Watermelon is an AI-driven software reliability platform that enables enterprises to conduct no-code functional and API testing, chaos engineering, and service level objective (SLO) management throughout the application lifecycle. The platform addresses the challenges of system reliability by providing predictive insights and automated remediation to enhance application performance and customer experience.
Funding
$3.6M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Enterprises face challenges in maintaining software reliability due to unvalidated architectures, code developed without a focus on reliability, complex and siloed testing processes, and a disconnect between release cadence and system stability. Reactive observability and incident response further exacerbate these issues, leading to unmeasured impacts on customer experience.
Solution
Watermelon provides an AI-driven, no-code software reliability platform that enables enterprises to conduct functional and API testing, chaos engineering, and service level objective (SLO) management throughout the application lifecycle. The platform simplifies reliability across pre-production and production environments, addressing challenges for various personas within the application lifecycle. By offering predictive insights and automated remediation, Watermelon enhances application performance and customer experience, ensuring alignment with business objectives. The platform's modular design allows users to address specific reliability needs with AI-driven solutions.
Target Audience
The primary target audience includes engineering, operations, and testing teams within enterprises that require software to fuel their businesses and seek to ensure reliable digital systems.
Features
- No-code functional testing for web, mobile, desktop, and legacy applications, incorporating observability-driven testing concepts.
- AI-powered, no-code API testing with support for data-driven and chained API testing, including auto-generation of test cases.
- Chaos Engineering module with over 180 failure injection scenarios across on-premise and cloud platforms (VM, Kubernetes, AWS, Azure, GCP).
- SLO Management platform leveraging data across APM, log ingestion tools, databases, and cloud monitoring systems to proactively manage business journey reliability.
- Predictive capacity management and auto-remediation capabilities.
- Single unified platform addressing the siloed nature of the SDLC.