Four elements. One integrated assurance system
Xpandia Language Assurance
TM
Localization
Adapts language and content to the target market, audience, and customer context.
Language QA
Tests meaning, clarity, terminology, tone, and user-facing risk.
Applied Cultural Intelligence
Evaluates expectations, trust, behavior, and cultural friction in the target market.
Human Evaluation
Uses expert human judgment to assess language quality, cultural fit and real-world user impact.
Our services
We help customer-facing AI work reliably, so it feels clear, natural, and trustworthy across Latin America.
Language & Cultural
Quality Audit
A country-specific assessment of customer-facing AI outputs for language quality, cultural fit, user friction and market exposure.
01 / UNDERSTAND
02 / DECIDE
Launch Readiness Validation
Pre-launch validation of critical AI outputs and interactions to decide whether the experience is ready for the target market.
03 / PROTECT
Ongoing AI Language QA
Recurring quality cycles to detect regressions, language drift, and market-specific issues as AI systems and content change.
Markets
We review how your AI communicates in the market, audience, and context it is meant to serve. Not generic language.
SPANISH
20
country-specific markets
PORTUGUESE
Brazil
COUNTRY-SPECIFIC LATIN AMERICAN SPANISH
Mexico · Colombia · Argentina · Chile · Peru · Venezuela · Ecuador · Guatemala · Costa Rica · Panama · Dominican Republic · Puerto Rico · Uruguay · Bolivia · Paraguay · Cuba · Honduras · El Salvador · Nicaragua · US Hispanic
BRAZILIAN PORTUGUESE
Brazil-specific language calibrated for audience, region and customer context.
Tone, terminology and cultural expectations are calibrated market by market.
Issues we find
By reviewing AI outputs, interactions, and priority flows we identify language, cultural, and experience issues before they affect trust, support, conversion, or launch readiness.
"Coger" does not travel well
In some markets, coger means “pick up.” In others, it carries a strong sexual meaning. The sentence “puedes coger tu pedido” is fluent and grammatically correct, yet risky for customer-facing AI. Using it wrongly can create embarrassment, damage trust, or expose the brand to unnecessary risk.
Detected: market-specific meaning risk (esMX)
Classified: S1 / market-specific language risk
Corrected: “recoger” recommended for safer output
Safer output: “Puedes recoger tu pedido”
LATIN AMERICAN SPANISH
SPANISH + PORTUGUESE
"Propina" changes meaning
In Spanish, propina commonly means "a tip". In Brazilian Portuguese, the same word commonly means a bribe. Similar words can trigger a very different outcome.
Detected: false-friend risk (ptBR)
Classified: S1 / meaning shift across languages esAR-ptBR
Corrected: “gorjeta” recommended for safer output
Safer output: “gorjeta”
Fluent can still fail in the target market
AI systems we evaluate
We review the customer-facing AI experiences your users actually read, hear, follow, and trust.
Use case
What we help you see
✔ AI Chatbots
✔ Customer Support AI
✔ AI Copilots
✔ AI Agents
✔ Generative AI Outputs
✔ AI Avatars & Voice AI
✔ Product Flows
✔ UX Copy & Support Content
If answers sound right but fail users.
If users still need human support.
If suggestions shift meaning or certainty.
If language triggers the wrong action.
If fluent responses create risk or distrust.
If spoken language feels unnatural or awkward.
If users misunderstand or abandon key steps.
If wording creates friction or confusion.
Industries we work with
We help teams in industries where unclear, unnatural, or market-misaligned language can create friction, risk, or loss of trust.
Banking & Fintech
Healthcare
Insurance
E-commerce & Retail
Travel & Hospitality
Telecom
Software & SaaS
Education & EdTech
HR & People Tech
Government
When to call Xpandia
Use Xpandia when your AI is entering a market, changing behavior, creating concern, or needs ongoing language-quality control.
Use case
What we help you see
✔ New-market launch
✔ Major product release
✔ Customer support automation
✔ AI output quality baseline
✔ Prompt or model change
✔ Multimarket rollout
✔ High-visibility customer journey
✔ Localization quality dispute
✔ User complaints or escalations
✔ Ongoing quality monitoring
If the AI is ready for that market.
If language changes create new user risk.
If the AI understands but does not resolve.
If current quality is measurable and comparable.
If updates improved or damaged language quality.
If one language version fails across countries.
If critical flows create friction or distrust.
If teams need evidence, not opinions.
If language issues are driving support volume.
If language drift appears as the AI evolves.
Our process
A typical engagement runs 10–15 business days, from scoping to retest.
Days 1-2
Days 3-7
Days 8-11
Days 12-15
01 / Scope
Align the AI experience, users, markets, goals and quality bar.
02 / Evaluate
Review representative outputs for language QA, meaning, tone and market fit.
03 / Prioritize
Classify findings by severity, user impact and implementation urgency.
04 / Report + Advise
Deliver prioritized findings, repair guidance, and clear recommendations for what to fix, retest, or monitor.
Findings your team can act on
Every engagement turns expert review into clear, measurable decisions.
What you receive
-
Quality Scorecard for the target market
-
Issue taxonomy with severity and user impact
-
Market-specific evidence from the AI outputs reviewed
-
Prioritized findings with safer alternatives and repair guidance
-
Executive readout with clear next actions
Decision-ready readout
✓ What can move forward
✓ What needs fixing
✓ What must be retested
✓ What can wait
Pricing
Typical ranges. Multi-market and enterprise engagements are custom-scoped
Markets, flows, output volume, complexity, exposure, review depth and cadence determine the investment.
ONGOING AI LANGUAGE QA
3k-15k USD
per month or scheduled cycle
Recurring reviews, regression monitoring, market scorecards, business interpretation and advisory support.
PROJECT ENGAGEMENTS
5k-50k USD
per project
Audit: $5K–$50K. Launch Readiness: $5K–$25K. Both include decision-ready findings, executive readout and fixing priorities.
Client testimonial
K–12 EdTech success case across Colombia, Uruguay, Spain, and the United States.
Intertext
CASE STUDY
A shared quality framework for market-ready learning content
AI-assisted K–12 adaptation, evaluated market by market.
Xpandia helped us integrate Language Assurance into the K–12 digital content we adapt for U.S. educational publishers. Their market-specific approach gave our teams a more consistent way to evaluate terminology, tone, and cultural fit for Spanish-speaking students in Colombia, Uruguay, Spain, and the United States."
“
Diego F. Moreno
CEO, Intertext
Language · cultural fit · learner impact · market-specific decisions
Why Xpandia
Xpandia turns technically correct AI language into market-ready experiences users can trust.
Founder-led accountability
Nestor Solano brings 20+ years of leadership in localization, language quality, and cross-cultural communication, including multilingual programs across 42 locales for products serving 150M+ users in over 80 countries and Fortune 500 organizations.
Founder & Language Assurance Lead
What Xpandia brings
01
Senior enterprise experience.
02
AI localization + language QA + cultural intelligence.
03
Country-specific Spanish and Brazilian Portuguese.
04
Market-native expert network.
05
Shared criteria, severity levels and calibrated findings.
Xpandia Language Assurance
TM
Common Questions
Clear answers for teams evaluating AI quality, market readiness, and language risk.
A framework combining AI localization, Language QA, Applied Cultural Intelligence, and market-specific review to evaluate how customer-facing AI performs for real users.
What is Xpandia Language Assurance ?
TM
No. Translation changes text from one language to another. We evaluate whether AI communicates clearly, naturally, and safely in the target market.
Is this translation?
Chatbots, copilots, agents, avatars, support AI, generative outputs, product flows, and prewritten responses that directly affect users.
What types of AI systems do you review?
Usually not. Most projects use representative outputs, prompts, responses, conversation logs, or priority flows supplied by your team.
Do you need access to our systems?
You receive prioritized findings, safer alternatives, repair guidance, and a clear decision about what can move forward, what needs fixing, and what should be retested.
Which markets and languages do you cover?
You receive prioritized findings, safer alternatives, repair guidance, and a clear decision about what can move forward, what needs fixing, and what should be retested.