The funding brings fresh support to a company trying to solve the problems of vast submission volumes, limited talent, and tools that haven’t kept pace with the insurance industry’s demands. 

The round was led by Stellaris Venture Partners, with backing from Y Combinator and Arali Ventures.

Pibit.AI’s founder Akash Agarwal watched the slow, paperwork-heavy world his father worked in and later saw tech-driven industries move faster while underwriting barely changed. That contrast eventually impacted the central idea behind the business.

At the centre of the company’s features is CURE, a consolidated environment that takes an application from raw submission to risk-rated output. It brings together document intelligence, triage tools, research layers, risk modelling and workflow management in one system, rather than leaving underwriters to jump between fragmented tools. 

The platform includes ClearCURE, DocumentCURE, ResearchCURE, RiskCURE and WorkflowCURE, each responsible for a step that used to rely heavily on manual effort.

Agarwal says the aim isn’t to remove the underwriter but to give them a system that can be trusted. “Pibit.AI was built around one idea: that AI should empower underwriters, not replace them,” he said.

“Too many systems prioritise speed over trust. We’re building something that’s transparent, explainable, and decision-ready – a system that gives underwriters confidence in every output while helping them move faster than ever before.”

Companies using the platform are already reporting a change in how much work their teams can handle. Several clients, including HDVI, Shepherd Insurance, RMS Insurance Brokerage, Kinetic and Method Insurance Company, have seen underwriting cycles cut by as much as 85%, alongside increases in premium per underwriter and improvements in loss ratios. 

For businesses dealing with high submissions, these margins can determine whether growth is sustainable.

Operational leaders inside these firms say the benefits are not theoretical. Michaela Morrison, COO of Method Insurance Services, explained the impact clearly: “As a fast-moving company scaling our operations nationally, Pibit.AI played a key role in ensuring we achieved that growth without losing control.” She added, “Our outcomes aren’t magic; they are the direct product of thoughtful engineering and a team that genuinely listens.”

Kinetic’s CEO, Adam Price, also pointed to the expansion the system made possible. “Pibit.AI helps us to handle more than a billion dollars in submissions on an annual basis without scaling our overhead costs, and grow our business by close to 100% in premium because we’re able to get those looks and quotes up and running.”

For investors, underwriting is too important to remain slow or inconsistent. Stellaris Venture Partners’ Alok Goyal said the platform addresses that directly. “Underwriting has long been constrained by manual reviews, inconsistent data and tools that haven’t kept pace with rising submission volumes,” he said. 

“With CURE, Pibit.AI automates and unifies these workflows, improving accuracy, reducing costs and accelerating quote generation to drive higher revenue. We’re excited to partner with Akash and lead Pibit.AI’s Series A round as it scales.”

Pibit.AI now employs more than 125 people and plans to deepen its infrastructure, expand integrations and build more advanced risk models.

The company also intends to broaden its API capabilities and secure additional data partnerships, making the platform adaptable to new lines of insurance and emerging risk categories.

The startup’s vision-based automation platform replaces fragile test scripts with natural language prompts, cutting testing time from days to minutes.

Led by Stellaris Venture Partners and Shastra VC, the round included participation from Anuj Rathi (ex-CBO, Cleartrip) and Vaibhav Domkundwar. The funding will fuel the continued development of Drizz’s Vision AI engine, enhancing its speed, accuracy, and usability across enterprise environments.

“Every app team is accelerating with AI, but testing still lags behind,” said Asad Abrar, co-founder and CEO of Drizz. “During my time as a product manager at Coinbase, locator-based tests broke with every UI shift, turning QA into a bottleneck. That frustration led us to build Drizz—an AI-native platform that keeps up with modern development and actually delivers confidence at scale.”

Drizz allows teams to write, run, and maintain end-to-end test coverage using plain English prompts instead of fragile code. The system evaluates apps visually, just like a real user, eliminating the need for locator selectors, manual updates, or separate test suites across devices. 

Its AI doesn’t rely on brittle xPath locators or accessibility IDs, and instead interprets the UI visually, adapting automatically to screen density, hardware differences, and device-specific behaviours.

“Drizz’s multimodal engine understands the screen context and layout, even when elements are dynamic and constantly changing,” said Yash Varyani, co-founder and CTO of Drizz. “Where traditional testing may break, Drizz remains stable and flags bugs with detailed log intelligence that pinpoints the root cause. This ultimately saves testing teams both time and guesswork.”

Developers and QA teams can run tests across iOS and Android using one shared suite, generate test flows in natural language, and rely on self-healing automation that stays stable across UI changes. 

The platform is built for production readiness, with support for CI/CD pipelines, real device cloud testing, real-time reporting, and full enterprise-grade compliance. Drizz supports a comprehensive range of testing needs – including UI, Functional, API, multi-app, and end-to-end testing.

The system also supports field-level fallback logic and step-by-step execution that boosts reliability and makes debugging easier – even on the most complex interfaces. This opens doors for non-technical stakeholders to actively contribute test scenarios, with no coding required. 

It streamlines collaboration and helps teams move efficiently. In early deployments, Drizz has helped teams achieve over 97% test accuracy and reduce test creation time by a factor of 10.

The company is already working with multiple unicorns globally and is seeing strong developer engagement, with users spending an average of 15 hours per week writing and executing test cases. 

Looking ahead, Drizz plans to extend its vision-based infrastructure toward testing for visually rich and highly interactive environments, areas where traditional locator-based tools can’t operate due to dynamic interfaces and the lack of deterministic DOM structures. 

“We want to redefine how quality software is shipped in the age of AI,” said Partha Mohanty, Drizz co-founder and CPO. “With Drizz, test authoring becomes effortless, execution highly accurate, and bug resolution near-instant – all powered by intelligent automation.”

Alok Goyal, partner at Stellaris Venture Partners commented: “AI is fundamentally changing how software is built, tested, and deployed. In an era where more software needs to be shipped even faster than ever, software quality has become the biggest bottleneck. Drizz is therefore tackling one of the most critical parts of the software development cycle with a unique, vision-first approach. 

“By solving real QA pain points and bringing non-technical users into the loop, Drizz is reimagining mobile application testing with AI. We’re thrilled to partner with them on this journey.”

With AI redefining the speed and complexity of software creation, Drizz is supercharging teams to test faster and ship confidently.