NPS went from 22 to 61."

COO, Trackvex Freight International

E-commerceCase Study #05

Shoplynk AI

Cart abandonment down 31%. AOV up 28%.

Next.jsPythonPyTorchElasticsearchRedisPostgreSQLStripeAWS

The Challenge

A $200M GMV retail platform had a 72% cart abandonment rate and mediocre search relevance. Static pricing left revenue on the table during high-demand periods. Product recommendations were rule-based and generic, resulting in low click-through rates and missed cross-sell opportunities.

Our Solution

We replaced the rule-based recommendation engine with a hybrid collaborative filtering and content-based model updating in real-time. A dynamic pricing engine monitors competitor prices and demand signals, adjusting prices within merchant-set guardrails. Semantic search using text embeddings replaced keyword matching, dramatically improving search relevance for long-tail queries.

28%
Average order value increase
3.4x
Search-to-purchase conversion
31%
Cart abandonment reduction

ROI Summary

$44M additional annual revenue attributed to personalization and dynamic pricing

"The recommendation engine alone generates $3M+ monthly in revenue we would have left on the table."

VP Engineering, Shoplynk Commerce Group

ManufacturingCase Study #06

Factorion OS

$2.8M annual savings. 44% less downtime.

ReactPythonTensorFlowMQTTInfluxDBPostgreSQLKafkaAzure IoT

The Challenge

Unplanned machine downtime was costing a precision manufacturer $2.8M annually. With 800+ machines across 15 factory floors, maintenance was reactive — teams learned of failures when production stopped. Quality defect rates of 3.2% were costing another $1.2M per year in waste and rework.

Our Solution

We deployed an IoT data platform ingesting vibration, temperature, and current draw data from 800+ machines at 100Hz. An LSTM neural network trained on 3 years of sensor history predicts failure events 72 hours in advance with 89% accuracy. A real-time operations dashboard gives plant managers facility-wide visibility and one-click maintenance ticket creation.

44%
Unplanned downtime reduction
0.8%
Defect rate (was 3.2%)
$4M
Annual cost savings

ROI Summary

8-month full payback period on total project investment

"We went from discovering failures when production stopped to preventing them 72 hours in advance. This changed how we run our facilities."

Plant Director, Factorion Precision Works

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