Scanbase vs Browser Use
Side-by-side comparison of AI visibility scores, market position, and capabilities
Computer vision API reading at-home lateral flow test photos for 40+ test types; $3M revenue with 5-person team enabling telehealth result verification for COVID, flu, and STD tests.
About
Scanbase is a healthcare technology company providing a computer vision API that enables medical and consumer health companies to analyze at-home diagnostic test results through smartphone photos — reading lateral flow tests (the strip-based rapid tests used for COVID-19, flu, RSV, strep, pregnancy, and STDs) and returning structured results that can be recorded in health apps, telehealth platforms, and clinical systems. Founded in 2022 in San Francisco and a Y Combinator W23 graduate, Scanbase raised $2.5 million from Dupe Ventures and Liquid 2 Ventures, achieving $3 million in revenue in 2024 with a 5-person team.\n\nScanbase's API integrates into health apps, telehealth platforms, and employee health programs — when a user takes a photo of their at-home test strip, the API analyzes the image to detect control line and test line presence/intensity, returning a validated result (positive, negative, invalid) with confidence scores. This replaces manual result entry (prone to misinterpretation) and photo review by human staff with automated, consistent computer vision interpretation. The API covers 40+ test types including COVID-19, flu A/B, RSV, pregnancy, and various STD tests.\n\nIn 2025, Scanbase competes in the digital diagnostics and at-home testing technology market with Sight Diagnostics, LumiraDx, and platform-specific solutions built by major diagnostics companies for at-home test result interpretation. The COVID-19 pandemic permanently expanded at-home testing adoption, creating a large installed base of consumers comfortable with lateral flow tests and a growing need for digital result capture and verification in telehealth workflows. The $3M ARR with a 5-person team demonstrates exceptional capital efficiency. The 2025 strategy focuses on expanding the test coverage library, growing integrations with telehealth and employee health platforms, and adding verification workflows for use cases where authenticated test results are needed (insurance claims, return-to-work programs).
Browser Use is an open-source Python library that enables AI agents to control web browsers, making it easy for LLMs to interact with any website through a clean, model-agnostic API.
About
Browser Use is an open-source project that provides a Python library allowing AI agents and large language models to control web browsers as a tool. The library sits between LLM APIs and browser automation frameworks like Playwright, providing a clean, model-agnostic interface that makes it straightforward for AI agents to navigate websites, fill forms, extract information, and complete multi-step web tasks without requiring developers to write custom browser control code.
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