CaseStudies

Manual claim validation with 4–6 day average turnaround

NLP-based claim summarizer and fraud pattern detector using document AI

• 78% faster claims processing
• ₹1.2 Cr saved annually via fraud detection automation

Legacy CRM lacked mobility and offline sync

Built Progressive Web App with agent activity tracking and voice logging AI

• 60% more claims closed per week
• 25% increase in active agent participation

High policy lapse rates

Machine Learning churn prediction model integrated into CRM

• 35% drop in lapse rates
• 15% upsell conversion boost

Manual underwriting file processing

Automated underwriting file extraction & classification

• 50% less manual QA overhead

Fragmented medical datasets across 7 hospitals

FHIR-compliant data unification pipeline with anomaly detection

• 3× faster data access
• Enabled AI diagnostics interoperability

Time-consuming manual MRI report creation

Computer vision model auto-detecting anomalies in MRI scans

• 90% diagnostic precision
• 50% less report creation time

High call center load for patient queries

Multilingual conversational AI for pre-op and post-op guidance

• 72% drop in call center load
• Higher patient satisfaction index

Manual prescription checks

Trained transformer-based NER to detect contraindications from prescriptions

• Automated 85% of manual checks by pharmacists

Low cart conversion rates

Collaborative filtering & context-based AI recommender integrated into storefront

• 31% higher average order value
• 22% increase in repeat customers

Manual pricing unable to compete effectively

Automated price adjustment based on competition & stock levels

• ₹2.8 Cr additional revenue in one quarter

High cart abandonment rates

Chat sentiment & purchase probability scoring using fine-tuned LLM

• 18% reduction in abandoned carts

Slow and error-prone inventory audits

Edge camera analytics for SKU count & movement optimization

• 44% faster inventory audit cycle

Reactive maintenance increased downtime

IoT + ML forecasting of machine failure

• 40% drop in unscheduled downtime
• 15% reduction in operational cost

Limited visibility into plant processes

Real-time simulation of plant processes using live sensor data

• 65% increase in throughput visibility

Manual quality control bottlenecks

YOLOv8 computer vision for automated defect detection

• 99% defect detection accuracy
• 70% faster quality control

Inefficient maintenance order dispatch

RPA bots dispatching maintenance orders based on sensor triggers

• 30% better SLA adherence

Frequent stock-outs and overstock

AI forecasting engine trained on 2 years of sales & weather data

• 92% accuracy
• Reduced stock-outs by 37%

Slow territory decision-making

Centralized Power BI dashboard with auto-refresh APIs

• 3× faster territory decision-making

Low campaign engagement

Built omnichannel automation using RevinoFlow + WhatsApp + Email triggers

• 42% campaign engagement uplift

Time-consuming manual property appraisals

AI valuation & predictive rent modeling

• Reduced manual appraisals from 5 hrs → 15 mins

Slow project audits

Site photo analytics using drone imagery + segmentation AI

• 28% faster project audits
• 100% visual record traceability

Slow lead closure process

Automated lead assignment + follow-up voice bot

• 50% faster lead closure time

High fleet operational costs

Data ingestion system processing 20k+ signals per second

• Reduced fleet cost by 25%

High insurance claim ratios

ML model predicting driver safety risk for insurers

• 85% precision
• Lowered claim ratios

Unpredictable battery maintenance

IoT sensors + ML regression on temperature/current data

• Improved predictive maintenance planning

Low student engagement

AI-based content recommendation & student analytics

• 45% better engagement
• 33% grade improvement

Time-consuming oral exam grading

STT-based oral exam grading automation

• Saved 900+ faculty hours/semester

High dropout rates

Data pipeline for tracking dropout patterns

• 28% improvement in retention

High churn rates among subscribers

AI model predicting churn based on usage heatmaps

• 40% increase in renewals

High manual DevOps overhead

Automated provisioning and monitoring using Terraform + Prometheus

• Reduced manual DevOps tasks by 65%

Slow support response times

Knowledge graph-based support assistant integrated with CRM

• 3× faster support responses

High false positive rates in security alerts

AI-powered anomaly detection and automated ticket triage

• 80% fewer false positives
• 5× faster incident resolution

Undetected security breaches

Behavior modeling using unsupervised learning

• 90% reduction in undetected breaches

Time-consuming compliance audits

Real-time monitoring dashboard for ISO, GDPR, SOC2 readiness

• Saved 200+ audit hours annually

High cloud infrastructure costs

ML-based cost recommendation engine across AWS/Azure

• 32% cost reduction

Traffic spikes causing downtime

Terraform, AWS ECS, Grafana alerts

• 99.99% uptime with dynamic traffic handling

Security vulnerabilities in containers

CI/CD-integrated image vulnerability scanner

• Reduced risk exposure by 76%

Low customer satisfaction

AI voice analytics interpreting sentiment during calls

• Improved satisfaction by 24%

Low conversion rates

NLP-driven dynamic landing page builder

• 38% higher conversion

Slow campaign setup process

RevinoFlow + HubSpot API + Gemini NLU

• Cut campaign setup time from 2 days → 3 hours

Unpredictable power consumption peaks

AI model predicting power consumption peaks

• 97% prediction accuracy
• ₹4.1 Cr annual savings

Suboptimal solar generation efficiency

Time-series ML models forecasting solar yield

• 22% increase in generation efficiency

Equipment failures causing outages

Transformer sensor data + anomaly AI

• Prevented 12 potential failures in 6 months

High fuel costs and slow delivery

AI-based dynamic routing using traffic + order data

• 18% fuel savings
• 20% faster delivery

Slow item retrieval process

RPA controlling inventory scanning robots

• 45% faster item retrieval

Inaccurate freight cost estimation

ML regression for price estimation per route

• 30% better cost accuracy

Reactive network maintenance

AI detects anomalies in real-time log streams

• 80% proactive maintenance success

Low viewer engagement on OTT platform

Deep-learning viewer profiling for OTT

• 2× watch-time per user

High customer churn

Personalized LLM-based customer retention conversations

• 28% reduced churn

Slow grievance processing

Multilingual NLP engine analyzing grievance text

• 65% faster issue triage

Slow approval processes

End-to-end digitization of approval pipelines

• Reduced turnaround by 70%

Uncertain policy outcomes

Predictive modeling on socio-economic datasets

• Helped decision-makers simulate 12 policy outcomes