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Infosys Agent Control Framework for Deterministic SDLC AI, part of Infosys Topaz

Overview

Enterprises are investing in AI tools, assistants, and agents, to accelerate software engineering and modernization. Yet many still struggle to achieve governed scale, consistent quality, and measurable ROI, across the software development lifecycle (SDLC).

Infosys Agent Control Framework, part of Infosys Topaz, addresses this gap by adding an opinionated orchestration layer over existing AI assistants. It is enabling teams to apply enterprise context, approved integrations, reusable agent patterns, and human-centered guardrails to make agentic AI more reliable, repeatable, and aligned to enterprise priorities.

This is the secondary section below the main overview, typically next to or above supporting media. It should include:

  • Supporting Statement: Agentic AI promises exponential productivity, but without controls, it can introduce inconsistency, security exposure, governance gaps, and operational complexity. Infosys Agent Control Framework provides the enterprise-grade foundation needed to scale agentic AI safely and effectively across the SDLC. By combining guardrails, workflows, enterprise context, approved integrations, and human oversight, IACF turns probabilistic AI interactions into deterministic business outcomes. The result is faster delivery, higher quality, stronger compliance, and sustainable ROI from existing AI investments, without forcing teams to change how they work.
  • Detailed Capabilities: Available as part of Infosys Topaz Fabric as well as a standalone accelerator, Infosys Agent Control Framework brings several capabilities across engineering life cycle:
    • Deterministic outcomes over ad-hoc prompting
    • Governed AI adoption using enterprise controls
    • Scalable usage through workflows, skills, and re-usable patterns across greenfield, brownfield software engineering and modernization
    • Higher productivity without platform sprawl
    • Democratized AI adoption with uniform and standardized capability distribution
    • Optimized token spend with pre-tested and peer-reviewed agentic -harness
  • Call-to-Action: Explore how Infosys Agent Control Framework can help standardize agentic SDLC delivery across requirements, design, development, modernization, testing, and operations. Engage with our team to evaluate fitment, rollout patterns, guardrails, and enterprise integration priorities. Contact us at sdlc.ai.lab@infosys.com.

Convert probabilistic AI to deterministic, governed SDLC outcomes with Infosys Agent Control Framework

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  • Focus on business outcomes, not just features
  • Modernize applications for agility and scalability
  • Rapid enterprise AI adoption without changing existing ways of working
  • Drive measurable impact across all SDLC personas
  • Improve time to market through automation and advanced analytics
  • Reduce operational AI token spending while enhancing efficiency
  • Integrate with leading agentic solutions like Github Copilot, Cursor, Amazon Q, and Claude
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Challenges & Solutions

Standardize execution using pre-built agents, structured workflows, and configurable guardrails to drive repeatable outcomes.

Embed enterprise guardrails, human critique, and controlled integrations to keep AI usage aligned with policy and quality requirements.

Use configurable multi-agent workflows and pre-approved MCP connectivity so teams can orchestrate end-to-end SDLC activities consistently.

Package proven agent patterns, skills, and prompts so teams can adopt agentic ways of working without starting from scratch.

Apply opinionated controls and structured execution paths so outputs arrive with greater consistency, traceability, and review discipline.

Unlock value from existing AI investments by operationalizing governance, collaboration, and workflow reuse at scale.

Use pre-tested, pattern-specific, and best-fit model selection for agents and skills to reduce human-agent handoffs, improve first-time-right outcomes and reduce token consumption.

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