AI Data Operations · Latin America

Hard-to-source data,
from the real world.

We help AI teams source, collect, annotate and evaluate custom datasets across Latin America.

Floowi helps AI companies build hard-to-access datasets using real businesses, real environments, and real domain expertise across Latin America.

Data sourcing · Custom collection · Annotation · Evaluation · Expert QA

Data request

Draft spec
Need
Egocentric workplace video
Environment
Warehouses
Region
Latin America
Volume
5,000 hours
  • SOURCE

    Businesses & operators identified

  • COLLECT

    Capture workflow deployed in the field

  • ANNOTATE

    Labeling & structuring against spec

  • QA

    Expert review, acceptance criteria

  • DELIVER

    Model-ready dataset handoff

Core capabilities

You define the data need.
We build the operation.

From finding existing datasets to creating new ones and making them model-ready.

Data sourcing

Find data that already exists.

We identify and source hard-to-access existing and historical datasets from businesses, organizations and operators across Latin America.

  • Operational data
  • Historical records
  • Industry datasets
  • Media archives
  • Domain-specific data

Custom data collection

Create data that doesn't exist yet.

When the dataset does not already exist, we design and run the collection workflow based on your specification.

  • First-person / egocentric video
  • Workplace video
  • Audio and images
  • Field ground truth
  • Multimodal datasets
  • Human demonstrations

Expert data operations

Add the human expertise models need.

We recruit and manage the right people to annotate, evaluate, curate and quality-check AI data.

  • Annotation & labeling
  • Expert review
  • Model evaluation
  • Ranking tasks
  • Curation and QA
  • Domain-specific workflows

Why Latin America

Why Latin America?

Because the advantage is not just labor. It is access.

Real businesses

Access to fragmented industries and businesses that are difficult to reach through traditional data vendors.

Real environments

Hotels, farms, warehouses, restaurants, factories, logistics operations, call centers, medical and industrial contexts.

Domain experts

A large and diverse base of professionals across healthcare, finance, engineering, agriculture, customer operations and more.

Regional diversity

Spanish, Portuguese, varied accents, multiple geographies, and operational contexts that make datasets richer and more representative.

Sourcing network

Businesses, environments and experts, mapped and coordinated across the region.

Our story

We didn't start as a data company.
We started by building access.

Floowi was built solving a difficult operating problem: finding, vetting and managing talent across Latin America for global companies.

Over the last few years, that work gave us recruiting infrastructure, local operating experience, and access to people and businesses across the region.

We are now applying that same infrastructure to AI data.

Instead of asking "who do you need us to find?" we now ask: "What data do you need us to source, collect or help operate?"

Capability evolution

  1. Talent sourcing01
  2. Distributed operations02
  3. AI data operations03

The underlying capability is the same: find hard-to-access supply, qualify it, coordinate it and deliver it reliably.

Access

Access across the real economy.

We are especially interested in data that lives inside real businesses, real workflows and real environments.

Worker scanning and packing boxes inside a warehouse
Logistics environments: picking, packing, sorting and delivery workflows.

Agriculture

Farms, crops, processing, field operations, ground truth.

Hospitality & travel

Hotels, restaurants, cafés, service workflows, customer operations.

Logistics

Warehouses, distribution centers, picking, packing, sorting, delivery.

Industrial

Manufacturing, tools, maintenance, equipment workflows, physical operations.

Healthcare

Medical professionals, workflows, evaluations, expert-in-the-loop tasks.

Customer operations

Call centers, support interactions, sales workflows, voice and service data.

Professional expertise

Finance, legal, engineering, business operations, domain experts.

Field operator recording crop data on a tablet

Illustrative examples

What could a request look like?

Every project starts with a concrete model need. The requests below are illustrative examples, not client work.

Example 01

Illustrative

For robotics / physical AI

We need 5,000 hours of egocentric video of workers performing warehouse picking and packing tasks.

We help source

  • Warehouses
  • Workers
  • Capture workflows
  • QA
  • Delivery

Example 02

Illustrative

For foundation models / data companies

We need experienced accountants to create and evaluate complex finance tasks.

We help source

  • Qualified experts
  • Project ops
  • Task workflows
  • Review and QA

Example 03

Illustrative

For agriculture AI

We need field-level crop imagery connected to real-world ground truth.

We help source

  • Farms
  • Field collection
  • Operators
  • Metadata
  • Quality control

Expert-in-the-loop

Some datasets need more than labeling.
They need judgment.

We can help recruit and manage qualified professionals for data projects where generic annotation is not enough.

Doctors evaluating medical outputs
Accountants reviewing finance tasks
Engineers validating technical content
Native speakers evaluating regional language
Industry professionals creating ground truth
QA reviewers checking collection quality

Process

How it works

From problem definition to model-ready data.

01

Tell us the need

Share the data spec — or simply explain the model problem you are trying to solve.

02

We design the operation

We identify the people, businesses, environments and workflows required.

03

We source / collect / annotate

We run the project across Latin America based on your requirements.

04

We QA and deliver

Data is reviewed against agreed acceptance criteria and delivered in the required format.

Rights & provenance

Built around consent, rights and clear data provenance.

We design projects around explicit participation, commercial usage rights and traceable sourcing processes.

  • Explicit participation
  • Commercial use considerations
  • Traceable sourcing workflows

Who we work with

Built for teams working at the frontier of AI.

Whether you are trying to source existing datasets, create new real-world collections, or add expert evaluation layers, we are interested in understanding the problem.

Foundation models
AI data companies
Robotics & physical AI
Multimodal AI teams
Vertical AI companies
Research teams

The data you need may not exist yet.

Tell us what you're trying to source.

Send us the data need, environment, expertise or collection challenge. We'll determine whether we can help build it in Latin America.

hello@floowi.com

Submit a data request