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Product Overview

Product Description​

LLMOps is an enterprise-ready platform designed to simplify the management of Large Language Models from initial customization to production deployment. The platform combines model lifecycle management, application development, monitoring, and pre-built AI solutions into a single, unified interface.

It caters to a wide range of enterprise needs — from creating highly specialized models for domain-specific applications to deploying ready-made AI assistants that handle operational, analytical, and creative workflows.

Key Features​

Model Fine Tuning​

  • Customize open-source models with proprietary data.
  • Support for quantization and performance optimization.
  • Full training job tracking for auditability.

Model Compression​

  • Reduce the size of pretrained models for faster inference.
  • Maintain core accuracy while lowering infrastructure costs.
  • Deploy compressed models seamlessly into production.

App Design​

  • No-code / low-code drag-and-drop workflow builder.
  • Support for LLM-powered and agentic workflows.
  • Customizable prompts, triggers, and integrations.

Monitoring​

  • Track and audit every LLM request and response.
  • Enforce governance policies and compliance rules.
  • Monitor token usage and operational metrics in real time.

App Store​

  • Central hub for accessing pre-built AI applications.
  • Enterprise-specific apps for analytics, HR, logistics, and more.
  • Examples include:
    • Data Vizard – Natural language-driven data exploration and graph generation.
    • Smart Chat – Multi-model conversational experiences.
    • Nexen HR – AI assistant for HR operations.
    • Optilogistics – AI-based delivery and routing optimization.
    • Speech to Text, Text to Image, Image Chat, Smart Researcher, etc.

Benefits​

  • Accelerated AI Adoption: Reduced time-to-value with ready-to-use AI solutions.
  • Operational Efficiency: No-code workflows and compressed models enable faster, more cost-effective deployments.
  • Governance & Compliance: Built-in monitoring ensures responsible AI usage.
  • Scalability: Support for multiple concurrent workflows and applications.

Example Use Cases​

  • Financial Services: Automated report generation and risk analysis.
  • Human Resources: Candidate screening, onboarding automation, and policy compliance checks.
  • Logistics: Real-time fleet route optimization and predictive delivery planning.
  • Creative Industries: Text-to-image generation and AI-driven content creation.