5+ Years Of
Experience
$3+ Million R&D
Sriya.AI has developed the world’s 1st Large Numerical Model (LNM) powered by its proprietary SXI++ AI-ML algorithm technology suite. LNMs is to numerical structured data what LLMs are to unstructured data. LNMs are very accurate and DO NOT hallucinate. LNMs run on energy friendly CPUs not GPU or TPU and have very low computing needs (No need for AI-ML companies to invest in nuclear power plants).
Highly curated LNMs enable companies to benefit immensely from the data their business processes/ERP generate. LNMs can provide a potential 20-200% improvement in business outcomes. Our LNMs deploy real world solutions in healthcare, financial and industrials verticals with high accuracy, recall and precision. 7 US Provisional Patents have been filed on the LNM and SXI++ technology suite.
Sriya.AI provides a real ROI to our customers with our AI as it quantifies business improvements. Sriya’s revolutionary technology allows even SMEs who generate small but valuable data to gain actionable insights and get improvements in business outcomes which they truly deserve (Why should only big guys have all the AI fun?).
LLM | LNM | |
---|---|---|
Personal vs. Enterprise | Enhance individual creativity | Enhance enterprise productivity. |
Language vs. Numbers | Process and generate text | Process numbers and generate precise actionable insights. |
Uncertain vs. Predictable ROI | Provide qualitative benefits | Offer quantitative returns (e.g., a 20% efficiency boost). |
Probability vs. Certainty | Hallucinate | Highly accurate |
General vs. Industry-Specific: | Generic | Curated Vertically |
Costly vs. Efficient: | Use GPUs | Run on CPUs |
• Unplanned Readmission (HURRA)
• Sepsis Detection (HOSRA)
• Fraud
• Payments
• Loans
• Backorder Reduction
• Inventory Optimization
• Logistics Optimization
Industry | Case Study | ChatGPT (GPT-4o) | XG Boost/Random Forest Auto-ML | H2O.AI V:3.46.04 | Alteryx V:2023.26++ | Sriya.AI |
---|---|---|---|---|---|---|
Healthcare | >30 Days Hospital Unplanned Readmissions | 64.54% | 62.62% | 57.21% | 53% | 99.8% |
National Ambulance Activation (NEMSIS) | 75.75% | 68.58% | 68.61% | 65% | 98.56% | |
Emergency Triage | 89.9% | 82.9% | 80.45% | 84% | 99.76% | |
Supply Chain | Inventory Optimization | 75.11% | 78.9% | 87.83% | 86% | 99.76% |
Backorder Reduction | 78.74% | 94.42% | 95.02% | 99% | 99.10% | |
Industrial | Cement R&D | 95% | 97.56% | 77% | 100% | 100% |
Predictive Maintenance | 60.85% | 62.32% | 56.12% | 57% | 97% | |
Telecom | Wireless Churn Reduction | 58% | 67% | 62.47% | 59% | 98% |
HR | HR Churn Reduction | 84.13% | 85.96% | 85.22% | 81% | 99.12% |
Marketing | Adobe Photoshop Relevance | <10% | 51.28% | 67.65% | 62% | 99.32% |
Financials | Current & Late Payments | 85% | 84.52% | 84.23% | 84% | 98.25% |
Predict Default Payments | 94.2% | 93.87% | 70.2% | 72% | 99% |
A patient returning to the hospital unexpectedly within a certain time frame after discharge.
Read MoreAI detects financial fraud by analyzing data and identifying suspicious transactions.
Read MoreAI lowers maintenance costs by predicting failures and automating repairs.
Read MoreAI improves logistics through route planning, inventory management, and automation.
Read MoreAI boosts subscription growth through data analysis and personalized marketing strategies.
Read MoreAI enhances loan analysis by automating assessments and predicting repayment behavior.
Read MoreAI enhances productivity by automating tasks and optimizing workflows efficiently.
Read MoreAI improves logistics through route planning, inventory management, and automation.
Read More• Large synthetic datasets for faster roll out with 95%+ accuracy and precision
• Missing data, missing features, additional features, heterogenous data mapping and more
• 97%+ accuracy and precision even in very small datasets (150 records)
• 98% accuracy and precision in very large datasets (51M records and > 100 features)
• 25% reduction in R&D time and # of experiments (DOE)
• 25% Improvement even in abstract KPIs like employee churn, resource scheduling or recruiting