AI Agent Development Company in Mexico City

Workflow count is the first thing that changes a CDMX agent budget: a scoped agent for one defined workflow (KYC onboarding, CFDI invoice generation, flight booking, SKU replenishment) at CDMX rates, or multi-workflow agents with hand-offs between specialist agents. Scope drivers include tool catalogue design, agent orchestration, evaluation harness, shadow deployment, and three months of post-launch monitoring. For nearshoring clients with US parents we invoice in USD on fixed-fee MSAs to avoid peso-dollar exchange volatility. CDMX rates sit above Guadalajara and Monterrey because of the AWS Querétaro region premium and the talent concentration at ITAM, Tec de Monterrey CDMX campus, UNAM, and IPN.

Yes. The Mexican aviation booking workload is interesting because it mixes Mexican aviation tax handling (TUA airport tax, DNR migration fee), multi-currency MXN+USD pricing (US-bound flights price differently than domestic), code-share complexity (Aeromexico's Skyteam alliance, Volaris's US codeshares), and multi-dialect Spanish customer service. Our agents integrate with the airline APIs through standard NDC (New Distribution Capability) and legacy GDS interfaces (Sabre, Amadeus), handle price comparison across both airlines, draft and validate booking with the correct tax breakdown, and produce CFDI 4.0 invoices for business travel that meet SAT requirements. For corporate travel the agent integrates with the company's expense system (Concur, Mexican local equivalents) and produces the audit-friendly trail Mexican finance teams need.

América Móvil-pattern pan-LatAm telecom or Mercado Libre-pattern pan-LatAm commerce workloads serve customers across Mexican, Colombian, Argentine, Chilean, Peruvian, Venezuelan, and Central American Spanish dialects from CDMX or São Paulo headquarters. The dialects are genuinely different (Mexican mande and ándele, Argentine che and vos conjugation, Colombian chévere and parcero, Chilean cachai and weón), and a generic LatAm Spanish prompt produces awkward output that customers notice within two turns. Our agents detect country from session signals (phone country code, IP geolocation, explicit user selection) and route to a dialect-tuned system prompt or LoRA adapter on the base model. Evaluation runs per-dialect, not aggregated. The dialect work shows up in CSAT and retention, not just in model evals.

Yes, and this is one of the highest-ROI agent workloads in CDMX. CFDI 4.0 is the SAT's mandatory electronic invoice schema, and the end-to-end workflow (draft from natural language input, validate against the official XSD, sign with the digital seal CSD certificate, submit to a SAT-authorised PAC, handle rejection cycles, deliver to recipient) is mechanical enough to automate at 90-95 percent end-to-end. Our agents handle the entire workflow with deterministic tool wrappers around each step (the LLM never generates raw XML directly; it drafts content that goes through deterministic schema generators). Rejection handling routes to the appropriate fix path (timbrado issues, RFC validation, código postal mismatches). Mexican small businesses too small to staff a full accountancy function are the natural customer for this agent pattern.

Banco Azteca operates an unusual hybrid model: full banking license, branches embedded inside Grupo Elektra retail stores across thousands of small-format locations serving customers who historically lacked access to traditional banking. The agent workload is onboarding (INE voter ID capture, CURP validation, biometric face match), product cross-sell (small loans, remittances, prepaid cards), and customer service in Mexican Spanish for a demographic that often prefers voice over text. Our agents integrate with the branch tablet stack, handle the INE OCR and validation against the INE database, draft loan documents in Mexican Spanish at appropriate reading levels, and escalate to the human branch staff for the 10-15 percent of cases that hit known edge conditions. Direct Banco Azteca engagement happens through their procurement; we work most often with Tier 1 Mexican banking integrators on this pattern.

Banorte, BBVA Mexico, Citibanamex, Santander Mexico, HSBC México, and the Fintech Law 2018 neobanks operate under CNBV and Banco de México oversight. Agent deployments for these clients carry model risk documentation patterned after OCC SR 11-7 from the US (which CNBV regulators reference informally), challenger testing against alternative model versions, explicit human-in-the-loop checkpoints for high-stakes decisions (credit approval, large-value transfers, account closure), and full audit logging in Spanish for compliance review. The Fintech Law neobanks (Stori, Cuenca, Albo, Bnext) operate under lighter oversight than the universal banks but the same general framework applies. We have shipped agent work across both ends of the Mexican financial regulatory spectrum.

Yes. The Mexican federal digital service landscape (SAT for tax, IMSS for social security, INFONAVIT for worker housing, CONAGUA for water, PROFECO for consumer protection) absorbs significant agent work, particularly for small businesses too small to staff dedicated compliance functions. Our agents navigate the SAT portal for CFDI 4.0 submission, tax declarations, and audit response drafting; IMSS for employer registration and worker affiliation; INFONAVIT for housing fund contributions; and PROFECO for complaint intake. Direct federal government contracting goes through Compranet and the Mexican federal procurement process, which we do not bid on directly. We work with private sector clients (accounting firms, payroll processors, SMB-focused fintechs) who serve the small business demographic that needs government workflow automation.

Hallucinations in agent systems handling real money (CFDI invoice amounts, KYC decisions, loan approvals, Aeromexico booking prices in MXN and USD) are unacceptable, and we design for that from the start. Our pattern: the LLM is constrained to drafting natural language and selecting tool calls; deterministic Python or TypeScript code executes the actual money-moving or decision-finalising step; schema validation runs on every tool input and output; multi-step workflows include verification checkpoints that confirm intermediate state before continuing; high-stakes decisions route to human-in-the-loop review with full Spanish-language context; and evaluation harnesses run thousands of historical and adversarial scenarios before any production deployment. The agent does not generate raw SQL, raw XML, or raw money movement; it orchestrates deterministic tools that do.