AI-powered process automation
We automate business processes by combining integrations, data, and artificial intelligence to reduce manual tasks, interpret information, and connect actions across different systems. We analyze current workflows, identify automatable stages, and build flows adapted to the tools the company already uses: ERP, CRM, websites, databases, email, marketing platforms, or external services.
Document management and interpretation
We can collect documents, validate them, extract information using OCR and AI, structure the data, and subsequently send it to ERP, CRM, databases, or other systems.
Sales processes and CRM
We analyze and enrich customer or company information, segment databases, and can trigger sales or nurturing processes based on the detected profile.
Issues and tracking
We connect APIs, email, CRM, ERP, or other platforms to detect issues, interpret information, initiate actions, and perform follow-ups.
Content and communication
We can automate parts of the research, writing, review, translation, scheduling, publishing, and content measurement process while maintaining human validation points.
Classification and prioritization
AI can analyze information and assign categories, priorities, profiles, or other criteria that the system then uses to decide the next step.
Data enrichment
We can combine internal data with information from websites, APIs, or other sources to complete records and obtain a more useful view of customers, companies, or processes.
Information generation and transformation
Summaries, translations, data structuring, field extraction, document generation, or content adaptation can all be part of an automated workflow.
System connectivity
When a process involves multiple tools, we integrate the necessary platforms so that data and actions flow without the need for manual intervention at every step.
Automation is more than just doing things faster
Some processes require copying information between platforms, reviewing documents, classifying data, checking for issues, or executing the same sequence of actions repeatedly.
In these cases, we can build systems that collect information, process it, make decisions based on defined rules, and execute the corresponding actions.
Artificial intelligence allows us to go a step further when the process needs to interpret unstructured content, classify information, extract data, evaluate results, or generate content.
But we don't automate for the sake of automating. First, we understand the process and decide what makes sense to solve with rules, what requires AI, and at which points a human remains necessary.
AI is one piece of the process. The goal is for the entire system to work better
Real-world AI automation cases
From PDF invoices to ERP automatically
In this project, we automate the incorporation of purchase invoices received in PDF into the company's management system.
The process collects multiple documents, verifies their validity, and extracts content using OCR and AI interpretation. The information obtained is transformed into structured data so it can be processed by the system.
Before final incorporation, the user can review and validate the results from a web environment. Once approved, the invoices are automatically sent to the ERP.
Documents or results that do not pass validation are logged for review.
Real-world AI automation cases
Customer segmentation and nurturing with AI
The process starts with existing CRM information and enriches it with publicly available data from the internet. The system queries registered companies, identifies their web domain, and analyzes the content of each site using scraping tools and artificial intelligence.
AI interprets this information to determine the company profile and its commercial potential, transforming the result into structured data that is subsequently fed back into the CRM.
This classification allows for more precise segmentation and the preparation of nurturing processes or sales actions tailored to each profile.
Real-world AI automation cases
Detection and tracking of transport issues
In another project, we connected carrier data with the company's internal systems to detect and manage shipping issues.
The system periodically checks shipment status via the carrier's API and logs the information. When an issue is detected, AI evaluates the case and can trigger defined actions, such as sending a communication or initiating a follow-up.
Subsequently, the system re-checks the status until the issue is resolved, updating the information available in internal tools and generating data to analyze results.
COMMON-SENSE PROJECTS
Our Methodology
We automate processes
with you in mind
FREQUENTLY
asked questions
If you have any questions we haven't answered or need to evaluate a specific case, we'll be happy to help. Tell us about your project and we'll offer the best solution for your business.