AI Automation & Agents

Your manual processes
can work on their own.

We design and implement AI-powered automations that free up team time, reduce errors, and integrate with the systems you already use.

0%
companies with tools but no real value
0%
of challenges are organizational
0d
from pilot to production
0%
of companies have an AI policy
AUTOMATION WITH AI AGENTS
Turn manual processes into agents that work alongside your team.
We identify concrete opportunities, design AI-integrated workflows, and build automations connected to your real operation.
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initial diagnosis · real processes · custom agents · measurable impact
The starting point

The symptoms are well known.
So is the underlying problem.

Mid-sized companies have processes that consume time disproportionately. As the team grows, these processes scale poorly: more volume, same people. AI can solve many of these problems. The challenge is not the technology: it is identifying which processes are real candidates and designing solutions that integrate with what already exists.

01
Overflowing inboxes

Emails, tickets, or inquiries that require manual classification and routing every single day.

02
Trapped data

Documents someone has to read, extract data from, and manually transfer to another system.

03
Knowledge bottlenecks

Internal questions that always fall on the same people who "know" how something works.

04
Disconnected systems

Systems that do not talk to each other, with data copied manually from one tool to another.

When you're ready

Not everything needs an agent.

At fuubo we design before choosing technology. Sometimes a flow in n8n, Power Automate, or Make is enough; other times, an agent makes sense when natural language, context, or conversation is required. The key is knowing when to use each one.

Schedule a call →
What we build

Some of our solutions

These are not templates. Every implementation starts from a real process diagnosis and adapts to the client's systems, data, and team. These are the most common patterns.

Customer support

First-level support agent

Handles frequent customer inquiries via web, WhatsApp, or email. Responds with accurate information and escalates to a human when the case requires it. Operates without intervention.

↓ Support team workload · ↑ 24/7 availability
Internal knowledge

Team assistant

Agent trained on the organization's internal documentation. Answers team questions about policies, processes, products, or clients in Slack or Teams.

↓ Information search time · ↑ Team autonomy
Communications management

Automatic classification

Classification and routing of emails or tickets by type, urgency, and owner. Automatic responses for the simplest cases. Notifications to the right team.

↓ Response time · ↑ Inbox organization
Document processing

Automatic extraction

Processes PDFs, invoices, contracts, or forms and extracts the relevant information. Automatically pushes it to the destination system: CRM, ERP, or spreadsheet.

↓ Manual entry hours · ↓ Error rate
Sales team

Sales copilot

Assists the team with drafting proposals, summarizing calls, updating the CRM, and preparing follow-ups. Reduces administrative workload.

↑ Time selling · ↓ Time on admin
Operations & management

Automated reports

Collects data from multiple sources and generates periodic reports with natural-language analysis. Includes automatic alerts when a key metric deviates.

↓ Preparation time · ↑ Report frequency
Methodology

How we work:
never building before understanding.

Every project follows five phases. Total time depends on complexity. We do not start building until we have clarity on what we are building and why.

01
Coffee Chat
Listen

We start by understanding the real process, not the ideal one: people, tasks, friction points, data, and systems involved.

02
Assessment
Analyze

We choose where to automate first based on impact, feasibility, and expected return. Not everything needs an agent.

03
Blueprint
Design

We design the right flow or agent, including integrations, business rules, exceptions, and how it will coexist with the team.

04
Action
Build

We build, test, and adjust in short cycles using real data, to validate value before scaling.

05
Continuity
Sustain

We launch with hands-on support, training, and clear metrics so the automation does not get abandoned after the demo.

Technology stack

Some of the tools we use

The honest answer: it depends on the problem, not on technical preference. These are some of the tools that guide our choices.

Flow orchestration
n8nMakePower AutomateZapier
Agentic frameworks
Claude APIOpenAI SDKGoogle ADKLangGraphCopilot Studio
Language models
ClaudeOpenAI GPTGeminiGemmaLlama
Knowledge bases (RAG)
SupabasePineconeChromaWeaviate
Why fuubo?

We don't sell AI.
We guide its real adoption.

01

Diagnosis before solution

We do not arrive with a predetermined technology. We start by understanding the process, the data, and the team. The solution emerges from the diagnosis, not the other way around.

Process first, agent second
02

Emphasis on adoption

Building the automation is only half the work. The other half is making sure the team uses it, understands it, and can operate it. Without that, even the best-designed solution fails.

Agents the team actually uses
03

Focused on the LatAm market

Global consulting firms don't serve all companies regardless of size. We serve all types of organizations seeking clarity, focus, and real return on investment for their teams.

Automation at your scale
04

Measurable results from the start

We define success metrics before building. If we cannot measure the impact, we revisit the project design. We do not deliver automations without evaluation criteria.

Measurable impact, not pretty demos
When you're ready

Do you have a process that could run on its own?

We help you assess whether it is a good candidate for automation before committing resources.

Schedule a call →Take the assessment first
FREQUENTLY ASKED QUESTIONS

Everything you need to know.

If your question is not here, write to us directly.

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An AI-powered automated flow can be in production in 3 to 4 weeks. An agent with a knowledge base and multiple integrations takes between 6 and 10 weeks. In the diagnostic phase we can give you a more precise estimate for your specific case.

It is not a requirement. But it is necessary to designate an internal process owner who understands the business and can make decisions about scope. For ongoing maintenance, we train that person to operate the basic solution autonomously.

It depends on the solution. In many cases, client data is not stored in external systems: it is only processed at the moment of the query. In cases where data persistence does occur, we work with the privacy configurations of the providers (Anthropic and OpenAI offer data non-retention modes). We define this during the design phase.

An automated flow follows a predefined sequence of steps. If X happens, do Y. It is deterministic and predictable. An AI agent decides in real time what to do based on context, using a language model to reason. Most mid-sized company projects are well served by flows with AI in one or two steps.

It is more common than it seems. In that case, the diagnostic phase carries additional weight: before designing the automation, we help document and organize the process. Sometimes the diagnosis reveals that the process needs to be simplified before it can be automated.

We deliver complete documentation and train the internal owner to operate and monitor the solution autonomously. For more complex changes or ongoing maintenance, we offer monthly support retainers.

AI Automation & Agents — fuubo.ai