AI Force
NVIDIA AI Integration
TBR Report

Overview

AI Force is HCLTech's flagship service transformation platform, leveraging GenAI to revitalize software engineering, business processes and IT operations.

At its core, AI Force is mapped to people and their workflows, using advanced machine learning algorithms and neural networks to deliver tangible benefits—from enhanced efficiency and productivity to accelerated time-to-market for products and services.

Its unique ability to seamlessly integrate with the existing IT landscape and the tooling in place ensures it's a non-disruptive force multiplier. 

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Fast Facts

30%

Acceleration in software development

Up to 50%

Acceleration in legacy application modernization

30%

Increase in testing speed

25%

Faster issue resolution

18-20%

Reduction in MTTR

Key Features of AI Force

LLM-agnostic

Plays well with all LLMs and SLMs, both proprietary and open source, including Azure Open AI, Google Gemini, Phi, Llama, etc.

Responsible AI

Governance features include fairness, accountability, data anonymization and security measures to protect sensitive information. This emphasis on ethical AI practices is a competitive differentiator.

Multi-modal governance

Speech recognition input capability to upload voice recordings of application requirement-related content to be able to generate detailed features and user stories 

Agentic tech for IT operations

Offers autonomous agents that detect, resolve and learn from IT incidents in real-time. Users can review chat histories, test agent skills and obtain ticket statuses and remediation process documentation.  

Prebuilt use cases and recipes

Uses advanced automation and GenAI models to analyze historical ticket data to create resolutions, prioritize test cases, summarize/migrate code and check for security vulnerabilities.

Customization

Fully customizable and extensible, it supports creating custom connectors and developing new use cases on top of the existing platform, making it highly adaptable to unique business requirements. 

Telemetry

Track metrics like active users, executed jobs, downloads, published content, tokens used by different language models and job reruns—all configured in the UI as widgets, giving users insights into overall tool usage and performance.

FinOps-friendly

OOTB parameters like prompts, total tokens consumed and dollars spent per job execution are already available and can generate reports for end users. Additional widgets can be designed for increased consumption.

Deployment and consumption models

The solution can function as a standalone system or be integrated into existing tools. It offers API functionality requiring no user interaction for smooth integration and can be deployed on AI-powered PCs for enhanced accessibility and performance in real-time applications.

AI Force Competitive Differentiators

No other platform on the market offers all these features right out of the box:

By automating routine tasks, analyzing data in real-time, and optimizing workflows, this approach minimizes delays and reduces operational costs.

Features a unified platform for code generation and rectification, epics, security, etc.

Includes a diagnostic questionnaire for quick and effective remediation

Generates contextual code in various languages, including C, Python, Java, etc.

Integrates with (rather than replaces) existing tools and brings data sets together, creating a knowledge graph of the relationships between datasets and conducts comprehensive root cause analysis

Addresses technical debt challenges by accelerating modernization and migration of legacy IT landscapes, leading to higher quality code, better documentation and more cost-effective landscapes

Includes 18 patents, offers multimodal capabilities and is microservices-enabled, modular and scalable

Reduces strain on the underlying cognitive infrastructure through batch processing, leading to reduced energy consumption

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