More accurate answers
The assistant relies on your real documents and data, not only the model’s generic knowledge.
AI solution development for business
We create AI tools tailored to real processes: internal assistants, chatbots, recommendation systems, document analysis, content generation, task automation and RAG solutions connected to your company data.
We integrate AI into real products, processes and platforms
AI can save time, improve customer support and unlock new features — but only when it is properly connected to company data, tools and processes.
At Digitup we design and implement complete solutions: backend, frontend, database, prompts, context, business rules, integrations and control panels. The goal is useful AI inside the product or daily operations — not an isolated experiment.
What we can build with AI
Internal assistants for teams
Tools that help employees query information, resolve questions, analyze documents, generate answers or automate repetitive tasks.
Learn moreCustomer chatbots
Assistants that answer questions, recommend products, check availability, handle requests and escalate conversations to human agents.
Learn moreRAG over your own documents and data
Systems that let people query internal information, PDFs, databases, websites or corporate docs in natural language.
Learn moreContent generation and improvement
Tools to create, rewrite, translate, summarize, classify or adapt content across languages, formats and channels.
Learn moreProcess automation
Flows that combine AI, APIs and business rules to reduce manual work in support, sales, admin, operations or marketing.
Learn moreConversation and document analysis
Message classification, data extraction, intent detection, summaries and automatic prioritization of requests.
Learn moreRAG: AI connected to your company information
We build RAG systems so an assistant can answer using real business information: documents, databases, FAQs, contracts, internal pages, products, bookings, policies or any structured or unstructured source.
Less made-up information
Cuts hallucinations by grounding each answer in retrievable company sources.
Query your own data
Ask in natural language about PDFs, FAQs, databases or internal pages.
Update content without retraining models
Update documents or sources and the system uses them without retraining the LLM.
Integration with internal panels
Fits into the tools and workflows your teams already use every day.
Permission and source control
You decide who sees what and can audit where each answer comes from.
We work with different models for each case
Not every project needs the same model. We choose by quality, speed, cost, privacy and task type.
The key is not using “the most famous AI”, but choosing the right architecture so the solution is useful, stable and sustainable.
- OpenAI
- Gemini
- Anthropic
- DeepSeek
- Perplexity
Our process for AI projects
We analyze the use case
We identify which part of the process AI can improve and which data or tools must be connected.
We design the architecture
We define model, backend, database, prompts, memory, RAG, rules and conversation flows.
We create a first version
We develop a functional prototype to validate answers, cost and real usefulness.
We integrate with your systems
We connect AI to WhatsApp, web, CRM, PMS, ERP, Google Sheets, Stripe, databases or external APIs.
We launch and optimize
We monitor usage, quality, cost, errors and improvements needed to evolve the system.
OpenAI, Gemini, AnthropicRAG and documentsAgents and assistantsAI built into productsFrom idea to production
Specialised services
Which AI service does your business need?
It depends on what the AI has to do: run tasks in your systems, answer from your documents, handle WhatsApp or the phone, or move data between tools. Pick the need closest to yours.
I want the AI to do tasks in my systems, not just answer
AI agents
Agents that read your email, your documents and your CRM, prepare the work and carry it out following your rules. A person approves the steps that require it and every action is logged.
View serviceWe want to use ChatGPT, Claude or Gemini in our tools
AI integration
We connect models from OpenAI (GPT), Anthropic (Claude), Google (Gemini) or other providers to your CRM, ERP, website, app or WhatsApp. We choose the model by task, quality, cost, speed and privacy.
View serviceWe need an assistant that answers from our documents
RAG for business
An assistant that searches your manuals, contracts or catalogue, answers from that information and cites the source, with per-user permissions. We applied it to the Mundomar Cruceros catalogue.
View serviceWe get too many enquiries on WhatsApp
WhatsApp AI chatbot
A chatbot on the official WhatsApp Business API that answers from your company information, queries your CRM or calendar and hands the conversation to a person when needed.
View serviceWe can't pick up every call
AI voice agent
A virtual receptionist that answers the phone, resolves frequent questions, manages appointments and takes details. If it cannot answer, it passes the call to your team.
View serviceWe move data by hand from one tool to another
Process automation
Workflows that connect APIs, CRMs, ERPs, Stripe, Google Sheets, WhatsApp or email, with AI models where they are needed. At Deliciosos Ramos, the notifications for each order go out on their own when its status changes.
View serviceFrequently asked questions
What is an AI solution for business?
It is a tool connected to your data, processes and systems (CRM, documents, WhatsApp, databases, etc.) that uses language models to automate tasks, answer questions or generate useful day-to-day content.
What is RAG and when does it make sense?
RAG (Retrieval-Augmented Generation) lets an assistant answer using your company’s real information — documents, FAQs, databases or internal pages — instead of guessing. It makes sense when you need accuracy and source control.
Which AI models do you work with?
We integrate OpenAI, Gemini, Anthropic, DeepSeek, Perplexity or others based on quality, cost, speed, privacy and task type. There is no single model for every project.
How long does an AI project take?
It depends. A useful first version can often be validated in weeks if the scope is clear; complex integrations with multiple systems and internal panels may need more phases.
Can AI connect to our current systems?
Yes. We can connect the solution to WhatsApp, web, CRM, ERP, Google Sheets, Stripe, databases or custom APIs so it becomes part of real business workflows.
What is the difference between a chatbot and an AI agent?
A chatbot converses: it answers questions using your company information and hands the conversation to a person when needed. An AI agent also acts in your systems: it reads an email, updates the CRM or prepares a document following your rules, with human approval for anything that commits your company. Many projects combine both. We explain it with examples in our guide to chatbots and AI agents and on the AI agents service page.
Do we need to train an AI model on our company data?
For an assistant to answer with your company information, normally not. With RAG, the assistant searches your documents at the moment of answering, so updating a document is enough to change the answer, with no model retraining. You can also control which sources each user sees and check where each answer comes from. We explain it on RAG for business.
How much does a custom AI project cost?
Digitup Studio projects start at €1,000. The price depends on what the AI has to do, the channels it works on (web, WhatsApp or Telegram), the systems it connects to and how much information it handles: a web chatbot with your company information is closer to the minimum, and integrations or custom software raise it. Besides development, the AI model has a usage cost, which can be capped by design. Depending on the project, you can contract it as a fixed project, with flexible payment over 6 or 12 months, or with a monthly fee (Build & Run); we explain it in ways of working.
Want to apply AI in your company?
We can help identify the best use case, design the solution and build a production-ready tool.
Talk about my AI project