AI systems already working in production.
We prefer to show what artificial intelligence can do through real systems. Every project starts from a different problem, but they all share one thing: AI is part of a business process and works with real data, tools and rules.
Guided troubleshooting for whoever is at the machine
Plant knowledge lived in dense manuals and in the heads of the most experienced people. We built an assistant on the company’s own systems. Operators query production and fault data, and get step-by-step guided troubleshooting when a machine stops.
6 specialized agents, coordinated by an orchestrator that routes every query.
See the plant assistant case →
98% of invoices processed with no human intervention
A system that automates receiving, interpreting and processing invoices. It combines artificial intelligence, validations and integrations with the rules of the back-office process to reduce manual work.
98% of invoices complete the process with no human intervention.
See the Stanton case →
More than 3 hours a day saved screening rental inquiries
Every rental inquiry arriving on WhatsApp took five to ten minutes of manual checking, and dozens came in every day. The agent talks to the applicant, collects reason, budget and paperwork, and emails the team a summary with a paragraph explaining why each one fits or doesn’t.
More than three hours saved every day checking rental inquiries. The team stopped screening applications and went back to booking viewings.
See the Barceloneta Premium case →
Querying databases in natural language
A system that gives access to business information through questions in natural language. The user does not need to know SQL or dig through dashboards: the system interprets the question, works out which data it needs and uses a controlled data-access layer.
The model never runs arbitrary queries directly against the database.
See the Savian case →
An AI agent that manages appointments through a conversation
Wazzy is our own product, not a client’s. It manages appointments straight from WhatsApp in dental, physiotherapy and aesthetic clinics: it checks the real calendar, suggests times, books, changes or cancels, and alerts the team when the conversation needs it.
Hundreds of appointments a month, and not one double-booked in the product’s entire history.
See the Wazzy case →Tell us about the process you want to improve.
You do not need to know which model to use, which architecture you need or whether the problem calls for an AI agent. Tell us how the process works today, who is involved and which tools you use.
We’ll reply within one business day with a first read of your case.