Mesh runs a payment network that routes digital asset payments and conversions across exchanges, wallets and PSPs. Its polyglot stack (Go, Rust, Scala, Solidity, TypeScript) on Azure Kubernetes Service with Terraform, now adding Terragrunt, points to infrastructure-as-code maturing as routing logic scales. Director-heavy hiring across sales, legal and compliance, plus APAC regulatory pain points, signals a push from build mode into regulated geographic expansion.
Notable leadership hires: Sales Director, Head of Design, Compliance Director
Mesh, founded in 2020 and headquartered in San Francisco, operates a network that connects crypto exchanges, wallets and payment service providers so digital assets can be used for payments and conversions. It sells to merchants and PSPs through a Mesh Pay sales pipeline, alongside integrations with centralized exchanges and web3 wallets. The company has 51–200 employees and is privately held. It hires across the United States, India, Bulgaria, Brazil, Japan and Uganda, spanning engineering, sales, legal, product, design and security.
Mesh uses Go, Rust, Scala, Java, Python, TypeScript, React and Solidity, running on Azure Kubernetes Service with Terraform, Datadog and CircleCI. It is adopting Terragrunt; go-to-market tools include Salesforce, HubSpot and Gong.
Mesh is headquartered in San Francisco, California, and hires in the United States, India, Bulgaria, Brazil, Japan and Uganda.
Mesh is building its global crypto payments network, standardizing and scaling routing logic, integrating centralized exchanges and web3 wallets, building a compliance risk assessment, and expanding into APAC.
Other companies in the same industry, closest in size
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.
