Repetitive decisions involving documents or data
The team repeatedly classifies information or extracts and validates similar fields.
Data & AI
Data & AI applied to business processes
Companies already generate documents and data, but AI only creates value when it addresses a real workflow with defined rules, validation, and controls. We assess how to apply it within the process and confirm the technical scope for each case.
Signals to assess
When AI makes sense
The starting point is a specific operational situation. These signals help identify cases that warrant technical assessment.
Large volumes of unstructured information
Documents, messages, or records must be read and processed before the workflow can continue.
AI capabilities isolated from the workflow
An established tool or provider is available, but its outputs still have to be transferred manually into working systems.
An existing system needs an API connection
The process may require an integration governed by rules, validations, and available technical mechanisms.
Sensitive data requires greater control
The case calls for assessing whether processing can take place within infrastructure controlled by the client.
The team needs practical capabilities
People need to learn how to apply AI to real company situations, not just understand general concepts.
Possible approaches
How we can help
The appropriate option depends on the problem, data, controls, and configuration confirmed for the scope.
AI applied to processes
This fits when classification, validation, or processing can be incorporated into a business workflow with defined rules and human oversight.
AI integrations through APIs
This applies when an established provider or model offers a viable interface and must connect with existing systems under agreed controls.
Private or controlled local AI
This may be assessed when the case requires data processing within client-controlled infrastructure; feasibility, configuration, and any use of local models are confirmed case by case.
Document and data intelligence
This fits when the workflow requires classification, extraction, validation, or information processing. Scan2x can provide the document layer, with Data & AI extending it where confirmed for the scope.
Practical AI training for companies
This is useful when a team needs to work on the organization’s real use cases, with usage criteria, controls, and exercises tailored to the agreed context.
Working method
How we approach it
Technology is selected after the process is understood and the right approach for the case has been defined.
Business problem
We understand the problem, the current process, its inputs, decisions, exceptions, and controls.
Approach
We determine whether the case calls for an API integration, a controlled local environment, document intelligence, or training.
Technology
Only then do we select the specific technology and confirm its configuration and technical scope.
Frequently asked questions
Data & AI basics
Does Cálamo train its own AI models?
No. Cálamo integrates and applies established AI technology to real processes; it does not develop or train foundation models of its own.
Does AI work with every system?
That is not assumed. Each integration is assessed according to its interfaces, data, security, and available mechanisms, then confirmed for the agreed scope.
What is a private or local AI environment?
It is an option for processing data within infrastructure controlled by the client when the case requires it. Architecture, feasibility, and configuration are assessed individually.
Do you offer AI training?
Yes. Training is practical and applied to the company’s real use cases, with an agreed scope and controls, rather than being limited to general theory.
Does Data & AI replace Scan2x?
No. They are complementary: Scan2x provides the document layer, while Data & AI may extend it or apply to other processes, as confirmed for the scope.
Let’s assess your case
Let’s review the problem, process, data, and controls to define a technically feasible approach and scope.