Most failed outsourcing engagements do not fail in month six. They fail in the sales process, when warning signs were visible and nobody asked the right question. Latin America has excellent senior engineers and plenty of well-run firms, but like any region it also has vendors that overpromise. If you are a US company shopping for a nearshore partner, this is a field guide to what to watch for.
1. Vague answers about who will actually do the work
The classic bait and switch: a polished senior person appears in the sales calls, and the work lands on someone you have never met. Ask for the names, roles and seniority of the people who will touch your project, and ask who is accountable for the outcome end to end. A healthy answer names one lead who owns the project and explains how specialists are brought in when the scope requires them.
Be equally wary of the opposite extreme. A vendor that boasts a huge bench is often a staffing pipeline, and a vendor that is truly one person has no backup when that person gets sick. You want an accountable senior lead plus a clear model for pulling in vetted specialists, such as a data engineer or a QA specialist, when the work needs them.
2. No description of how communication works
Do not accept “we communicate great” as a process. Good partners can describe their communication system in concrete terms: how they preview what will be produced before building it, how often check-ins happen, what the written status report looks like, and where you can see work in progress. If the answer is “we are available on Slack anytime,” you are buying improvisation.
A related point: do not select a partner on conversational polish alone, and do not rule one out because of an accent. What predicts a smooth engagement is structure. Written specs, agreed acceptance criteria, recorded decisions and a staging environment where you can click through the work make communication reliable even when the team is distributed and people are not native speakers of each other’s language.
3. A price that is far below everyone else
Cost savings are a legitimate reason to work nearshore, but an unusually low quote is usually a signal about something else: junior people billed as seniors, no time for testing, or a plan to recover margin through change orders. Ask for the quote to be broken down by role and by phase. Compare the assumptions, not just the totals. If two proposals differ by 40 percent, the cheaper one is almost always leaving something out.
4. Fuzzy contracts on IP, NDA and data
You should see, before kickoff, a contract that assigns all work product to you, an NDA that covers the vendor and every subcontractor, and a clear statement of where your code and data will live. Red flags include “we retain rights to reusable components” without a defined list, no mention of subcontractors, and reluctance to sign your standard paper. Also ask who owns the repositories and cloud accounts. They should be yours from day one, with the partner given access, never the other way around.
5. No production references you can actually call
Logos on a website prove little. Ask for two or three references you can speak to, ideally on projects similar in size and type to yours. If confidentiality prevents naming clients, ask for a walkthrough of how a comparable project was run: scope, milestones, what went wrong and how it was handled. A candid account of a problem and its fix is a better sign than a flawless story.
6. Skipping discovery and promising a date immediately
If a vendor quotes a fixed price and a delivery date after one call, they are guessing. Mature partners propose a short discovery or assessment first, produce a written scope with assumptions and risks, and only then commit. For AI work this matters even more, because data quality and integration constraints often decide whether a feature is feasible at all.
7. Everything is “yes”
A partner who never pushes back is not agreeing with you; they are not thinking. Seniority shows up as questions: why do you need this feature, what happens if the source data is wrong, who will use the output on Monday morning. During evaluation, bring a real but modest problem and watch whether the vendor challenges your assumptions and proposes a smaller first step.
8. Weak engineering hygiene
Ask to see how work moves from idea to production. You are looking for version control with code review, automated tests on critical paths, separate staging and production environments, written deployment steps and basic monitoring. If the answer to “where can I test this before it goes live?” is unclear, expect surprises on release day.
A quick scoring checklist
- Can they name the accountable lead and explain how specialists are added?
- Can they show a sample status report and describe their check-in cadence?
- Is the quote broken down by role and phase, with assumptions listed?
- Does the contract assign IP to you and cover subcontractors?
- Do you get a reference conversation or a candid project walkthrough?
- Do they propose discovery before committing to dates?
- Did they challenge at least one of your assumptions?
- Is there a staging environment and a documented release process?
Two or more “no” answers is a reason to keep looking, or to start with a small, paid pilot that lets the vendor prove itself on real work before you commit to a larger engagement.
Turning the checklist into a pilot
The best protection is a staged start. A paid pilot of a few weeks with a defined deliverable lets you evaluate the team on the things that matter: how fast they understand your problem, how clearly they report, how they handle a change in scope and whether the work is something your own people can maintain. Agree on the success criteria in writing up front, and treat the pilot as the real interview.
Brazil in particular offers strong senior talent, overlap with US working hours and a legal system that supports clear commercial contracts, but none of that replaces due diligence. Whichever country you choose, the same eight questions apply.
Want to put this to work? Convertty runs an AI assessment of your workflows and delivers an implementation plan with a pilot in production in 30–60 days. Book a call.
