AI Force is HCLTech’s enterprise-grade GenAI platform designed to transform software engineering, business processes and IT operations. It applies generative AI, machine learning and agent-based workflows to increase efficiency, reduce manual effort and accelerate lifecycle activities across development and operations. The platform is built to integrate with existing enterprise IT environments and toolchains rather than replace them. It supports multiple commercial and open-source large and small language models, allowing flexible model selection depending on workload and cost considerations. AI Force includes governance and security mechanisms designed to support responsible AI adoption. It incorporates structured security controls addressing infrastructure, inbound and outbound data protection. The solution can be deployed in different consumption models, including standalone environments, embedded integrations within enterprise tools, API-driven headless usage, and edge deployments on AI-powered PCs. Performance improvements reported for the platform include acceleration in software development, legacy modernization, testing, issue resolution and mean time to resolution (MTTR).

Key Features

LLM-Agnostic Architecture Supports multiple proprietary and open-source LLMs and SLMs.

• Compatible with commercial and open-source models
• Flexible model selection per workload
• Cost-aware “horses for courses” approach

Agentic Workflows for IT Operations Autonomous agents detect, resolve and learn from IT incidents.

• Real-time incident detection
• Ticket status visibility
• Continuous learning from historical cases

Prebuilt Use Cases and Automation Recipes Applies GenAI to historical ticket and engineering data.

• Automated resolution generation
• Test case prioritization
• Code summarization and migration
• Security vulnerability checks

Telemetry and FinOps Controls Built-in monitoring of usage and consumption metrics.

• Token consumption tracking
• Job execution metrics
• Cost visibility per execution
• Custom dashboard widgets

Responsible AI and Governance Governance mechanisms embedded into platform design.

• Fairness and accountability controls
• Data anonymization mechanisms
• Infrastructure, inbound and outbound data security
• Disaster recovery and network protection

Multi-Modal Capabilities Supports text and speech-based inputs.

• Speech recognition input
• Feature and user story generation from voice input
• Search and summarization functions

Flexible Deployment Models Multiple consumption options for enterprises.

• Standalone deployment
• Embedded into IDEs, testing tools and ticketing systems
• API-based headless integration
• Edge deployment on AI-powered PCs

Benefits

Acceleration of Software Engineering Lifecycle Improves speed across development and modernization activities.

• Faster software development cycles
• Accelerated legacy modernization
• Increased testing speed

Reduced Incident Resolution Time Enhances operational responsiveness.

• Faster issue resolution
• Reduced MTTR
• Continuous agent learning

Improved Integration with Existing IT Landscapes Designed to complement current toolchains.

• Non-disruptive adoption
• Toolchain integration
• Knowledge graph–based analysis

Cost Transparency and Control Enables monitoring of AI consumption and cost drivers.

• Token usage tracking
• Cost per job execution
• FinOps-oriented reporting

Enterprise-Grade Security and Governance Structured data protection strategy.

• Infrastructure security controls
• On-prem embedding options
• Controlled inbound and outbound data flows