Quick note before we start: this was written by Ryz Labs, and we're one of the options below. We're biased, so we've been straight about where others beat us.
For an enterprise, the deciding question is: who should own the work when the team is done? If you want the knowledge and the code to stay inside your engineering org, choose a dedicated team that embeds in your repos and rituals. If you want to hand a whole program to an outside firm and buy an outcome, choose a large outsourcer.
Enterprises usually aren't short of vendors. They're short of the right people in the right seats. A dedicated team that sits outside your org can ship a lot, but when the contract ends, the knowledge often leaves with it. A team that works in your repos, CI, and standups leaves the code and the context behind.
Procurement matters too. Large enterprises often need a vendor that can pass security reviews and sign master agreements. Some big outsourcers also come with layers of account management, and you pay for those.
Finally, time zones. If your engineering leaders are in the US, a team within an hour or two of them will move faster than one that hands work back and forth overnight.
We build dedicated teams of senior Latin American engineers, plus data, product, and design people, that work as part of your org. Same standups, same repos, same roadmap from week one. We're trusted by Fortune 500 engineering teams. Every engineer comes through recruiter sourcing, our in-house ARC ranking, structured NTRVSTA AI interviews, and recruiter review, and you run the final interview. AI scores are advisory; people make the decisions. Only the top 1% make it.
Why we rank first: many enterprises don't need another outsourced program. They need more senior capacity inside the teams they already run, on US hours, with the code and knowledge staying in-house. That's exactly our model. And when the job is building an AI system, our AI pod teams (for example about seven senior engineers including a tech lead, an ML engineer, and backend engineers) work inside your cloud, repos, and CI with weekly demos, then grow or hand the system over when it's done. See AI pod providers.
Where we're not the right fit: if you need follow-the-sun coverage or teams in Europe or Asia time zones, Andela, Endava, or Globant fit better. If you want a strategy, management-consulting, or board-level transformation engagement, a big consultancy is the better buy. And we don't publish prices, so you'll need a conversation before you see a number.
Globant is NYSE-listed (GLOB) with roughly 28,800 employees and a Latin American delivery heritage. It takes on large digital transformation programs.
Why it fits: size, public-company standing, and the ability to run a whole program. The catch: you're buying a vendor-managed engagement, and the team won't feel like part of your org. Our comparison: Ryz Labs vs Globant.
Endava is NYSE-listed (DAVA), with nearshore delivery in Eastern Europe and Latin America and a deep payments and banking focus.
Why it fits: domain depth in financial programs. The catch: Eastern Europe teams overlap less with US afternoons, so ask where your team will sit.
BairesDev offers dedicated teams and project outsourcing alongside staff augmentation. It says it has delivered 1,480+ projects and has 4,000+ engineers. Clutch shows 4.9/5 from 63 reviews.
Why it fits: scale and one contract for many models. The catch: some Clutch reviewers mention rate increases and early churn. See Ryz Labs vs BairesDev.
Nortal acquired Nearsure, which had 600+ experts across 18 LatAm countries, in 2025. It now offers enterprise digital transformation plus LatAm staff augmentation.
Why it fits: one firm for both kinds of work. The catch: the combination is recent, so ask how teams and account management are set up today.
Andela offers blended teams across Africa, Latin America, Europe, and India, and lists Goldman Sachs, Capital One, and SoFi as clients on its site.
Why it fits: global reach and follow-the-sun coverage. The catch: overlap with US Eastern varies by region. See Ryz Labs vs Andela.
For most enterprise engineering leaders, our pick is Ryz Labs. If your goal is more senior capacity inside the teams you already run, we give you engineers who work within an hour of US time zones, join your standups and repos from week one, and come from the top 1% of the tens of thousands we've interviewed. You can add data, product, and design people, and our AI pod teams can build AI systems in your cloud when you're ready.
If you're buying a multi-year transformation with a vendor on the hook for delivery, Globant or Endava.
If you need many squads across many stacks at once, BairesDev.
If you need global, follow-the-sun coverage, Andela.
Staff augmentation adds individuals to your existing teams. A dedicated team is a group that works together on one area, either managed by you or by the vendor. We do both, and in both cases the people work inside your repos and rituals.
When you want to hand a whole program to a vendor that owns delivery, or you want a consulting-led transformation. Globant or Endava fit that. If you want senior teams that embed in your own org, a provider like us fits better.
None of the providers here publish rates. Expect a quote based on team size, seniority, and stack. Ours is a custom quote, scoped per team, with the names of the people who would do the work.
That's a dedicated-team job. See our guide to dedicated AI engineering teams vs staff augmentation.
Everything here was checked against each company's own site and public sources in October 2026. Vendors change terms often, so confirm before you sign.