General Enterprise Case studies
Use Case - Customer Data Platform (SaaS)
Platform Scale & Data Overview
- 230M Consumers
- 15-Year History
- 60 TB Data
Solution Headline
- Co-managed IT Services in AWS.
- EC2, Redshift, Python, DynamoDB, Glue, & Sagemaker.
- Onboarded Big data, Analytics and Full Stack. development resources in 2 weeks.
- Proven Knowledge transition process.
1. Driver
- New business growth with increased custom IT development.
- No scalable, skilled internal IT pool.
- Delayed projects, lost business opportunities.
2. Outcome
- Team productive in first month.
- 50% cost reduction.
- Platform scaled to 3X client volume.
- No HR burden for client.
- IT services rapidly scaled to meet business growth.
Use Case – Services Organization
Service Overview
- 20K Customers, Leads
- Sales team – 100
- 200M Marketing Budget
Solution Headline
- Onboarded Salesforce Salescloud, MarketingCloud and Commercecloud resources.
- Requirements analysis, design, build and deployment in 8 months.
- Force.com, Lightning, System integrations.
1. Driver
- Migrate custom CRM applications to Salesforce.
- Aggressive Product launch schedule.
- External expertise to improve OOTB solution and reduce custom development.
2. Outcome
- 60% cost reduction with Hybrid resource model.
- On schedule GTM.
- Enhanced Sales performance.
Use Case – Insurance Services Company
Insurance Service Overview
- 30K Users
- 100-year history
- Legacy Technologies
Solution Headline
- Replatform applications with latest MERN Stack, Mobile technologies hosted in AWS.
- AWS EC2, Load balancer, Cloudfront, & Cognito.
- Design, configuration, QA and launch in 6 months.
- Mobile and web apps upgraded to latest stable versions.
1. Driver
- Legacy technologies.
- Cost reduction.
- Delayed projects, lost business opportunities.
2. Outcome
- 40% cost reduction.
- Reduced technical debt, more secure production environment.
- Improved SLAs..
Use Case – Consumer Durables Manufacturer
Consumer Durables Overview
- 1M Appliances
- 30M Sensors
- 50TB Data
Solution Headline
- Hadoop Big Data with HDFS, Hive, Cassandra in cloud to store and process millions of sensor events.
- SAS, BOBJ analytics to perform advanced and predictive analytics.
- Feedback loop to consumer portal (web and mobile).
1. Driver
- Reduce product defects and reduce warranty reserves.
- Avoid expensive Technician visits to substantially improve overall margins.
- Sensor data analysis is a competitive differentiator in energy efficiency.
2. Outcome
- Concept-2-Solution in 4 Months.
- $20 M / year warranty savings due to defective part replacement.
- 5% improvement in Energy efficiencies.
Use Case – Services Company
Services Company Overview
- High Value Consumers
- 100+ Applications
- Missing SLAs
Solution Headline
- Seamless transition to Managed Services Provider approach.
- Introduced new technologies.
- Renegotiated vendor licenses.
- Implemented Cloud solutions.
1. Driver
- Complaints of delayed response times and incomplete solutions.
- Unable to address unique strategic needs of the business.
2. Outcome
- Reduced response times, improved SLAs.
- Streamlined incident handling.
- 40% savings in IT Support & licensing costs.
- improved cybersecurity.
- Sustainable foundation and scalable environment.
Use Case – Services Company
Company Services Overview
- Very high volume campaigns
- 200+ Applications
- Cybersecurity concerns
Solution Headline
- Quick transition
- Threat intelligence & assessment
- Newer technologies
1. Driver
- Geopolitical events and general hits to company digital assets.
- Legacy cybersecurity footprint.
- Cloud adoption & migration
2. Outcome
- Reduced MTTD SLAs.
- 99.9% detection rate for endpoint-based threats.
- 30% reduction in critical vulnerabilities
- Reduced phishing click-through rates by 70%.
AI Case studies
Case Study – Data Insights
Data Insights Overview
- High volume marketing to 230M consumers
- 15-Year data and content history
Solution Headline
- Implemented AI-powered Copilot on Big Data and content repositories.
- Tailored configuration and training of NLP models, LLMs on historical data.
- Integrated Copilot with enterprise data in Redshift, DynamoDB and Sharepoint.
- Trained to answer analyst questions like ‘Which Campaign has lowest marketing spend but highest return in Q2” without manual slice and dice.
- Piloted to key stakeholders, refined the solution and Rollout
1. Driver
- Analysts were pulling repetitive reports and ad-hoc data requests, diverting valuable time from high-impact analysis and strategic insights.
- Reliance on IT for simple projects and long approval cycles
- Stalled by Data Silos
2. Outcome
- Automated data exploration and instant answers
- Boosted Marketing & Operations team’s productivity
- Faster decision-making and rapidly adaptable campaigns to emerging trends in real-time
- Minimal new technology footprint
Case Study – Empowering Patients
Patients Overview
- VC funded Startup in Healthcare
- Estimated 10K daily users
Solution Headline
- Created NLP based mobile App.
- AI driven document reader solution
- Tech stack – Open AI, Retrieval Augmented Generation (RAG), LLamaIndex
- Implemented Gen AI (OpenAI’s APIs) solution. Created Prompt engineering to get right answers for patient questions and context around symptoms, medical conditions, lab results and prescriptions.
- Mobile App development for Apple and Android
1. Driver
- Overwhelmed and anxious patients about medical conditions, treatments, and upcoming doctor visits
- Complex Medical Terminology for patients to understand, leading to confusion and ineffective communication with healthcare providers.
- Limited access to reliable information
2. Outcome
- Personalized answers instantly on patients’ phone
- Response to patient queries in simple language, avoiding complex medical terminology.
- Improved patient knowledge, and reduced stress
- Improved Doctor-Patient communication with better preparedness and increased engagement
Case Study – Smart Hiring Solution
Hiring Overview
- Growing Non-profit organization
- HR Department busy with talent acquisition
Solution Headline
- Implemented machine learning algorithms to automatically screen resumes, match candidates to job requirements and scoring.
- Integrated AI chatbots powered by NLP to automate replies to applicant inquiries and schedule interviews.
- Implemented Co-Pilot based solution to track candidate responses, send automated reminders for follow-ups, and verify application details against internal databases.
1. Driver
- HR teams faced manual processes in candidate screening of hundreds of applicants and email replies
- Fragmented processes in interview scheduling, response tracking, and leading to inefficiencies and delays.
2. Outcome
- 30% faster applicant screening and 20% reduction in time-to-hire.
- Increased interview scheduling efficiency, with 70% of interviews scheduled automatically.
- Enhanced candidate experience due to real-time interactions.
Case Study – AI Chatbot for Ingredient Details
Ingredient Details Overview
- Mid-size food processing company with 5,000 B2B clients
- 50 member Customer Service team
Solution Headline
- Identified unified and dynamic knowledge base with historical and real-time company data.
- Configured and trained AI bot on company data and content
- Contextual understanding & NLP solution
- Integrated AI Bot to client portal
- Requirements analysis, design, build and deployment in 4 months.
1. Driver
- Challenges in providing instant, accurate info to clients. Sales & Client service teams spend time on complex questions on ingredients, GMO, Gluten-free type details, and product roadmap.
- Time consuming manual lookups and inconsistent responses
2. Outcome
- 2 out of 5 questions answered by Bot
- 24/7 on demand responses to client questions empowering B2B clients
- Faster sales cycles and conversions
- Improved market responsiveness
Case Study – AP Automation
Automation Overview
- Global Manufacturing company
- 25 AP Team processes 20K invoices a month
Solution Headline
- Integrated Computer Vision technology to accurately read and extract data from invoices in PDF and scanned image formats.
- Implemented RPA (Robotic Process Automation) to automate user keystrokes for data entry, validation, eliminating manual data entry.
- Modeled and trained AI algorithms to match invoices with purchase orders, flag discrepancies and route exceptions for manual review.
- 6-member team, completed in 5 months
1. Driver
- Manual data entry by the AP team led to inefficiencies, high error rates, and slow invoice processing.
- Integration with legacy systems is prohibitively expensive and time-consuming.
2. Outcome
- Faster invoice processing, improved cash flow, and operational efficiency
- 90% of invoices processed automatically and only 10% routed to human intervention.
- Reduced error rates and streamlined workflow
- $1M productivity gains, 3X ROI
