Accelerating Development through AI-Powered Test Automation - A Real-World Journey
Submitted Jan 10, 2026
Indicate the track in which your submission fits:
Track 1 AI in Software Development Life Cycle (SDLC)
Type of submission:
30 mins talk
Description
Traditional test automation breaks down at scale: test suites become brittle, coverage lags behind feature velocity, and QA teams spend more time maintaining tests than finding real issues. At IDfy, we ran into similar problems while shipping multiple times a week across APIs, UIs, and ML-based solutions. This session walks through how we designed and built an AI-powered QA automation platform that fundamentally rethinks test creation, execution, and analysis. By using LLMs to understand PRDs, visual designs (screenshots, PDFs, videos), and API specifications, we automated the generation of comprehensive test cases covering positive, negative, and edge scenarios with minimal QA overhead.
The talk goes deep into the architecture and practical implementation of a unified platform that supports API, UI, and ML test automation at different stages of product maturity and scale (0-1, 1-10, and 10-100). You’ll see how we approached context design and prompt strategies, optimized test execution with intelligent test selection, and how we integrated the platform into our development lifecycle. The session will include a live demos of our internal tool, some real production metrics (time and cost savings), and concrete patterns you can adapt immediately in your own teams.
Takeaways
- How to design and implement an AI-driven test automation platform that dramatically improves coverage, speed, and QA productivity across APIs and UIs.
- Practical techniques for using LLMs to generate, execute, and analyze tests from PRDs, visuals, and API specs: without rewriting your entire QA stack.
Audience
- Audience Level: all levels
- This session is especially valuable for QA engineers, SDETs, test automation architects, engineering managers, and product teams responsible for quality at scale. It’s also relevant for senior developers and tech leads exploring how to apply LLMs pragmatically within development lifecycles and developer workflows.
About the speaker
Manas Chaturvedi is a Tech Lead at IDfy. He has worked on building and maintaining multiple platforms at IDfy and worked on integrating AI into various systems and workflow
Comments
Hybrid access
Hosted by
Jumpstart better data engineering and AI futures
Supported by
Platinum sponsor
Nutanix is a global leader in cloud software, offering organizations a single platform for running apps and data across clouds.
{{ gettext('Login to leave a comment') }}
{{ gettext('Post a comment…') }}{{ errorMsg }}
{{ gettext('No comments posted yet') }}