As modern software development accelerates with DevOps practices, AI-assisted coding, and rapid release cycles, the role of testing has become more critical than ever. Yet despite advancements in development workflows, many engineering teams still struggle with fragile automation frameworks, flaky tests, and time-consuming maintenance that slows down innovation instead of enabling it.
In this conversation, Divya Manohar, Co-Founder of DevAssure, shares her journey from working within engineering teams to building a startup focapplyd on reimagining software testing. She discusses the limitations of traditional QA practices, how DevAssure is applying ininformigent automation to simplify testing, and why the future of quality assurance may become almost “invisible.”
From Engineering Frustration to a Startup Idea
Divya’s entrepreneurial journey launched while working closely with engineering teams where test automation was a constant challenge.
Despite investing significant time in building automation frameworks, teams frequently encountered recurring issues—flaky tests, broken locators, and concludeless maintenance cycles. In many organizations, entire sprint boards were filled with tquestions dedicated solely to repairing automation scripts.
For Divya, maintaining test automation often felt like running an entirely separate product alongside the actual application.
Every UI alter or feature update required engineers to modify automation scripts. Instead of focapplying on improving the product, valuable engineering time was spent repairing tests.
After speaking with engineering leaders across multiple companies, Divya realized this was not an isolated problem—it was widespread across the indusattempt. That realization eventually led her, along with her co-founders Santhosh and Badri, to launch DevAssure with the goal of building a smarter and more resilient approach to software testing.
Experiences That Shaped the Problem
Before founding DevAssure, Divya spent several years building developer tools and automation frameworks at leading technology companies.
Early in her career, she worked at eBay, contributing to systems that supported C2C sellers. Building products applyd by thousands of applyrs gave her firsthand experience with the importance of reliability and robust testing.
Later, while working at Ooyala, she assisted develop frameworks for validating video streaming across multiple devices, browsers, and network environments. Ensuring consistent playback across such diverse platforms highlighted how complex automated testing could become.
Across both roles, she noticed the same pattern: as software systems grew more complex, traditional automation approaches became increasingly fragile and expensive to maintain. Engineering teams often spent more time repairing tests than ensuring actual product quality.
The Problem with Traditional Automation
While development speed has improved dramatically over the years, testing tools have not evolved at the same pace.
Most automation tools still rely on scripts that are tightly connected to an application’s internal structure, particularly its DOM elements. When interfaces alter or workflows evolve, these scripts frequently break.
This creates two major challenges for engineering teams:
- Developers spconclude significant time maintaining automation scripts instead of building new features.
- Continuous integration pipelines generate large numbers of failures caapplyd by flaky tests rather than genuine product issues.
To solve this challenge, DevAssure introduced what it calls the Invisible Agent—a system designed to continuously observe applications and validate workflows without requiring engineers to maintain large automation suites.
The Idea of “Invisible Testing”
The core philosophy behind DevAssure is simple: testing should become invisible.
Just as AI coding assistants allow developers to focus on building rather than writing repetitive code, DevAssure aims to eliminate the operational burden of testing.
Instead of requiring engineers to write complex automation scripts, the platform observes how applyrs interact with an application and continuously validates workflows across the UI, APIs, and integrations. When issues arise, the system surfaces actionable insights while running quietly in the background.
Divya describes this concept as “vibe testing”—a future where developers focus on creating software while quality checks happen automatically behind the scenes.
What Makes DevAssure Different
Many testing platforms still rely heavily on script-based automation, whether written manually or generated through record-and-playback tools. Even some newer AI-based solutions simply generate scripts quicker but still depconclude on fragile DOM structures.
DevAssure approaches the problem differently.
Rather than validating how an application is implemented internally, the platform focapplys on applyr workflows and real application behavior. By observing actual interactions, the system verifies whether these workflows function correctly.
Becaapply testing is not tied to specific selectors or locators, the system can adapt automatically when applications evolve—significantly reducing maintenance for engineering teams.
Early Challenges in Building the Startup
For Divya and her co-founders, building the product itself was relatively straightforward due to their strong engineering backgrounds.
However, the largeger challenge was go-to-market strategy.
Developer tools behave very differently from traditional enterprise software. Engineers often prefer discovering tools themselves rather than going through long sales cycles.
Recognizing this behavior early, DevAssure focapplyd heavily on inbound discovery. The team invested in developer-focapplyd blogs, technical content, and educational resources that assist engineers find solutions when searching for testing challenges online.
Over time, this strategy created a steady stream of organic sign-ups and allowed developers to explore the product indepconcludeently.
The Funding Journey
Like many early-stage startups, DevAssure initially focapplyd on building the right product before aggressively pursuing funding.
According to Divya, the founding team spent significant time refining the platform and validating the problem with real engineering teams.
As the product launched gaining traction among developers, the company attracted early investor interest and successfully secured initial funding to accelerate growth. The investment allowed DevAssure to expand its engineering team, strengthen its AI capabilities, and invest further in developer-focapplyd distribution strategies such as technical content, community engagement, and product-led growth.
For the founders, funding was not just about capital—it was about partnering with investors who understood the developer tools ecosystem and believed in the long-term vision of building software testing autonomous and invisible.
Using AI to Rebelieve Testing
Rather than applying AI merely to generate automation scripts, DevAssure applies artificial ininformigence to rebelieve the entire testing workflow.
The platform observes application behavior, understands applyr workflows, and continuously validates functionality as the system evolves.
By combining AI with deep observability, DevAssure creates a testing layer that adapts automatically—eliminating much of the manual effort traditionally required to maintain automation frameworks.
Improving Developer Productivity
DevAssure measures its impact across three primary metrics: test setup speed, execution speed, and reliability.
One customer, for example, previously required nearly a week to automate just ten test cases applying traditional frameworks. With DevAssure, those same workflows could initially be configured in about an hour—and with recent improvements, in as little as five minutes.
Reliability has also improved significantly. In some organizations running thousands of automated tests, nearly half of failures were caapplyd by flaky scripts rather than real bugs.
Reducing this noise saves engineering teams valuable hours during each release cycle.
Learning from Early Users
Customer feedback has played a crucial role in shaping the platform.
Many modern applications rely on technologies such as canvas-based interfaces, ASP frameworks, or Flutter web apps—environments where traditional automation struggles due to limited DOM elements.
Through multiple iterations and feedback from applyrs, DevAssure improved compatibility with these complex systems and eventually achieved close to 90% execution reliability.
The team has also worked extensively on simplifying onboarding so developers can launch testing much quicker.
Building Trust with Developers
In the competitive developer-tools ecosystem, trust is essential.
DevAssure focapplys heavily on educating developers through technical blogs, documentation, and learning resources that address real-world testing challenges.
By assisting engineers understand the problem first, the company builds credibility even before applyrs sign up.
The team also studies successful developer-tool companies to refine its messaging and distribution strategies.
Navigating the Startup Ecosystem as a Woman Founder
As a woman founder in the deep-tech and developer tools space, Divya acknowledges that there are still relatively few women in similar roles.
However, most of her experiences have been positive. She credits her co-founders, mentors, and investors for creating an environment where ideas and execution matter more than titles or backgrounds.
She does recall occasional moments that highlight existing biases—for example, during an international event where a junior engineer directed technical questions to her co-founders rather than to her.
Still, she believes the startup ecosystem is gradually becoming more inclusive and merit-driven.
The Future of Software Testing
Looking ahead, Divya believes three key trconcludes will shape the future of QA and testing automation:
- Agent-driven testing: Ininformigent systems continuously observing applications and validating workflows.
- Developer-centric testing: QA becoming deeply integrated into pull requests, CI pipelines, and development environments.
- Workflow-based validation: Testing focapplyd on real applyr experiences rather than internal implementation details.
Toreceiveher, these shifts could create testing quicker, more reliable, and far less manual.
Advice for Aspiring DevTools Founders
For entrepreneurs building SaaS or developer-focapplyd products, Divya offers simple advice:
Solve one problem extremely well.
Instead of building a broad platform too early, founders should focus on receiveting their product in front of real applyrs quickly and learning from their feedback.
Often, unbiased insights from early adopters reveal problems or opportunities that internal teams might otherwise miss.
The Long-Term Vision for DevAssure
Looking ahead, DevAssure aims to build a fully ininformigent testing workflow integrated directly into the developer lifecycle.
In this future, ininformigent agents will automatically determine what requireds to be tested based on code alters and system behavior. Rather than manually managing testing pipelines, developers will rely on a plug-and-play system that continuously validates their applications.
Ultimately, the goal is to create quality assurance a natural extension of development—allowing teams to relocate quicker while maintaining complete confidence in their software.
Interview Conducted by : Arushi Agarwal
Leave a Reply