Industries
Industry expertise
Every industry is unique, with complex challenges shaped by regulations, market dynamics, and evolving customer expectations. At Agenthum AI Solutions, we don’t believe in “one-size-fits-all.” Instead, we combine Artificial Intelligence (AI), Cloud Transformation, and Business Intelligence (BI) to craft tailored solutions that help businesses stay resilient, innovative, and future-ready.
Why Choose Agenthum Across Industries?
- Industry-Aware AI – RAG, Agentic AI, and Predictive AI designed for specific industry problems.
- Cloud-First Approach – Hybrid & multi-cloud strategies for scale and compliance.
- BI-Driven Decisions – Unified dashboards for smarter, faster choices.
- Proven Impact – Tangible business outcomes across BFSI, Healthcare, Retail, Insurance, Life Sciences, and Manufacturing.
Banking and financial services
Industry Challenges:
- Regulatory compliance is resource-heavy, requiring continuous monitoring of RBI, SEBI, Basel III, and international guidelines.
- Rising digital fraud schemes make traditional fraud detection ineffective.
- FinTech disruptors raise customer expectations for 24/7 personalized banking.
- Legacy IT systems limit agility and innovation.
Agenthum AI Solutions:Industry Challenges:
- RAG-powered compliance copilots → AI grounded in policy/regulatory docs for accurate, traceable compliance answers.
- Fraud detection engines → Machine learning models detecting anomalies in transaction patterns in real time.
- AI-driven personalization → Customer insights enabling tailored loan offers, wealth advisory, and cross-selling.
- Cloud-native banking → Migration of legacy core banking apps to cloud for scalability.
- BI dashboards → Unified reporting for risk, revenue, and compliance metrics.
Example:
A leading NBFC adopted our AI-powered fraud monitoring. By analyzing millions of transactions per day, it flagged anomalies in under 3 seconds. The result: 30% fewer false positives and millions saved annually.
Business Impact:
- Improved compliance accuracy
- Reduced fraud-related losses
- Higher customer retention with personalization
- Faster innovation cycles through cloudtions:Industry Challenges:
Healthcare
Industry Challenges:
- Patient volumes are rising, while staff shortages strain resources.
- Manual-heavy processes in Revenue Cycle Management (RCM) delay cash flows.
- Fragmented EHR systems prevent a holistic patient view.
- Strict compliance requirements (HIPAA, GDPR) demand secure data handling.
Agenthum AI Solutions:Industry Challenges:
- Agentic AI workforce → Digital agents automating billing, scheduling, and patient outreach.
- Cloud-hosted EHR platforms → Interoperable, HIPAA-compliant systems that unify patient data.
- AI triage assistants → Chatbots and copilots that handle symptom checking and direct patients to the right care.
- Analytics dashboards → Track hospital performance, bed utilization, and patient outcomes.
Example:
A multi-specialty hospital implemented our multi-agent AI system.
- Agent 1: Scheduled appointments.
- Agent 2: Processed billing & claims.
- Agent 3: Generated real-time dashboards for administrators.
This reduced administrative workload by 40% and improved patient satisfaction scores by 25%.
Business Impact:
- Faster patient care delivery
- Cost savings in RCM
- Reduced staff burnout
- Regulatory compliance assured
Insurance
Industry Challenges:
- Fraudulent claims lead to revenue leakage.
- Underwriting is slow and manual, reducing competitiveness.
- Customers demand instant, digital-first policy support.
- Compliance with IRDAI and global regulations requires traceability.
Agenthum AI Solutions:Industry Challenges:
- RAG-powered policy assistants → AI agents answering queries with citations from policy docs.
- Claims automation → NLP & computer vision for automated document verification.
- Agentic AI in underwriting → Automates risk profiling and policy pricing.
- Cloud BI dashboards → Real-time visibility into claim ratios, fraud trends, and customer churn.
Example:
For a health insurer, we built an AI claims triage system. Claims processing time dropped from 7 days to 24 hours, improving customer satisfaction and reducing fraud.
Business Impact:
- Faster claims turnaround
- Reduced fraud losses
- Enhanced compliance
- Improved customer trust
Life Sciences
Industry Challenges:
- Fraudulent claims lead to revenue leakage.
- Underwriting is slow and manual, reducing competitiveness.
- Customers demand instant, digital-first policy support.
- Compliance with IRDAI and global regulations requires traceability.
Agenthum AI Solutions:Industry Challenges:
- AI for drug discovery → Predicts molecule behavior & accelerates candidate identification.
- RAG copilots for researchers → Summarize and analyze vast research literature.
- Cloud-hosted data platforms → Store & analyze genomic/clinical data securely.
- BI dashboards → Monitor trial progress, patient adherence, and research efficiency.
Example:
A biotech company used our AI-driven drug discovery pipeline hosted on cloud. Time to identify viable compounds dropped by 30%, cutting costs significantly.
Business Impact:
- Faster R&D cycles
- Cost-efficient research
- Regulatory-ready documentation
- Collaboration across global R&D teams
Retail
Industry Challenges:
- Fluctuating consumer demand makes inventory planning difficult.
- Customers expect personalized, omnichannel experiences.
- Supply chain disruptions increase operational costs.
- Retailers struggle with siloed data across POS, e-commerce, and warehouses.
Agenthum AI Solutions:Industry Challenges:
- AI demand forecasting → Predict sales trends using seasonal + behavioral + market data.
- Personalization engines → Tailored product recommendations to boost basket size.
- Cloud-native e-commerce platforms → Scalable, secure digital shopping experiences.
- BI-powered supply chain dashboards → Real-time tracking of stock levels and supplier performance.
Example:
A fashion retailer deployed our AI demand forecasting system, integrating POS and e-commerce sales data. They cut inventory waste by 20% while ensuring 95% product availability during peak seasons.
Business Impact:
- Increased sales from personalization
- Reduced operational costs
- Improved inventory accuracy
- Stronger customer loyalty
Manufacturing
Industry Challenges:
- Unplanned downtime leads to heavy losses.
- Inefficient supply chains disrupt production.
- Pressure to adopt Industry 4.0 (IoT, AI, robotics).
- Quality control still relies heavily on manual inspection.
Agenthum AI Solutions:Industry Challenges:
- Predictive maintenance AI → Uses IoT sensor data to predict failures.
- AI-driven smart factories → Digital agents optimize production scheduling and workflows.
- Cloud ERP modernization → Replace outdated systems with agile platforms.
- BI dashboards → Real-time visibility into OEE, yield, energy usage.
Example:
An automotive manufacturer deployed our AI predictive maintenance system. Downtime reduced by 25%, saving millions annually while improving delivery timelines.
Business Impact:
- Improved uptime & efficiency
- Reduced operational costs
- Higher product quality
- Faster supply chain response
