Not another chatbot.
Not another RAG app.
A chatbot answers questions. A RAG app searches your documents. Hobasa connects to your live systems, cleans the data, and runs the intelligence for you.
Most "AI for your data" is one of two things.
Most tools calling themselves AI for your business are either a chatbot or a RAG app.
A chatbot is a conversation. You ask, it answers from what it was trained on plus whatever you paste in.
A RAG app is search with a language model on top. You load in a set of documents, and it answers questions grounded in those files.
Both are useful for what they do. Neither one connects to your real systems, reconciles the data across them, or does the work for you. That is the gap Hobasa was built for.
Three different things, side by side.
Chatbots and RAG apps are useful for what they do. Hobasa is a different category.
What you actually get with Hobasa.
It plugs into your systems, not a folder of documents.
A RAG app only knows what you upload. Hobasa connects to the systems your business already runs on and keeps that connection live, so the intelligence reflects reality, not last month's export.
It cleans and reconciles, so the intelligence runs on one reliable truth.
The hard part is not the AI, it is the messy, mismatched data underneath it. Hobasa normalizes and aligns data across your tools and files into one canonical model, so what you see holds together.
It is agentic and proactive. It finds what you would miss.
A chatbot waits for a question. Hobasa runs domain-trained agents that review your data continuously and flag exceptions, anomalies and leakage before you think to look.
It is run for you, not a tool you have to operate.
No prompts to engineer, no pipelines to maintain. We scope it, connect it, clean the data, validate the findings and support you. You get the outcome. We carry the operational load.
It is built for your business, not a generic assistant.
Hobasa is configured to your industry and your data, with rules validated by people who know the domain, so the output is relevant, not generic.
Enterprise security and governance, from day one.
Built for sensitive data, with access control and governance across everything. ISO 27001 certified. SOC 2 Type II in active audit.
How Hobasa compares to the big models.
We use foundation models under the hood. But sitting a chat window next to your business is not the same as running the intelligence on top of your systems. See the difference against each one.
Claude
A capable assistant in a chat window.
- Great at reasoning inside a conversation
- Doesn't connect to your live systems
- You still have to ask, phrase and validate
ChatGPT
A general-purpose assistant for everyone.
- Broad knowledge, plus files you upload
- No reconciliation across your systems
- Answers depend on prompts and pasted context
Gemini
A powerful model tied to Google's stack.
- Strong multimodal and Workspace integrations
- Not built to run your finance and workforce data
- Reactive: you drive, it answers
This is not a knock on chatbots or RAG.
Chatbots are great for answering questions. RAG apps are great for searching a body of documents. If that is all you need, use them.
Hobasa is not trying to be a better chatbot. It is a different category: the connected, cleaned, run-for-you intelligence layer that sits on top of your systems. Use it when the answer lives between your systems and someone needs to find it, prove it and act on it.
A chatbot answers. A RAG app retrieves. Hobasa runs the operation.
Connected, clean, intelligent, and run for you, on top of the systems you already use.