AI agents and chatbots
Conversational agents over WhatsApp, web and phone, wired into the client's own APIs and CRM, with RAG and purpose-built calculation functions.

ANDRES QUINTERO · Valencia, Spain
AI Engineer · Automation and self-hosted infrastructure
22 years hands-on with systems, since I was 14 · Open to employment or projects · Valencia, hybrid or remote
I build conversational agents, automate processes and run the infrastructure they live on. When the data is sensitive, all processing happens inside the client's perimeter: local models, a segmented network and not one byte to third parties.
Most people cover one. The value is in having the conversation, the process, the data and the server designed by whoever will answer when something breaks.
Conversational agents over WhatsApp, web and phone, wired into the client's own APIs and CRM, with RAG and purpose-built calculation functions.
Self-hosted n8n, with close to twenty flows in production, integrating Odoo, Holded, Pipedrive, payment gateways and telephony.
Complete applications end to end: multi-tenant SaaS, a FastAPI backend with hashed keys, signed URLs, sessions and an audit trail, and the interface on top.
Proxmox, OPNsense and Docker on our own servers: VLAN-segmented networks, WireGuard VPN, HAProxy publishing, hardening and audit trails. No SaaS dependency and no third-party processors to add to your GDPR record, because the data never leaves your perimeter.
Work done for third parties is described by sector, without naming companies.
13 projects shown
Using AI on sensitive data normally means shipping it to an outside provider. I wanted the opposite: full AI capability without a single record leaving the perimeter.
An owned inference and AI services server, built and operated end to end. Virtualisation with a dedicated GPU in passthrough, and language, voice and document-search models running locally behind a model proxy. Network segmented into VLANs behind my own firewall, remote access over an encrypted tunnel and services published through a reverse proxy. It is the machine everything else I build runs on, and the proof the approach holds: the same result as a cloud service, without the data leaving.
Billing a monthly subscription to hundreds of customers meant chasing invoices one by one and hand-checking every payment receipt that arrived over messaging.
A daily automatic sweep of active unpaid invoices, with a personalised reminder to each customer over WhatsApp and email, with no human in the loop. Receipts sent in by customers are processed with OCR: the destination account is checked, approval number and date are extracted, and the payment is recorded, or the exception is logged with its reason. Any failure in the process raises an alert immediately.
Running a paid service for more than 150 customers, billed by connected device count, while competitors aimed denial-of-service attacks at the infrastructure.
Infrastructure deployed and operated entirely by me on AWS. Service continuity under attack: address rotation, migration to other servers and recovery without cutting customers off. Sign-ups, cancellations, support and recurring billing all handled end to end, single-handed.
Keeping an infrastructure's state and security current demands constant review that, in practice, nobody performs as often as they should.
A team of agents running local models inside an isolated virtual machine, working against the hypervisor and firewall APIs. They do more than audit: they detect changes and security findings, create virtual machines, apply rules and deploy services. No action that writes runs without prior human approval, and every one lands in a local Git repository that works as an auditable record of what was done and why.
Commercial voice-agent platforms charge by the minute and leave recordings and transcripts in a third party's hands.
Transcription, language model and speech synthesis all running locally, on a self-hosted PBX with a SIP line. The same capability as the commercial platforms, with no per-minute cost, no vendor dependency, and recordings kept inside the perimeter.
The volume of information calls was eating the sales team's time.
A phone agent backed by the property database, with RAG over the conversation script. It works out which property the caller means from the address or the listing number. It qualifies, then hands the case to a second agent with its own RAG of criteria and a function that computes viability from income. The answer comes back within the same call.
Everything that enters the firm ends up filed in its case and can be queried. Whatever is scanned on the office multifunction arrives already tagged with its metadata; the same goes for manual uploads and for documents arriving over WhatsApp, email or the website chat, which attach themselves to the client who sent them. Milestones and deadlines are extracted from every document, so each case builds its own calendar as it goes. On top of that, RAG over the document base and over Spanish case law and legislation (CENDOJ, BOE): you can chat with any case file and ask it questions.
A single chat takes the lead from the first question to full membership. It answers with RAG over the terms, filters for eligibility and, if they qualify, offers to continue: the Stripe payment widget appears inside the conversation itself. Once paid, it collects data and documents, runs OCR on them and catches the problems before a person would — an expired ID, a field that does not match — so the member can fix it on the spot. If everything checks out it registers them on the cooperative's platform; if not, it leaves them pending with a note on what is missing.
WhatsApp chatbot that replies with synthesised voice, images and video, and also listens to and transcribes the audio the customer sends. It generates quotes by integrating directly with Holded.
All four channels land in a single inbox: WhatsApp, email, the website chat and telephony through Ringover. Calls to the firm's number are transcribed automatically and arrive with a summary, key dates and the next action, so the case file stays complete without anyone taking notes.
A legal assistant on the landing page that talks to the person, understands the case and sends the lead to the CRM with a summary, the strategy to follow and a fee estimate based on the bar association's scales.
A chatbot that takes the customer's latest bill, reads it, and compares it against the retailer's API to establish whether a better price can be offered.
Build-out of the company's physical server on Proxmox and OPNsense, with segmented networks and secure remote access over VPN. Self-hosting of n8n and the rest of the stack, with services published by subdomain, leaving the infrastructure ready and free of recurring SaaS cost.
Languages and data
AI
Automation and integration
Infrastructure
Security
The first laptop
I started at fourteen, when I was given my first laptop. Then came computing books of every kind, and the habit of opening things up to see how they are built inside.
The automating habit
Everything else came from there. Years before AI was a topic, I was already building reminders and automatic alerts with Python and Selenium, driving WhatsApp Web remotely because there was no other way: repetitive work has always looked to me like a technical problem, not an obligation.
My own businesses
Then came my own. A restaurant that grew to seven employees, run on Odoo I self-hosted, with the cameras installed by me and customer acquisition automated on social media. And a subscription service with hundreds of paying customers, on my own AWS infrastructure.
I have learned all of it by building things I needed.
What I now do for others is exactly that.

If you have a process that repeats every day, or a system you want to bring onto your own infrastructure, write to me and we will take a look.
Compliant without losing the conversation
Since August 2026, Article 50 of the EU AI Act requires that whoever calls or writes knows they are being served by an automated system. It sounds harsher than it is: one well-written opening line settles it and the conversation carries on, with nobody hanging up. I design it that way from the start. And the other half comes for free: because the processing happens inside your own infrastructure, there are no transfers to justify and no third-party processors to add to your record.