Global payment network connecting crypto exchanges, wallets, and PSPs
Mesh operates a cross-chain payments infrastructure layer that bridges hundreds of crypto platforms into a unified network. The stack is polyglot and Web3-native (Solidity, Web3, MetaMask, WalletConnect alongside backend languages like Go, Java, Python), with heavy testing infrastructure (Playwright, Cypress, Selenium, Puppeteer) — suggesting active effort to harden user experiences in an immature ecosystem. Pain points center on liquidity, transaction volume, and turning tokenized assets into everyday payment rails, while projects reveal an M&A-driven growth strategy alongside post-launch adoption work.
Mesh is a crypto payments infrastructure company founded in 2020, headquartered in San Francisco. The platform functions as a global network layer, connecting exchanges, wallets, and payment service providers to enable digital asset payments and conversions. The company operates across the United States, India, Bulgaria, Uganda, and China, with an engineering-heavy org structure (16 engineers across 25 active roles) skewed toward senior and staff-level hires. Current priorities include scaling backend services and APIs, building out M&A partnerships, and addressing adoption and onboarding barriers in a market where liquidity and transaction volume remain structural constraints.
Backend: Go, Java, Python, C#, C++, Scala. Frontend: TypeScript, React, Redux, Node.js. Blockchain: Solidity, Web3, MetaMask, WalletConnect. Infrastructure: Kubernetes, Docker, Terraform, AWS, Azure, GCP. Testing: Playwright, Cypress, Selenium, Puppeteer, WebdriverIO.
Core priorities: global crypto payments network foundation, secure payment and transfer products, backend services and APIs, end-to-end test automation. Growth strategy includes M&A and strategic partnerships, post-launch adoption optimization, and customer success planning.
Mesh's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.