• Automated data ingestion pipeline with use case-specific metadata extraction
• Multi-agent information retrieval solution
• Enhanced search experience through prompt engineering
• Business-specific rules and guidelines integration
• Flexible deployment options: Hyperscalers or on-premises infrastructure

Application Developed

• iScan: Uses NVIDIA Enterprise RAG application for the Energy and Utilities industries that provides accurate, real-time answers to queries from a comprehensive inspection report (knowledge base). The application enhances decision-making and operational efficiency by retrieving relevant information and generating insightful responses tailored to specific needs of industry professionals and consumers.
• Tech Stack: NVIDIA Enterprise RAG and NIM^TM

• Intuitive conversation UX design
• Responsible AI filters and business-specific guidelines integration
• Voice support capabilities
• Seamless enterprise information system integration

Application Developed

• CustCare.ai: A multi-domain MOE-based agentic application to automate customer support workflows via voice-call, webUI, and email. This application handles diverse queries, using expert models for accurate responses. It independently performs tasks like ticket creation and automates repetitive processes. Supporting multi-channel interactions, it increases efficiency and customer experience.
• Tech Stack used: RIVA/NeMo^TM-based ASR/TTS Application

• Custom AI model development, training, and fine-tuning
• Voice analytics
• Image and video generation
• Enterprise system integration

Application Developed

• ImageVideo Analyzer: Analyzes the overall context and relationships between the identified objects in an image to give a summary or caption.
• Used as a vision assistant, visual question answering and for language generation.
• TechStack used: NVIDIA-NeVA and stable diffuser.

• Custom Large Language Model (LLM) development
• Enterprise-specific knowledge base integration
• Optimized on-premises deployment with minimal compute requirements
• Enterprise-wide service deployment

Showcase: NeMo^TM-LLM Fine-tuning, TensorRT^TM LLMs

Application Developed

• Edge Optimizer: TensorRT^TM includes an inference runtime and model optimizations that deliver low latency and high throughput for production applications.
• TensorRT^TM optimizes inference using techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs.
• TensorRT^TM provides post-training and quantization-aware training techniques for optimizing FP8, INT8, and INT4 for deep learning inference.