Drive Innovation and transformation through STL Digital’s AInnov ™, a Generative AI solutioning fabric for enterprises
STL Digital’s AInnov™ empowers enterprises to leverage AI for innovation and business value realization. AInnov is a comprehensive AI solution framework with a human feedback loop. It integrates software libraries, model data engineering methodologies, model management, data structures and algorithms. It also includes 360-degree image-to-insights processing capabilities
AInnov™ Business Model
Built on Top of Industry-Leading AI Platforms
Foundation Models provide a fantastic combination of accuracy and versatility
Customization by fine-tuning these models for enterprise-specific data
Ready to use AInnov™ solutions that can be quickly implemented for your business needs
End-to-end solutioning capability, focusing on transforming raw data into meaningful insights, content, and recommendations tailored to specific use cases.
AInnov’s data ingestion, data preprocessing, and feature extraction modules are meticulously designed to handle the intricate process of converting enterprise data into a suitable format for model training while prioritizing data security and privacy.
AInnov's extensive model library includes prediction models, recommendation models, and more, all designed to meet the unique requirements and generate the appropriate content for the next best action
AInnov offers an AI-powered solution designed exclusively for simplifying data engineering pipelines for data acquisition in enterprises. It also includes enterprise custom model fine-tuning and features that help streamline enterprise business processes and increase awareness of standard operating procedures.
Harnessing the Power of Large Language Models (LLMs)
Versatile Data Source Support
File Tagging for Relevant Downloads
Seamless Integration into Enterprise Workflows
Efficient User Query Handling
Custom Web Application and MS Teams Integration
Industry Value Realization
Increase productivity by generating synthetic data, optimizing processes, and automating tasks
Improve predictive maintenance by predicting equipment failure and identifying anomalies
Enhance security and safety by detecting fraud and preventing accidents
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