CRED, India’s leading fintech platform for creditworthy users, has introduced CRED codelens, an advanced AI-driven intelligence layer designed to transform how engineering teams build, debug, and ship software. Built using Amazon Bedrock, the platform is already delivering up to 4x acceleration in engineering productivity, signaling a major shift toward agentic AI in enterprise development.
As CRED scaled to support more than 20 business verticals, 2,000 repositories, and over 500 microservices, managing engineering complexity became increasingly challenging. Traditional documentation methods struggled to keep pace. CRED codelens addresses this by creating a central, continuously updated source of truth one that gives every line of code full context across systems, architecture, and workflows.
The platform goes beyond static documentation. Starting from the user-facing application, it maps complete end-to-end request flows, tracing how services, APIs, and systems interact across the organization. Every code commit triggers automated analysis, generating documentation and indexing it into a vector database within 30 minutes ensuring real-time visibility into evolving systems.
“CRED has reimagined how engineering teams operate at scale by turning its entire codebase into living knowledge with 400+ AI agents accelerating decisions across engineering, product, and operations.”
— Kiran Jagannath, Head of FSI and Conglomerates, AWS India and South Asia
At its core is an agentic AI layer orchestrating more than 400 specialized agents. These agents handle a wide range of tasks, including code reviews, debugging, test generation, infrastructure troubleshooting, and knowledge retrieval. By embedding intelligence directly into development workflows, CRED codelens transforms weeks of engineering effort into hours.
Amazon Bedrock plays a central role by providing a unified, governed API layer that intelligently routes tasks to the most suitable AI models. It also ensures enterprise-grade security, compliance, and cost controls critical for scaling AI adoption across large organizations.
The impact has been significant. Within a year of deployment, over 500 users across engineering, product, data, and operations teams are actively using the platform. Engineers now ship features and resolve issues up to four times faster, while CI/CD debugging efforts have reduced by 40%. The system has achieved 74% code segment coverage and 92% endpoint visibility, with high accuracy in query responses.
Swamy Seetharaman, AI enabler at CRED, emphasized the broader transformation: the platform turns code, conversations, and operational context into “living knowledge” that teams can query and act on instantly improving decision-making even before development begins.
Beyond engineering, the platform is driving value across teams. Business units use it for campaign planning, operations teams for customer workflows, and security teams for compliance and threat modeling.
CRED codelens represents a new paradigm where AI is not just a tool, but an integrated intelligence layer powering every aspect of software development and enterprise operations.