Drizz, a deep-tech startup founded by former engineers from Amazon, Coinbase, and Gojek - Asad Abrar, Partha Sarathi Mohanty, and Yash Varyani - has raised $2.7 million in seed funding. The round was led by Stellaris Venture Partners, with participation from Shastra VC, Anuj Rathi, and Vaibhav Domkundwar. This fresh capital will be used to further refine Drizz’s Vision AI testing engine, hire top engineering talent, and scale early enterprise partnerships.

Vision-Led QA for Modern Software Teams

At its core, Drizz is tackling a massive pain point in software development: brittle and outdated testing infrastructure. Traditional QA relies on scripted automation based on locators like XPaths or accessibility IDs - methods that break the moment the UI changes even slightly. Drizz’s solution? A Vision AI-powered test engine that understands UI layouts like a human would.

Instead of writing lines of fragile code, users can create tests in natural language, and the AI does the rest - navigating, validating, and adapting across both Android and iOS. Tests that once took hours to write can now be created in minutes and reused across multiple platforms without rework. It’s not just automation. It’s intelligence with memory.

How They Engineered a Defensibility Moat

While many startups rush to ship features that impress in demos, Drizz focused on something much harder: invisible infrastructure. They designed the engine to absorb layout drift, semantic variance, and even visual noise - things that typically destroy test coverage in fast-moving teams.

More importantly, they embedded their AI at the level of how developers and testers think, not just what they do. And that’s where the magic starts to compound.

Founders should take note: when your product removes recurring effort rather than adding new effort masked as convenience, it creates emotional stickiness. Drizz didn’t try to convince teams to test more - they just made it effortless to test correctly. That’s how adoption spreads quietly but aggressively.

This is the kind of product strategy that builds a long-term moat. Not with exclusive data, not with feature sets, but by embedding into a team’s natural rhythm of work and becoming the default behavior before anyone realizes it.

Traction Across High-Velocity Teams

Drizz is already in pilot use across several unicorn-stage tech firms and mid-sized global development teams. Their Vision AI model is showing 97% reliability in complex UIs, and user feedback highlights 10x faster test creation compared to legacy tools. And because the platform integrates directly into CI/CD workflows, test automation can now be part of every push - not an afterthought.

This approach is especially appealing to teams releasing weekly or even daily builds. In fast-moving environments where product surfaces change constantly, Drizz’s resilience gives developers confidence and shortens feedback loops. It also enables non-technical product stakeholders to author and review test flows, further accelerating QA cycles.

Backing From Strategic Investors

With lead participation from Stellaris Venture Partners, Drizz gains more than capital - it gains strategic guidance from one of India’s top early-stage venture firms. Stellaris has a track record of supporting SaaS startups tackling deeply technical enterprise problems. The round also includes Shastra VC and prominent angels like Anuj Rathi, who brings product leadership experience from Swiggy and Flipkart.

The investment will be used to expand Drizz’s engineering team, advance the Vision AI architecture, and build out integrations with enterprise-grade tools and platforms. As part of the roadmap, Drizz will also explore localized testing features for emerging markets and support for dynamic, gesture-based apps.

Founders With Domain Authority

The founding team’s credibility runs deep. Asad Abrar dealt with frequent QA failures at Coinbase, especially in mobile-first customer flows. Partha Sarathi Mohanty helped architect scalable data platforms at Amazon, while Yash Varyani worked on deployment resilience at Gojek. Their experience has directly shaped Drizz’s priorities: test stability, speed to deployment, and visibility across teams.

Rather than chase hype cycles, they’ve focused on building an engine that learns from thousands of interactions, not just pass/fail logic. This grounding in real-world pain and scalable architecture has given Drizz early validation from technical teams and leadership alike.

Toward the Future of Human-Centered Testing

Looking ahead, Drizz aims to extend its vision-led automation framework beyond mobile. The team is exploring testing solutions for web platforms, interactive TV apps, and even AR/VR interfaces where traditional testing logic completely breaks down. They’re also building out deeper insights for QA analytics, helping teams not just find bugs, but understand why they occurred and how to prevent them upstream.

Drizz isn’t trying to replace QA engineers - it’s helping them scale themselves. And in a world where speed and quality increasingly define a startup’s ability to compete, that’s a value proposition too sharp to ignore.