The work gets executed. Not just assisted.
The operating layer for LATAM companies. Your team and AI agents execute the work together, under human control, priced per outcome.
Operating a company in LATAM is broken. Generic AI isn't fixing it.
Today's AI leaves the human as the bottleneck.
Copilots suggest, they don't execute.
ChatGPT, Copilot and Gemini help you write. They don't touch your ERP. They don't move money. The human still does the real work.
Vertical agents built for the US.
Sierra and Decagon execute, but in English, on Salesforce and Stripe. Your reality is CFDI, Siigo, WhatsApp, and 40%+ statutory burden.
'Company Brain' that maps existing chaos.
Glean and Copilot try to retroactively understand how your company operates. Oppero inverts the logic: we are where clean work executes from day one.
How Oppero works.
Canvas: where your team and agents execute together.
The shared surface where every workflow executes step by step. Humans approve where it matters. Agents execute where automation is possible. Every action is logged.
30 specialized agents, organized into 5 suites.
Each agent runs a real workflow with a price per delivered instance. Suites collaborate: a Collections agent can hand a case to a Service agent, on the same engine, under the same policy.
Agents collaborate across suites. Same engine. Same policy. Same log.
When a Collections agent needs to validate a fiscal record with the Ops team, it doesn't open a ticket. It hands the case to the E-Invoice Agent. The approval is logged. The human approving the critical action signs once, not twice. No copilot or isolated vertical agent does this.
Payment Reminder Agent
Validate fiscal record
E-Invoice Agent
Workflow log
5 suites. 30 agents. One operating layer.
Built in layers. Hiring is live. The rest follow a validated sequence.
Hiring
From candidate screening to onboarding. The lowest-risk entry point.
Candidate Screening Agent
Reviews CVs, scores against rubric, builds shortlist.
Interview Scheduling Agent
Coordinates calendars, reminders, reschedules.
Structured Interview Agent
Runs structured interview, transcribes, scores.
Offer Management & Hiring Ops Agent
Offer prep, approvals, electronic signature.
Employee Onboarding Agent
Pre-day-1 checklist, document collection, nudges.
HR Helpdesk / Policy Agent
Answers PTO, payroll, policy, benefits questions.
Collections
Reminders, negotiation, reconciliation and disputes. ROI you can see in cash.
Revenue
From lead to renewal. Qualification, follow-up, quote, activation, renewal.
Ops
Full back-office: AP, expenses, procurement, access, compliance, e-invoicing.
Service
Post-sale support and service. Triage, resolution, scheduling, returns.
Priced per work completed. Not per token. Not per seat.
Each agent has a price per delivered instance: per hire closed, per collection resolved, per invoice issued. A monthly platform plus outcome-based execution. No lock-in. Month-to-month.
Internal Lite
Low-volume internal coordination.
Structured Ops
High-volume structured workflows.
Conversational Growth
External communication and acquisition.
Critical Workflow
Regulated or financial critical workflows.
The math is simple.
Plus $40K+ in avoided recruitment CAPEX, and protection against severance liability.
AI crossed the execution threshold.
18 months ago, agents could not execute real work. In January 2026 they do it better than humans on open benchmarks. Generic models arrived, but they don't carry the LATAM operating backbone. That gap is Oppero.
Human level: 72%
Human ceiling 92%
The Operating Layer of today. The Intelligence Layer of tomorrow.
Every workflow Oppero runs generates clean, structured execution data: the best possible training data, because it comes from real execution, not scraping or synthesis. That data stays private per customer, never crosses tenants. But inside each company, agents continuously improve. The entry point is the Workforce OS. The destination is the intelligence layer underneath operational work in LATAM.
Built by LATAM operators.
Javier Escobar
Cofounder & CEO
- Dell Technologies Finance Development Program: executive briefs for the President's office.
- Processed $80M+ in executive-approved disbursements.
- Managed a $14.5M AUM fund, among the 10 largest student-managed investment funds globally.
- US/Mexico operator with deep finance, enterprise workflow, and LATAM adoption context.
Ana Clara Monteiro
Cofounder & CTO
- Built Oppero's agent orchestration layer end-to-end: workflow states, approvals, audit trails, and agent execution.
- AI researcher at King's Undergraduate Research Fellowships in London.
- Computer Science at King's College London, First Class Honors track.
- French-Brazilian engineer with Portuguese, Spanish, English, and French · LATAM context.
Frequently asked questions
How fast are we in production?
Days, not months. A typical Hiring Suite go-live takes one to two weeks, with access granted at kickoff. You configure tone, cadence and approval thresholds, not custom logic.
Do the agents act on their own?
They start in suggestion mode. You define which actions require human approval and which are automated. Every action is logged and reversible.
What if an agent makes a mistake?
Critical actions pass through human approval before they execute, and every action is reversible and auditable. The system is designed so an error never reaches your customer or your bank.
Does my data train other customers?
No. Learning is per company: your workflows tune only your agents. Tenant isolation is architecture, not an option.
How are we billed?
Per unit of work completed: per hire, per collection resolved, per invoice issued, per case closed. No per-seat pricing and no token charges.
What languages does it operate in?
Spanish and Portuguese first, English included. Agents reason in the language of your operation, not a translation.
Your team is exhausted. Your operation is breaking.
AI is ready to execute.
Days, not months. Pay per outcome, not per token. Humans in control, always.