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AgentIQ is an enterprise-grade AI agentic workflow platform that transforms Software Development Lifecycle (SDLC) automation through intelligent AI agents. Agentic turns fragmented SDLC activities into governed, reusable execution flows across enterprise tools. Built natively on AWS infrastructure, AgentIQ orchestrates 30+ specialized agents to automate requirement analysis, code generation, code quality testing, documentation, and SRE tasks - delivering measurable productivity gains while maintaining enterprise security and governance.
Overview
AgentIQ deploys specialized AI agents as tireless team members that handle repetitive SDLC tasks at machine speed. Whether generating production-ready code, synchronizing and conversing with your enterprise data, or orchestrating multi-agent workflows, AgentIQ enables enterprises to scale software delivery capabilities without proportionally scaling headcount. Core Capabilities:-
- More than 30 Pre-Built AI Agents: Requirement analysis, Code generation, Code testing, documentation, security reviews, SRE automation in multiple technology stacks including Java, Python, Cobol and others with built in HITL reviews
- Centralized governance : Full visibility and control on agent boundaries, tokenomics, model access, agent traces and evals. A dedicated budget management module ensures LLM cost is always under control.
- Multi-LLM Support: Easily pluggable with multiple LLM models from Anthropic, Open AI, Gemini and others.
- Visual Workflow Studio: Drag-and-drop LCNC interface for building complex automation workflows.
- Enterprise Integrations: Model Context Protocol connectors to Jira, GitHub, Confluence, S3, Figma and other enterprise data systems to integrate enterprise data into knowledge fabric.
- Zero-Trust Security: Enterprise data secured at rest and in-transit, HashiCorp Vault secrets management and secure access management.
Highlights
- Productivity & Efficiency:- 1. Reduce code generation time by 50% 2. Handle 2-3x more projects with existing teams 3. Eliminate 40-60% of manual SDLC tasks
- Cost Optimization:- 1. Cut operational overhead through intelligent automation 2. Real-time cost tracking prevents runaway LLM expenses 3. Augment teams with AI vs. hiring scarce senior talent / Speed & Time-to-Market:- 1. Compress sprint cycles with automated generation and testing. 2. Validate prototypes in days instead of weeks 3. Eliminate documentation bottlenecks
- Risk Reduction & Governance:- 1. Complete audit trails satisfy GDPR and SOC 2 2. Vault-based credential isolation eliminates hardcoded secrets 3. Enforce organizational best practices through agent policies / Competitive Advantage:- 1. Accelerate AI adoption without ML expertise requirements 2. Deliver features faster than competitors using manual processes 3. Reduce developer burnout by automating tedious tasks 4. Modular architecture adapts to emerging LLM models and custom agents
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AILedEngg CSTTeam - ailedengg.cstteam@ltm.com Prashant Kumar Singh - prashantkumar.singh2@ltm.com