Gigster Verified Company

Gigster builds enterprise software and AI products with an AI-first engineering method that automates the full delivery lifecycle. Our AI software factory runs from discovery through to deployment, supported by a global network of more than 50,000 vetted professionals and an outcome-based commercial model.

We commit to the outcome. Every engagement is scoped around a defined result, staffed with engineers matched to the technical requirements of the work, and governed by a delivery system that has completed 1,500+ successful projects for 200+ clients since 2014.

Our capabilities cover AI-accelerated product development, custom AI agent development, artificial intelligence, data engineering and data quality, platform engineering, cloud architecture and DevOps, innovation, design and UX, and modernization and optimization. Automated discovery turns requirements into machine-optimized specs. Specialized agents build across parallel work streams. Testing runs automatically with bug loopback. Deployment moves through approval gates, and governance and validation sit over every stage with human oversight.

Clients typically come to us with the same pressures: limited internal engineering bandwidth, long hiring cycles for specialist talent, mounting technical debt, and leadership asking for AI results that generic coding tools have not produced. Organizations that apply AI only to code generation see 10 to 15% improvement. Across the full lifecycle it reaches 20 to 45%, and closing that gap is the whole point of our method.

Founded in 2014 and headquartered in Texas, Gigster works with professionals in more than 130 countries. Published case studies include a computer vision community platform for Canon, a multilingual research analysis application for GSK, a cognitive AI platform for Vodafone that lowered operating costs by an estimated $15M a year, and a multi-year digital transformation program for Harley-Davidson covering more than 40 projects. We work with CTOs, CIOs, and engineering and product leaders at mid-market and enterprise organizations who need production-ready software on a predictable timeline.