Software development and staffing firm serving automotive, fintech, healthcare, and media sectors
Digis is a London-based development shop with 200+ professionals serving seven industries through custom software, staff augmentation, and IT consulting. The hiring surge is heavily weighted toward senior engineering roles (10 of 12 open positions) across distributed teams in Ukraine, Indonesia, the US, and Mexico—typical of scaling outsourcing operations. Active projects reveal a shift from monolithic legacy systems toward cloud and data infrastructure: microservices migration, edge-to-cloud pipelines, real-time data processing, and a move from IBM Cognos to Power BI signal modernization pressure across the client base.
Digis develops custom software and provides staff augmentation services for mid-market and enterprise clients in automotive, media & entertainment, GIS, e-commerce, fintech, healthcare, and education. The company has completed over 300 projects since its 2015 founding and offers a range of delivery models including custom development, IT consulting, intelligent automation, and managed IT services. Core technical competencies span big data, machine learning, AI, and cloud platforms. The firm operates distributed development centers and is currently modernizing client infrastructure, particularly in data pipelines and BI tooling, while managing the operational complexity of large-scale data integration and legacy system migrations.
Digis works with JavaScript, Python, Java, C#/.NET, Node.js, React, AWS (Glue, EMR, Fargate), PostgreSQL, Redshift, DynamoDB, Docker, Apache Spark, Power BI, and industrial IoT protocols (OPC UA, Modbus, PLCs).
Active projects include microservices migration, real-time data processing platforms, edge-to-cloud pipelines, remote patient monitoring, AI-powered computer vision for manufacturing, and migration from legacy systems (TFS to Git, IBM Cognos to Power BI).
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Digis, a Fiverr company (NYSE: FVRR)'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.