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TECNOLOGIX

Solutions · AI agents

An AI development company that builds AI agents around your business

The assistant bundled into your SaaS has never seen your stock, your prices or your customer history. As an AI development company we build the agents that have: connected to your own systems, working on web chat, WhatsApp and the workflows your team runs every day, with the code yours by contract.

What we build
A man with headphones around his neck types at a desk facing two wide monitors and a laptop filled with sales and analytics dashboards

Your AI already answers. Does it know anything about your business?

Subscription assistants sound fluent and know nothing: not your stock, not your prices, not your policies, not who the customer on the other side is. They cannot read your database or write to your CRM, so every answer that actually matters still ends with a human. Custom AI development closes that gap: the same models, connected to your data and allowed to act inside your systems.

  • Generic chatbots that frustrate customers because they know nothing about your business.
  • Valuable data locked inside systems your subscription AI cannot read.
  • Repetitive reading and classification work that eats hours from your team every week.
  • Sensitive data you are not willing to hand over to someone else's black box.

What we build

AI that knows your operation, not AI that sounds confident

AI agents that act, not just reply

An agent reads the request, looks it up in your systems and completes the action. Answering is the easy part.

  • Checks stock, prices and order status in real time
  • Creates records, tickets and appointments on its own
  • Hands over to a person when it should

AI features inside your product

Generation, summarizing and drafting embedded where your users already work, instead of a separate tool nobody opens.

  • Drafts, summaries and replies in context
  • Semantic search across your own content
  • Built into your app, not bolted on beside it

AI inside business workflows

Classification, extraction and routing applied to the repetitive reading your team does by hand today.

  • Reads invoices, contracts and forms and extracts the fields
  • Classifies and routes incoming requests automatically
  • Escalates whatever falls below a confidence threshold

RAG over your own data

The model answers from your documents, catalogs and history, and cites where each answer came from.

  • Indexing of manuals, policies, catalogs and tickets
  • Answers with a source, so they can be verified
  • Your data stays in your infrastructure

Web chat, WhatsApp and handoff

The same agent across the channels your customers already use, with everything logged in your CRM.

  • Official WhatsApp API and web chat
  • Handoff to a human with the full conversation history
  • Every interaction written back to your CRM

Typical situations

What this looks like in production

Customer service

Pain

Repeat questions about products, status and hours arriving on web chat and WhatsApp at all hours.

Solución

AI agent connected to the client's own catalog and systems, answering on web chat and WhatsApp and escalating what needs a person.

AI agents live on web chat and WhatsApp

Market intelligence

Pain

Competitor prices and public listings tracked by hand in spreadsheets, always out of date by the time anyone read them.

Solución

Automated collection running around the clock, cleaned and loaded into a BI dashboard the team actually opens.

Scraping and BI running 24/7

Sales teams

Pain

Leads arriving on WhatsApp and dying there, invisible to the CRM and to management.

Solución

CRM connected to the official WhatsApp API, with assignment, history and an automatic first response.

First reply under 2 minutes, live in 3 weeks

FAQ

What clients ask before starting

What is the difference between an AI agent and a chatbot?

A chatbot follows a script: it recognizes a phrase and returns a prepared answer, and anything outside the script ends in "let me connect you with an agent". An AI agent works the other way around: it understands the request in its own words, decides which tools it needs, queries your systems and completes an action, such as checking an order, booking a slot or opening a ticket. The practical difference is not how it sounds, it is what it can do. A canned assistant from a SaaS vendor can only reply from what it was given; an agent built on your data knows your inventory, your prices and your policies because it is reading them.

What happens to my data and who can see it?

Your data stays in your infrastructure. The agent queries it through APIs you control, with its own credentials and its own permission scope, so it can only read and write exactly what you allowed. What goes to the model is the fragment needed to answer that specific question, not your database. We configure providers in the modes that do not use your content for training, we can redact sensitive fields before anything is sent, and every query is logged so you can audit later what was consulted and by whom.

Which models do you use and who pays for the usage?

We are not tied to one vendor. We pick the model per task, since classifying a document and holding a conversation do not need the same thing, and for sensitive data an open model running on your own infrastructure is an option. Usage can be billed by the provider straight to your own account, under your own keys, if that is what you prefer: you watch the consumption in real time and you are not depending on us to change it. We can also run it on our side. Either way we set it out in the proposal, we explain which model each part uses and why, and the design keeps you able to switch models later without rewriting the system.

How does it integrate with the systems I already have?

Through the interfaces your systems already expose: REST APIs, webhooks, direct database access or the vendor's connector, depending on what each one offers. If a system has no API, we work with scheduled file exchange or controlled scraping. The agent does not replace your ERP, CRM or e-commerce platform, it talks to them: it reads what it needs to answer and writes back what it resolved, so the record lives where your team already looks for it.

How long until it is in production?

We start with a free 30-minute audit to map which conversations or tasks are worth automating first, and within 48 hours you get a written proposal with scope, phases and a fixed cost per phase. From there we work in weekly sprints, each closing with a demo you can try yourself. The first version goes live on a narrow, well-defined scope, and we widen it against real conversations. What stretches the timeline is how many systems it has to integrate with and how much of your knowledge is written down versus living in people's heads.

What happens if the model gets something wrong?

You design for it instead of hoping it will not happen. Every agent runs with limits: what it may do on its own, what needs human confirmation, and when it has to say it does not know. Anything below the confidence threshold is escalated to a person with the full context, actions that touch money or contracts require approval, and answers are grounded in your documents with a source attached so they can be verified. Every conversation is logged, and we review them with your team to correct what needs correcting.

Ready to boost your business performance?

Let's talk about building it together. No commitment.

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