VerifAI: End-to-End lifecycle validation of AI-based projects
Tech Mahindra Limited
Comprehensive AI validation and verification offering, designed to help organizations transition their AI use cases from Proof-of-Concept to Production efficiently and ethically
Comprehensive AI validation and verification offering, designed to help organizations transition their AI use cases from Proof-of-Concept to Production efficiently and ethically
Customer Challenge:
- Data quality and bias
- Ethical considerations & regulations
- Security aspects and privacy concerns
- Longer lead time in case of changes
- Integrating GenAI models with existing systems can be complex
- AI Transparency and Interpretability
Introducing VerifAI:
Tech Mahindra’s verifAI brings the power of Generative Al and Azure OpenAI to provide
a comprehensive AI validation and verification offering, designed to help organizations transition their AI use cases from Proof-of-Concept to Production efficiently and ethically. It provides a 360-degree validation framework with customizable metrics, pre-built solutions for faster value realization, and a microservices-based architecture for seamless integration. verifAI also emphasizes ethical AI practices, ensuring that AI systems perform as intended and adhere to legal and ethical standards.
verifAI is a comprehensive solution for validating and verifying the outcomes of AI and GenAI projects. Through this solution, Tech Mahindra will help enterprises validate the end-to-end lifecycle of AI-based projects, thereby enabling them to scale their AI initiatives with speed.
Our Advisory & Consulting Services
- Customized GenAI Studio
- Enterprise knowledge Search
- Data augmentation for models
- Responsible AI adoption
- Pre-Development Data analysis, Model selection, Hallucination detection, Monitoring the AI application
Possible Scenarios:
- Consulting
- Pre-built solution implementation
- Proof of concepts
- Third party solution implementation
- Tuning of the deployment models
- Validation and testing of AI models and hyperparameters.
- Validation of data quality for bias, anomalies and privacy
Business Benefits
- Faster Product development
- Quick adoption
- Regilatory complaint
- Improved Decision Making
- Enhanced Data Integrity
- Increased efficiency at low cost