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cRAiG: Your RAG Pipeline for Sovereign Enterprise AI
Enterprise knowledge today is scattered across Confluence, SharePoint, Office 365, or specialized applications — accessible mainly to those who know exactly where to look. This costs time, delays decisions, and ties up capacity needed elsewhere. Standard AI chatbots don't know these sources: they give generic, sometimes incorrect answers with no reliable traceability. For business-critical decisions, that isn't good enough.
With cRAiG – ConSol Retrieval Augmented Intelligent Generation – we've built our own modular RAG pipeline designed to solve exactly this: it securely connects your internal knowledge with the language model of your choice and makes it instantly usable via an OpenAI-compatible interface — in existing systems, agent frameworks, or front ends such as Open WebUI. With optional local deployment, your documents and data stay right where they belong: with you.
What cRAiG Delivers for Your Business
How RAG Works with cRAiG
Request
Employees or customers ask a question via chat.
Processing
cRAiG processes the request technically and linguistically.
Retrieval
The pipeline identifies the relevant documents from your connected data sources, such as Confluence, SharePoint, or Office 365.
Handoff
The question and relevant documents are passed to the language model of your choice.
Generation
The model generates a precise answer grounded in your content.
Output
cRAiG returns the answer via the OpenAI-compatible chat endpoint — transparently, and with source references on request.
Secure Funding for Your cRAiG Project
Many German federal states support digitalization and AI projects with attractive grants — covering up to 50% of implementation costs. We help you find and make the most of the right funding program.
Because we love IT and make AI projects succeed
- 40 years of IT expertise combined with state-of-the-art AI competence.
- Extensive open-source expertise for sovereign, independent solutions such as cRAiG.
- Cloud know-how across all major platforms, including German and European providers.
- Agile collaboration in close coordination with your team.
- Full-service consulting, implementation, and operations from a single source.
Frequently Asked Questions about RAG and cRAiG
What exactly is Retrieval Augmented Generation (RAG)?
RAG combines generative AI (LLM) with targeted access to your own data. The result: answers that are not only linguistically convincing but also grounded in your enterprise knowledge.
What sets cRAiG apart from a standard generative AI?
Standard AI often delivers generic or unreliable answers. cRAiG connects directly to your internal knowledge base — results are traceable, precise, and tailored to your business.
How secure is my data with cRAiG?
Data sovereignty is central: your information stays within your infrastructure or in sovereign EU clouds. There's no dependency on US hyperscalers and no risk of data leaks.
What use cases is cRAiG particularly well suited for?
Typical scenarios include knowledge management, chatbots for employees or customers, research and support tools, and the automation of decision-making processes — wherever knowledge needs to be put to efficient use.
Can cRAiG grow with my company?
Yes. cRAiG is built to be modular and scalable. You might start with a single use case and expand the solution step by step — all the way to an enterprise-wide AI ecosystem.
Any Questions about RAG or cRAiG?
Contact
Jan Zahalka