Assistant over your documents
Search and answers with source citations across contracts, manuals, price lists or project history, so the team finds in seconds what it takes minutes to locate today.
Implementing artificial intelligence in a business means connecting language models and other AI techniques to the real documents, data and processes of the company to solve a specific, measurable task: answering queries with citations, preparing drafts, classifying requests or extracting data from documents. At FH Tecnología every implementation starts with a scoped pilot, a measured baseline and a person who approves anything that affects customers or money.
What gets built
Artificial intelligence that fits how you already work.
This is not about adding a chatbot. It is about solving one specific process with a measurable result.
Knowledge
Operations
Agents that prepare the work
They classify requests, fill in records, spot missing data and write drafts. A person reviews and approves before anything leaves the company.
Data
Extraction and classification
Reading invoices, emails or forms and turning them into structured, recorded data, with quality controls and traceability.
Quality
Evaluation and monitoring
Automated tests, a log of responses, and usage and cost dashboards so you know whether the system works and what it costs each month.
How to do it well
One process, one metric, one pilot.
Most AI projects fail because they start too big. Pick a process with volume, measure how it performs today and build the smallest version that proves an improvement.
- Baseline first. Current time, cost and errors of the process, before touching anything.
- Human in the loop. The AI proposes; a person approves anything that affects customers and money.
- Privacy by design. Which data is used, where it is processed and with which provider, all documented.
- Continuous evaluation. A test set that runs on every change to catch regressions.
- No lock-in. Documentation and code are yours, with interchangeable model providers (Claude, OpenAI or others) and orchestration with n8n when needed.
How I work
From idea to production in four phases.
- Phase 1 · 1 week
Discover
Goal, available data, risks and success metric, all in writing.
- Phase 2 · 1-2 weeks
Prototype
A working version with your real data, to decide with evidence.
- Phase 3 · 2-6 weeks
Build
Product in production, with tests, security and documentation.
- Phase 4 · ongoing
Operate
Measurement, improvements and support so the result lasts.
Frequently asked questions
About AI implementation.
How much does it cost to implement artificial intelligence in a business?
It depends on the process, the quality of the data and the integrations required. A scoped pilot lets you learn the real cost before committing a larger budget. After the discovery phase you receive a fixed proposal with scope and timeline.
Is my data used to train models?
I choose providers and configurations that do not use your data for training, and I document which data goes to which provider. If the case requires it, hosting in the EU or models deployed on your own infrastructure are options.
Does it comply with GDPR and the EU AI Act?
The design starts by minimising personal data, documenting the processing and classifying the system by its risk level. For high-risk cases or where there is legal doubt, specialised legal advice is recommended.
What happens if the AI gets it wrong?
Quality is measured with a test set before going into production and continuously afterwards. Decisions that affect customers or money always go through a person for approval.
How long does a pilot take?
A pilot usually takes between three and five weeks as a guide, depending on the integrations and the quality of the starting data.
Other services
Works well with.
Service
Websites and platforms
Fast, accessible corporate websites built to rank on Google and turn visits into enquiries.
Service
Applications
Mobile apps and internal tools your team will use, from prototype to the app stores.
Service
Automation
Flows that connect your tools and remove the repetitive work from quotes, invoices, customer service and filing.
Let's talk.
Tell me what you want to achieve. I reply with a proposal for the next step.
Tell me about your project