Bevi manufactures connected water dispensers for commercial spaces, combining embedded firmware (ARM Cortex-M, C/C++) with a modern cloud stack (Python, Snowflake, Kafka, dbt, Looker). The tech mix reveals a hardware-forward company building toward software and data—recent projects include a fleet intelligence platform, AI-driven tools adoption, and end-to-end validation testing. Hiring skews engineering-heavy (6 of 13 roles) across firmware, embedded systems, and data, indicating active scaling of connected-device operations and troubleshooting infrastructure.
Bevi operates a subscription model for filtered water dispensers installed in commercial offices, gyms, and similar venues across the US, Canada, UK, and Ireland. The business combines hardware deployment (dispensers with embedded intelligence), operational fleet management (monitoring and diagnostics across installed units), and a backend software platform for customer administration and device orchestration. Core challenges center on scaling prototype hardware to production, managing global device fleets, automating manual purchasing workflows, and reducing troubleshooting cycle times that impact customer experience.
Embedded: ARM Cortex-M, C/C++, LabVIEW. Cloud/data: Snowflake, Kafka, Apache Spark, dbt, Looker, Fivetran. Operations: Salesforce, NetSuite, Oracle Field Service, Zendesk. Design: Solidworks, Altium Designer, MATLAB.
Boston, MA. The company was founded in 2013 and currently operates across US, Canada, UK, and Ireland.
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Bevi'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.