Bots that know your data – and take action.
Chatbots and agents connected to your documents and systems – for sales, support, HR, and knowledge management. With source references in their answers, developed as a custom project.
Three reasons why bot pilots often fizzle out.
The patterns that make projects fail are similar – and they rarely have anything to do with the underlying model.
Off-the-shelf bots do not know your data.
Generic AI tools answer generically – tariff sheets, contract clauses, codebooks are not in the models. Made-up answers cost more than they save.
RAG is curation, not plug-and-play.
Only a clean knowledge base turns an LLM into a reliable agent. Chunking, retrieval, re-ranking, source citations – that is engineering work, not a prompt.
Compliance slows down pilot projects.
Data protection approval, logging, source evidence, where it runs. Anyone who does not plan for this from the start fails at the first security review.
Six building blocks that separate a pilot from a product.
Building blocks we combine in custom chatbot projects, depending on your requirements.
Answers with Source Citation
Answers point to the original source – tariff sheet, contract clause, study. So every statement can be checked.
Tool Use & Actions
Agents can read from systems such as CRM or ticketing, prepare quotes, or trigger workflows – depending on the project.
RAG over Your Knowledge Base
PDFs, SharePoint, Confluence, databases – connected per project, with document-level permissions if needed.
Guardrails & Logging
Topic filters, protection against prompt injection, and conversation logging – tailored to your requirements.
Multilingual
The bot can answer in the language of the question – even if the sources are in another language.
Human-in-the-Loop
Handover to subject-matter experts when the bot finds no suitable source. Feedback is used to maintain the knowledge base.
How a deepsight agent answers a question.
Four stages, always in the same order. What changes from project to project are the data sources, tools, and depth of guardrails – not the architecture.
Knowledge Base
Consolidate documents, databases, APIs. Chunking, embedding, versioned. Permissions per source.
Retrieval
Hybrid search, re-ranking, filtering. For every query, relevant sources are returned with a score.
Tools & Model
The LLM decides and calls tools (CRM, Jira, custom APIs). Multi-step agents with plan-and-act.
Guardrails
Topic filters, masking of personal data, logging. Answers can be checked against defined rules before they are returned.
Chat with your data or your own chatbot?
Questions about survey and feedback data are answered by the chat in deepsight cloud. A chatbot for your company knowledge is something we develop as a custom project.
Ask questions about your survey data.
If you want to ask questions about your survey and feedback data, you don't need your own bot: the chat in deepsight cloud works with your analysis results.
- Ask questions about survey and feedback data
- Group comparisons, quotes, and charts as answers
- Part of deepsight cloud – no separate project needed
- Get started with a personal demo
Chatbots for your company knowledge.
Knowledge chatbots and assistants connected to your documents and systems – developed as a custom project, with a local LLM if you wish.
- Concept, development, and operations from one team
- Connection to your documents and systems per project
- Infrastructure per project – including local LLMs on your premises
- Maintenance and operations as agreed
Domain Agent. Not ChatGPT Plugin.
Generic bot platforms are quick to set up – and just as quick to shut down because compliance, source citations, or tool integration are missing. Three properties that set us apart:
- Sources instead of guesses. Answers show the original document and location. If the bot finds no suitable source, it can hand over to experts.
- Actions, not just answers. Where it makes sense, the bot reads, writes, and triggers workflows in your systems.
- Data protection from the start. DPA under Art. 28 GDPR when we process data on your behalf. Infrastructure per project – including local LLMs on your premises.
What else belongs to the solution.
Bots rarely run alone – they sit on a knowledge base, a tracking setup, or a custom platform. Here are the neighbors.
Chat with your survey and feedback data – as part of the platform, no separate project needed.
PowerPoint presentations from existing Excel data – a standalone product.
Knowledge chatbots, document extraction, special system integrations, and local LLMs.
Structured fields from documents – often the precursor to contract or sales agents.
Bring us three typical questions your users ask.
In a conversation, we look at your data sources, sketch the knowledge base, and clarify whether a custom project is the right path – or whether the chat in deepsight cloud is already enough.