Documents
Extracting fields from contracts, receipts, forms or attachments and preparing the information for validation.
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S/03
AI implementation
Artificial intelligence.
We put practical AI to work in your business: from intelligent assistants and search across your documentation to predictive analytics and classification models. We work with commercial providers, open-source models and custom solutions adapted to your data and needs.
The opportunity
We apply artificial intelligence where there is a concrete problem and enough data: reading documents, finding information, sorting requests or preparing a decision.
Who it's for
It's for businesses that want to go from trying isolated tools to building AI into a real process, with permissions, human review and a clear way to measure whether it helps.
What we solve
Where applied AI adds value
Internal knowledge
Querying information spread across documents and systems while respecting each user's permissions.
Classification
Interpreting messages or requests and deciding which team, status or reply applies.
Prediction
Combining current and historical data to anticipate demand, needs or anomalies.
How we do it
AI built into the process, not stuck in a demo
A useful solution needs context, data, limits and evaluation. That's why the model is part of an architecture that validates inputs, logs results and allows corrections.
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Use case
We define the decision or task we want to improve and how we will know whether the system helps.
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Data and permissions
We decide which information the model can query and what each type of user should see.
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Testable prototype
We test with real examples, including ambiguous cases and common errors.
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Integration and monitoring
We connect the solution to the product or process and measure how it behaves after launch.
What you get
An improvement your team can use.
- A well-defined, measurable use case.
- Access to information with permissions and traceability.
- Human review for sensitive or uncertain decisions.
- A solution that can evolve with new data.
Projects
Where we've already applied it.
Clients
Client · FinTech / Digital wallets
Carga Virtual — an operation that never sleeps
Payment receipts received on WhatsApp, turned into an automated, traceable operation that runs at any hour.
+ARS 130MProcessed in 60 days1,518Top-ups completed
Client · Logistics consulting / B2B salesCedrés Consulting — B2B opportunities with a 47% acceptance rate
A B2B prospecting system that keeps up volume and consistency, qualifies conversations and saves human judgment for real opportunities.
47%Acceptance5,112Profiles visited
Client · Construction / SaaS / AIConstruction SaaS in Chile — contracts turned into knowledge
A contract stops being an isolated PDF and becomes a structured record that can be reviewed and queried with artificial intelligence.
+5,000Planned contracts1 PDFStarts the record
Client · Tourism / Travel agencySafari Viajes — from an image to a sellable package
An image with an offer becomes a structured web package, ready to continue the sale on WhatsApp.
~10 sTo create a package1 imageAs the starting point
Related guides and cases
Go deeper into this solution.
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Frequently asked questions
Before we start.
What kind of artificial intelligence does my business need?
It depends on the task, the data, privacy, volume and the level of accuracy you need. Not every process needs a generative model or the same architecture.
Can AI be used with private documents?
Yes, but access, storage, permissions and the right provider have to be designed so the information is handled according to the project's needs.
Can AI make decisions without supervision?
In well-defined tasks, it can automate low-risk decisions. In sensitive processes, it's best to combine thresholds, rules and human review.
How do you measure whether an AI implementation works?
We look at metrics tied to the process, such as accuracy, time saved, cases resolved, escalations, errors and the quality the team perceives.