AI Integration for Business
Go beyond the buzzwords. We implement practical Artificial Intelligence solutions that analyse your data, automate customer service natively, and extract structured insights from unstructured documents.
What integrating artificial intelligence into a company means
Integrating artificial intelligence into a company means connecting language models to the data and systems it already uses, so they handle concrete work: reading documents, classifying requests, updating records and answering with the source visible.
The difference from using a generic assistant is access. A public assistant knows neither your data nor your systems; an integrated model checks the real order, the real contract and the real history before answering.
What makes it useful
- Automated data extraction from invoices, contracts, and emails
- Intelligent AI agents for client support with context awareness
- Predictive analytics for stock, demand, and resource allocation
- AI-assisted decision-making tools for management
The Problem
Many businesses collect massive amounts of data but lack the analytical or technological capacity to use it effectively. Customer service teams face the same repetitive queries, and hours are lost extracting data from PDFs, emails, and unstructured documents.
Signs AI has not left the experiment stage
- The team uses personal AI accounts, with company data pasted into them.
- AI helps write text but never touches the process that generates revenue.
- Nobody can verify where an answer the AI gave came from.
- Each department tried a different tool and nothing reached production.
What it integrates with
Integration is the project. Without controlled access to the systems, the model keeps guessing.
- ERP and CRM, to read and update real records
- Document repositories, including SharePoint, Google Drive and your own server
- Email and service channels, to classify and route
- Internal databases, with permissions per role
- Company authentication, so each person sees only what concerns them
How the project runs
Four phases. Scope, timeline and price are fixed at the end of the second, and from there on there is no budget revision halfway through.
- 01
Assessment
30 minutesWe understand the operation, the systems in use and where the manual work sits. Free and with no commitment to proceed.
- 02
Discovery and proposal
2 weeksWe map the real process, design the architecture and list the integrations. Scope, timeline and price close here.
- 03
Build
8 to 14 weeksTwo-week cycles with a demo at the end of each one. You validate every delivery before we move to the next.
- 04
Go live
1 to 2 weeksData migration, team training and documentation. Three months of support included after delivery.
What it costs
We publish the numbers so you can decide before talking to us. These are real ranges from projects we run, not a price list. The exact figure closes in the proposal and does not change halfway through.
First case in production
€7,500 to €15,000
One concrete process automated end to end, connected to a real system.
Several processes
€15,000 to €25,000
Three to five cases connected to the same systems, under shared governance.
Company AI platform
€25,000 to €45,000
Centralised knowledge, agents per department and controlled access.
Frequently asked
Want to know what this would do in your operation?
Free diagnosis, no commitment. We look at your process and come back with a plan covering scope, timeline and investment. Reply within 48 business hours, NDA included by default.
- 100% free diagnosis
- No commitment to proceed
- Reply within 48 business hours
- NDA included by default
Request free diagnosis
Two minutes to tell us the essentials. We reply within 48 business hours with a first read on your case and, if it makes sense, a proposed session.
Explore other solutions
Every vertical has its own challenges. See how we approach other sectors where we have proven experience.