Cenovix – Detailed Success Stories Across Industries

Transforming Retail Performance with AI & Predictive Analytics

Client Overview

A leading retail chain with over 50 stores across metro and tier-2 cities was struggling with:

Challenges Faced

Demand Forecasting
Stockouts during peak demand
Demand Forecasting
Stockouts during peak demand
Demand Forecasting
Stockouts during peak demand

These bottlenecks led to dwindling sales and missed revenue opportunities. These inefficiencies were leading to frequent stockouts, excess inventory holding costs, and declining customer retention.

Intellivista Ai Powered Solution

We deployed a full-stack data-driven solution using Python, Power BI, and AI algorithms:

Implementation Breakdown

Predictive Demand Forecasting
  • Time-series modeling with Python
  • Real-time stock trend monitoring
Customer Segmentation
  • K-Means clustering for demographic & behavioral analysis
  • Defined buyer personas for targeted engagement
Inventory Optimization
  • Intelligent reordering based on sales velocity
  • ABC classification & safety stock buffer design
Personalized Marketing
  • AI-powered recommendation engine
  • Dynamic email and in-app promotions based on user behavior
Visual Dashboards
  • Interactive Power BI dashboards for:
    • SKU performance
    • Store-level forecasting
    • Campaign impact analysis

How Did our Solution Help ?

  • Forecast Accuracy
    +30%

    improvement in demand prediction throughout AI models

  • Retention Boost
    +25%

    more repeat customers via target engagement 

  • Sales Conversion

    Personalised recommendations drive purchase intent 

  • Investorsy Waste

    Reduced overstocking & dead stock with smart reording 

Client Testimonial

With AI-driven insights and predictive analytics, we’ve turned our retail chaos into an efficient, customer-focused engine. The impact was immediate — and measurable.

Chetan Arora

Director

Spice Bazaar, Miami, USA

Streamlining Logistics Operations with AI & Predictive Insights

Client Overview

A major logistics and supply chain provider with operations across multiple regions faced:

Challenges Faced

Poor Route Optimization
Longer delivery times
No Real-Time Visibility
Lack of shipment traceability
Inefficient Warehouse Ops
Delayed order processing
Equipment Breakdowns
Sudden downtime & costly disruptions

These issues resulted in delivery delays, increased costs, and customer dissatisfaction.

Intellivista Ai Powered Solution

We deployed a full-stack data-driven solution using Python, Power BI, and AI algorithms:

Key Implementations

AI Route Optimization
  • Trained ML models for shortest-time pathing
  • Traffic pattern analysis and re-routing
Real-Time Shipment Tracking
  • Power BI dashboards integrated with GPS and ERP
  • Live status updates for all logistics nodes
Warehouse Intelligence
  • Heatmaps for order flow bottlenecks
  • Slotting analysis and inventory optimization
Predictive Maintenance
  • ML-driven anomaly detection for machines
  • Scheduled interventions before breakdowns

How Did our Solution Help ?

  • Delivery Time
    -40%

    Education in average delivery duration using AI-ruting

  • Warehouse Productivity
    +35%

    Efficiency from layout heatmaps and smart slotting

  • Downtime Risk

    Proactive maintenance avoided costly breakdowns

  • Real-Time Visibility

    Power BI dashboards enabled full shipment traceability 

Client Testimonial

The AI-led transformation enabled faster delivery, fewer breakdowns, and complete shipment visibility. Our operations have never been this streamlined.

Paragaon SCM Pvt Ltd

Healthcare & Life Sciences

Elevating Patient Outcomes with AI-Driven Clinical Insights

Client Overview

A leading hospital network serving thousands of patients monthly struggled with:

Challenges Faced

Disjointed Patient Records
Incomplete health history & misdiagnosis
No Risk Prediction Models
Reactive rather than proactive care
Manual Reporting Processes
High admin burden, delayed decisions

These challenges led to missed early health warnings, reporting inefficiencies, and high readmission rates.

Intellivista AI-Powered Healthcare Solution

Using Python, Power BI, and clinical data science, we delivered:

Implementation Breakdown

Predictive Patient Risk Modeling
  • ML models trained on patient vitals & history
  • Identified high-risk individuals early
Clinical Dashboards
  • Power BI dashboards for:
    • DPatient admissions
    • Disease risk stratification
    • Doctor workload management
Automated Reporting
  • Reduced manual reporting by over 80%
  • Monthly compliance, readmission, and occupancy reports generated automatically

Healthcare & Life Sciences Success Story

Problem Statement

Healthcare providers faced challenges managing patient data effectively, lacked predictive insights into patient health risks, and dealt with inofficient reporting processes

Resolution Provided

Created comprehensive clinical dashbsards, predictive patient risk models utilizing Python-based machine learring, and automated reporting solutions with Power BI

Impact
  • Improved patient care outcomes and reduced hospital readmission rates by 18%
  • Streamlined reporting, saving hundreds of hours monthly
  • Enhanced operational transparency for healthcare providers
  • Python: Enabled precise predictive analytics for patient risk assessments

How Did our Solution Help ?

  • Better Patient Care
    18%

    fewer readmissions with Al-based risk prediction

  • Time Saved ↑

    Hundreds of hours/month saved via aumo- mated reporting 

  • Transparency

    Real-time dashboards provided clarity across departments

  • Data-Driven Decisions ↑

    Clinicians used live insights for proactive patient care 

Client Testimonial

Our physicians are now more empowered with predictive tools and dashboards that guide every decision — patient care has become proactive and insightful.

Chetan Arora

Director of Clinical Operations

Spice Bazaar, Miami, USA

Securing Finance & Insurance with Predictive Intelligence

Client Overview

A top-tier financial and insurance service provider struggled with:

Challenges Faced

Fraudulent Transactions
Financial losses and compliance risks
Manual Claims Process
Delays and poor customer experience
Poor Credit Scoring
Inaccurate risk predictions
High Customer Churn
Decreased loyalty and lost revenue

These inefficiencies were affecting trust, profitability, and overall operational efficiency.

Intellivista Ai Powered Solution

We implemented an end-to-end transformation using Python, Power BI, and AI-based models:

Implementation Breakdown

Fraud Detection Algorithms
  • ML models trained on transaction patterns
  • Real-time alerts for suspicious activity
Advanced Credit Scoring
  • AI-powered models evaluated customer risk profiles
  • Integrated alternative data for better decision-making
Claims Analytics Automation
  • Claims triaging using NLP and smart classification
  • Automated status updates and resolution pipelines
Churn Prediction Models
  • Tracked early signals of customer drop-off
  • Enabled targeted retention campaigns
Power BI Dashboards
  • Real-time fraud tracking
  • Claims lifecycle visualization
  • Risk exposure heatmaps

How Did our Solution Help ?

  • Fraud Detection ↑
    97%

    Accuracy in real-time fraud detection using Al

  • Claims Time↓
    50%

    Faster claims processing with automation

  • Churn Reduction ↓

    Targeted actions BOOSTED, CUSTOMER, RETENTION

  • Real-Time Dashboards

    Power BI enabled INSTANT RISK & CLAIMS INSIGHTS

Client Testimonial

Our transformation journey with AI brought precision, speed, and trust to our operations. Fraud dropped, claims sped up, and clients stayed longer.

Chetan Arora

Chief Risk Officer

Powering Manufacturing with AI & Real-Time Analytics

Client Overview

A large-scale industrial manufacturing company faced:

Challenges Faced

Procurement Issues
Quality issues and more investment in raw Material
Unplanned Downtime
Disrupted production and lost output

These challenges led to production delays, cost overruns, and declining customer satisfaction. No Real-Time Monitoring Poor visibility and delayed decision-making

Implementation Breakdown

What We Delivered
  • Real-time Raw Material Data Forecasting Time-Series ML models (ARIMA, XGBoost, LSTM) Automated forecast signals
Predictive Maintenance Models
  • ML models trained on sensor and historical data
  • Early detection of potential breakdowns
Real-Time Operational Dashboards
  • Power BI dashboards visualizing:
    • Live production KPIs
    • Machine health status
    • Efficiency metrics

How Did our Solution Help ?

  • Excessive Raw Material Purchase
    -22%

    Decreased by 22%

  • Equipment Downtime
    -40%

    Decreased by 40%

  • Operational Efficiency

    Enhanced through live dashboards

  • Operational Cost Savings

    Reduced through live dashboards

Client Testimonial

We now catch product issues early, maintain machines before failure, and make faster decisions—thanks to AI and real-time dashboards.

Chetan Arora

Plant Head

Alicon Group