Question 1

AI consulting in Dublin: what affects the price?

Accepted Answer

It depends on where the AI is built in (CRM, ERP, documents, email), the volume of data and your security requirements. Before building we agree a measurable goal, a test set of examples and a monthly cap on model cost. You get a written estimate after we review the scope.

Question 2

AI consulting in Dublin: what is specific to the local market?

Accepted Answer

Enterprise AI usually fails on integration, not on the model. We connect an existing model to the systems you already run, keep prompts and data on your side so a provider change is not a rewrite, and start with one measurable task rather than five at once.

Question 3

What should a company in Dublin prepare before an AI integration?

Accepted Answer

One concrete use case, a sample of real examples (documents, emails, tickets) and a named person who approves the output. With those we agree a measurable target and test the result against your examples before it goes live.

Question 4

Where are you based, and do you work with companies in Dublin?

Accepted Answer

We are based in Split, Croatia (Peričićeva 14). We work with companies in Dublin in writing, the same way for every city: you describe the project in the form, and the engineers who will build it reply.

Question 5

Can you integrate AI into my existing system without a rewrite?

Accepted Answer

Yes. AI Retrofitting is our core speciality. We use n8n workflow automation and LangChain to connect your existing SQL databases, ERP systems, CRMs, or legacy tools with modern LLMs without modifying your core system. The AI layer sits alongside your existing infrastructure, reading data through secure API connections and delivering document analysis, automated reporting and smart search without requiring a rewrite of what already works.

Question 6

Which AI models do you work with?

Accepted Answer

We work with the leading AI models: OpenAI, Anthropic Claude, Google Gemini, and open-source models (Mistral, Llama) for data-sensitive or air-gapped deployments. Model selection is driven by your use case, data volume, latency needs, and budget. For most business applications we use a stronger model for reasoning tasks and smaller models for high-volume classification. All integrations are model-agnostic by design, so you can switch providers without rebuilding the pipeline.

Question 7

How is our proprietary business data protected?

Accepted Answer

Your data is not used to train public models: we use API access, where OpenAI and Anthropic do not train on your data by default. With a RAG architecture, your documents sit in a private vector database hosted in the EU, and the model only sees the passages needed for each answer. For regulated industries (healthcare, finance, legal), we deploy via Azure OpenAI or AWS Bedrock with EU data residency and audit logging. Data encryption at rest (AES-256) and in transit (TLS) is standard on every project.

Question 8

How long does an AI integration take?

Accepted Answer

Timeline depends on scope. Simple integrations, like adding an AI chatbot to an existing website or automating document classification, move fast. Complex projects involving legacy ERP connections, multi-channel deployment, and custom RAG pipelines with LangChain and Pinecone take longer and run in phases. For complex systems a paid audit first maps data flows and success metrics, which is what confirms your real timeline and fixed price before development begins.

AI Consulting in Dublin