The 2026 nearshore AI landscape
Nearshore AI development companies are firms in Latin America that staff or build AI engineering capacity for US teams while working inside US business hours. By 2026 the field has split into three shapes, and naming the split is the fastest way to read it.
- Scale outsourcers. BairesDev, Globant, Softtek, and Encora. Thousands of engineers, enterprise process, AI as one service line among many.
- Vetted marketplaces. Revelo, Tecla, Turing, ThirstySprout, and nCube. Large pre-vetted benches matched to you, usually framed as a top-X-percent pool.
- Embedded specialists. Smaller curated benches, deeper integration, and an AI-native focus rather than a general dev shop with an AI page.
The arbitrage that drives the whole category is real and measurable. A US machine learning engineer carries an average base salary of $188,764, ranging from $113,990 to $312,589, based on 5.2k salaries updated June 15, 2026, per Indeed. A senior LATAM AI engineer costs a fraction of that fully loaded.
The stated savings cluster tightly across the field, which is a good sign the band is honest. Revelo cites 30 to 50% over US hires, on its homepage. Tecla cites 40 to 60%, on its homepage. Globy reports roughly 40% lower engineering costs, on its homepage. One documented Tecla client case reports a 52% reduction in salary costs, on the Tecla blog. The honest read is 30 to 60% lower fully-loaded cost than US hires, stated as a range across independent providers rather than one guaranteed figure.
The deeper point is that the price gap is now a commodity. Almost every LATAM provider quotes a version of it. What actually separates these firms is how they vet, how deep their AI specialisation runs, and what the contract locks you into. That is the lens this review uses.
How we evaluated each provider
Every provider below is scored on the same six criteria. We only state a number when a public source backs it. Where a firm does not disclose its AI bench size, vetting funnel, or per-engineer pricing, we say so instead of guessing.
- Engagement model. Staff augmentation, dedicated team, managed embed, recruiting marketplace, or studio delivery. These are not interchangeable.
- AI specialisation depth. Whether AI is a named, staffed practice with specifics, or one service line inside a general dev shop.
- Pricing transparency. Whether any rate is published. This is the industry's weakest spot and the cleanest differentiator.
- Vetting funnel. The selection process and any disclosed pass rate.
- Geographic coverage. Which countries, and whether the footprint is genuinely nearshore for a US buyer or partly offshore.
- IP and procurement posture. How the firm handles contracts, IP assignment, and compliance.
The single most useful filter is the AI-specialisation one. Most nearshore AI development companies are generalist staffing shops that added an AI service line, and the marketing rarely makes that obvious. Reading the six axes together is how you tell a true AI specialist from a staffing business with an AI landing page. For the regional and cost context behind these picks, see our guide to hiring LATAM AI developers.
The 10 providers
Ten providers, scored honestly. Each profile leads with verified numbers from the firm's own pages, then states the strength and the catch.
BairesDev
BairesDev is the scale play. The firm reports 4,000+ people, having vetted over 1.5 million candidates, operating across 40+ countries since 2009, with 91% customer satisfaction and average client relationships of 3+ years, per its about page. It positions on the top 1% of talent, with LATAM hubs in Argentina, Brazil, Colombia, and Mexico, and lists staff augmentation, dedicated teams, software outsourcing, and AI Development among its services, also on that page. Its AI-specific bench size, AI vetting funnel, and per-engineer pricing are not publicly disclosed. Read: strongest on scale and enterprise process, weakest on AI-native specialisation and pricing transparency.
Revelo
Revelo leads on bench breadth. It reports 400,000+ vetted software engineers, accepting only the top 2%, across Argentina, Brazil, Colombia, Mexico, and Peru, per its homepage. It claims 30 to 50% savings over US hires, a curated shortlist in 72 hours, and 14 days average time to hire on month-to-month terms with no upfront fees and no lock-ins, same page. It handles payroll, benefits, taxes, and compliance with no local entity required, also there. The genuine AI signal is 500+ developers for LLM post-training across RLHF, SFT, and DPO, on its AI engineers page. Read: the largest stated vetted LATAM pool with a real LLM-ops slice, though the AI offering skews toward data labeling and post-training rather than embedded product engineers. Per-engineer AI pricing is not disclosed.
Tecla
Tecla brings a long, verifiable track record. It reports eleven years, 500+ companies, and 50,000+ vetted professionals across 18+ countries in the US and LATAM, and was named to the Inc. 5000, per its homepage. Its vetting runs four stages from AI screen to technical assessment to recruiter interview to a reference check with 3+ references, and it markets your time zone at 40 to 60% lower cost, with an AI roster spanning LLM developers, prompt engineers, computer vision, and generative AI specialists, same page. One client case documents a 52% reduction in salary costs, on the Tecla blog. Read: best verified track record plus a clean four-stage funnel. AI talent is a roster category here, not an exclusive specialisation.
Howdy
Howdy is the boutique, retention-heavy option. It reports interviewing 100,000+ people per year, accepting the top 1%, with 98% retention, per its homepage. It runs 12 LATAM cities across Argentina, Brazil, Chile, Colombia, Mexico, Peru, and Uruguay, plus Austin, and staffs 31 full-time psychologists trained as recruiters alongside coaches with 10+ years of engineering management experience, same source. A cost example cites $97K in savings, though no transparent rate card is published, also there. Read: real vetting rigor and retention with a deep integration and coaching model. Howdy spans software, data, DevOps, design, and PM, so it is integration-led rather than AI-pure, and per-engineer pricing is not disclosed.
nCube
nCube is the engagement-model menu. It reports 200,000 developers in network, 95% holding a university degree, four engagement models from staff augmentation to R&D center, 2 to 4 weeks to launch a team, and 86% project-lifetime retention, per its homepage. Honest caveat: offices sit in Warsaw, Sao Paulo, London, and Kyiv, so nCube is anchored in Central and Eastern Europe with Sao Paulo as its only LATAM hub, same page. For a US client, only that Sao Paulo arm is genuinely nearshore. AI appears in the tech stack without detailed specialisation, and no pricing is disclosed.
Encora
This slot needs a caveat. As of 2026, encora.com redirects to coforge.com, observed via redirect at Encora. The destination site blocks automated fetches, and the acquisition could not be confirmed from an official or reputable third-party source. The only defensible statement is the observable one. The Encora brand appears to be in transition, so we do not publish a deal value or headcount for a change we could not verify. Read: historically a credible regional development shop, but verify the current entity, ownership, and AI staffing directly before shortlisting.
Globant
Globant is enterprise digital at studio scale. Founded in 2003, it reached 20k employees across more than 30 countries and has been NYSE-listed since 2014 under GLOB, naming clients such as Google, Electronic Arts, and Santander, per its about page. On AI it runs multiple vertical AI Studios and launched Globant AI Agents and immersive Playgrounds in 2024, same page. Read: a real, funded AI org, but it sells large-scale digital transformation engagements rather than embedded individual AI engineers. That is a mismatch for a founder or CTO who wants 1 to 3 engineers in the codebase. Per-engineer pricing and a vetting funnel are not disclosed.
Softtek
Softtek is the original nearshore brand. It reports 16,000 global experts, says it invented the nearshore model, and is a Mexican corporate entity led by Executive President and Chair Blanca Trevino, per its homepage. Its AI portfolio includes Softtek GenAI and FRIDA AI for Software Engineering, and it was named a Challenger in the 2025 Gartner Magic Quadrant for Custom Software Development Services, same source. Read: a credible Mexico-anchored enterprise option with real GenAI tooling, but engagement is enterprise services, not flexible single-engineer placement. No public per-engineer pricing or AI vetting funnel.
ThirstySprout
ThirstySprout is an AI-forward matching engine. It reports prescreening over a million candidate profiles, keeps 1000+ vetted experts on demand, cites a 90% success rate with candidates within 48 to 72 hours, specialises in AI and software engineering talent, and claims to cut hiring costs by 50% or more, per its homepage. Clients listed include Google, Intel, Zapier, Twitch, Uber, and Meta, same page. Read: genuinely AI-first and fast, but a recruitment and matching layer that is global rather than LATAM-specific. Once the hire is made, involvement largely ends and the client owns onboarding, management, and retention.
FutureProofing.dev
FutureProofing.dev is the senior-AI specialist embed. It contacts 2,000+ engineers monthly and accepts 12, a 99% rejection rate, through a 5-stage funnel that includes a paired AI challenge testing AI-native working style, not just AI knowledge, with Jess Mah as the final filter on every accepted engineer. Engineers join your codebase, GitHub, Slack, Linear, and ceremonies directly, Claude Code Max-fluent from day 1 on a sponsored 20x Claude Code Max seat, working in Claude, Cursor, LangSmith, and Pinecone by default rather than as generalists who also do AI. Pricing is a flat $13.5K/mo all-in, with no equity, no lock-in, and no conversion fees. Read: the only firm in this set whose entire model is senior-AI-only and embedded. The funnel math and the published flat rate are the proof points.
How LATAM compares to offshore and onshore
LATAM nearshore wins on timezone, costs less than onshore, and gives up the deepest discounts that zero-overlap offshore offers. That is the honest three-way tradeoff, and the numbers behind it are sourced and consistent.
Cost versus onshore. The onshore anchor is a US machine learning engineer base of $188,764, per Indeed. Provider-stated LATAM savings converge against it. Revelo claims 30 to 50%, on its homepage. Tecla cites 40 to 60%, on its homepage. Globy reports roughly 40%, on its homepage. That is a 30 to 60% lower fully-loaded cost than US hires, stated as a range across independent providers rather than a single guaranteed figure.
Timezone is the structural LATAM edge. Providers uniformly position the region for real-time US-hours overlap. Tecla advertises the same time zone as the US, on its homepage. Revelo frames it as working your hours, on its homepage. Globy markets US time zone coverage, on its homepage. That contrasts with nCube, whose base is primarily Central and Eastern Europe, per its homepage. FutureProofing.dev makes the sharpest version of the claim with a 0 to 3 hour US Eastern offset and full overlap with US Pacific. For a structured side-by-side, see our offshore versus nearshore AI development breakdown.
Vetting selectivity is the noisiest axis to compare, because the claims are marketing rather than audited:
- Top 1%. Claimed by Howdy, BairesDev, and Turing.
- Top 2%. Claimed by Revelo.
- 4% pass rate. Cited by Globy.
- 99% rejection. Roughly 0.6% accepted at FutureProofing.dev, which publishes the funnel math of 12 of every 2,000 candidates rather than a top-X adjective.
The honest caveat. Top 1% is a claim made across the field, not an independently audited figure. Treat the acceptance rate as a directional signal and weight the funnel detail and engagement model more heavily. For the full cost model across in-house and outsourced paths, see our AI development cost comparison.
How FutureProofing.dev positions in LATAM
Almost no one in this set is an AI-native embed specialist, and that is the FutureProofing.dev category. It is not the cheapest LATAM option. It is the most specialised one, and the positioning is deliberate.
Against the scale shops like BairesDev, Globant, and Softtek, the difference is structural. Those providers field thousands of engineers with per-engineer pricing that is rarely published, per their sites. FutureProofing.dev runs a curated senior-AI bench at a flat $13.5K/mo all-in per engineer, embedded directly into the client team rather than delivered from a separate center.
Against the marketplaces like Revelo, Tecla, and ThirstySprout, the difference is what happens after the match. Those are matching and placement layers, and several end their involvement once the hire is made. Revelo has a real 500-developer LLM-ops bench, per its site, but FutureProofing.dev is a managed model where AI is the specialty, not a roster category. Engineers are Claude Code Max-fluent on day 1, and a 7-business-day replacement at no extra cost means an underperformer is swapped without penalty.
Against Howdy, the closest analog on integration depth, the difference is the AI gate. Both embed and coach, and Howdy reports 98% retention, per its site. FutureProofing.dev is AI-pure, and its 5-stage funnel includes a paired AI challenge with Jess Mah as the Stage 5 final filter. Howdy is integration and coaching led across every discipline.
Pricing transparency is the second wedge. The large enterprise players publish nothing, and most marketplaces stop at a savings percentage. FutureProofing.dev lists a flat $13.5K/mo all-in rate with no equity, no recruiter fee, and no hourly billing, plus Net-30 invoicing. For a procurement lead burned by stacked platform fees or surprise conversion charges, a single published number you can put on a vendor form is a real differentiator.
The proof is in the work. Profile delivery runs about 48 hours and the median time to first PR is roughly two weeks. FutureProofing.dev has published the receipts on an embedded engineer shipping a production RAG pipeline with Claude Code in its production RAG case study. For the side-by-side against the marketplace and staffing incumbents, the Toptal vs Turing vs Andela vs FutureProofing comparison lays out pricing, vetting, and lock-in in one table.
Get started
The shortlist reduces to one question. Do you need an AI specialist embedded in your team, or staffing capacity at scale?
If you need raw scale or an enterprise outsourcing partner, BairesDev, Globant, and Softtek are built for that. If you need the widest vetted pool with payroll and compliance handled, Revelo is the breadth leader at 400,000+ engineers, per its site. If you want a long track record and a clean four-stage funnel, Tecla is the cleanest proof, per its site. All sit in the 30 to 60% LATAM savings band, per Globy. For more comparisons across the LATAM talent market, browse the LATAM AI talent resource hub.
If the job is senior AI execution embedded in your codebase, that is a narrower category, and it is the one FutureProofing.dev was built for. A flat $13.5K/mo all-in, a 5-stage funnel that accepts 12 of every 2,000 candidates contacted monthly with Jess Mah as the final filter, Claude Code Max-fluent engineers on day 1, and a 7-business-day replacement at no extra cost. No lock-in to argue your way out of later. See the active bench to evaluate who is available now.
Collection · LATAM AI Talent (landing)