Distributed is a UK-based company that builds and manages "Elastic Teams" — ready-made squads of vetted senior engineers that embed in your organization or deliver fixed-scope projects. If you're an enterprise or public-sector team that needs delivery accountability taken off your plate fast, it's a genuinely strong fit. If you want to pick and direct individual AI-native engineers yourself, it's a different kind of tool.

Distributed was founded in London in 2017 by CEO Callum Adamson (LinkedIn). It's a workforce-technology company, not a freelance job board — you don't browse profiles and hire one person. You describe what you need, and Distributed assembles and manages a team drawn from its global specialist network. The company has raised around £17M to date, including a £5M Series A in 2021 and an £8M follow-on round in 2022 co-led by Downing Ventures and Guinness Ventures, with earlier backing from Fuel Ventures and Capita (Crunchbase; Distributed blog). It has served enterprise-scale clients including Capita, WPP, and the UK Ministry of Justice (Maddyness). In 2026 the company positions Elastic Teams around AI delivery, including Forward Deployed Engineers who help teams put AI into production.

Distributed runs a managed model across three moves: match specialists from a network of 3,000+, embed them into your team or run a standalone project, and handle the operational overhead — vetting, onboarding, contracts, and performance management (Distributed). The numbers they lead with are specific and worth knowing. Distributed reports a 2% acceptance rate into its specialist community, a 5-day timeline to match and embed a team, and delivery it frames as roughly 3x faster than growing a team internally. Vetting covers technical skill, cultural fit, and a communication assessment for remote collaboration; the PMO monitors performance and replaces non-performers (What Elastic Teams Are).

Speed to a working team. Standing up a vetted, managed squad in days rather than running a months-long hiring cycle is a real advantage when a program can't wait. That's the core promise, and it's a good one. Delivery accountability sits with them. Distributed owns the PMO, governance, and performance management. If someone underperforms, replacing them is their problem, not yours — meaningful for a lean team without bandwidth to manage contractors. Enterprise and public-sector credibility. Working with the likes of Capita, WPP, and the Ministry of Justice means the procurement, compliance, and governance muscle enterprises need is already in place (TechRound interview). Elastic capacity. Teams flex up and down with the work, so you're paying for capability only as long as the project needs it — genuinely useful for burst work or fixed-scope builds.

Distributed's model is a managed team, not individual hires — and that shapes what it's best for. You're buying an outcome delivered by a squad Distributed selects and directs, rather than picking and embedding one named engineer under your own management. For a scoped project you want handled end to end, that's exactly right. If your goal is to build lasting in-house AI-native capability with engineers you choose and keep, that's a different shape of need. The strength is delivery, and the fit is best when the work is a defined project rather than a permanent seat on your core team. And because the model is team-and-outcome based, verifying how a specific engineer works with AI tooling day to day is something the managed layer sits between you and — reasonable when you want the team run for you, worth naming when you want to see it yourself.

The best AI engineers usually aren't sitting on any managed bench between projects, waiting to be assigned to a squad. The ones you actually want are already working — booked on a contract somewhere else, heads-down, not in a pool to be matched. And when you hire a managed team, you don't pick who's on it or direct how they work; you take delivery of a squad someone else assembled. Nextdev reaches the top 1% of AI engineers — the ones who aren't looking. We give each a real problem to build and watch how they actually work, so you know they're AI-native because you've seen it, not because a network vetted them for you. When you want one, we employ them for you — one named engineer, on your team, under your direction. The contract, payroll, and compliance never touch your desk. With a managed team, two jobs stay on your side: trusting someone else's read on how AI-native the people are, and living with a squad you didn't choose. Nextdev closes both. You're not picking from who signed up. You're getting the engineer who never would have.

Distributed is a genuinely good answer to a specific question: how do I get a vetted, managed, accountable engineering team live in days without running the hiring or the management myself? For enterprises and public-sector programs with scoped delivery work, it's worth a serious look. If instead you want to choose individual AI-native engineers, see how they build firsthand, and keep them on your own team, that's the job Nextdev is built for.