Artificial intelligence
Digital transformation has hardly captured a sector as profound as education and research. In this era of change, artificial intelligence (AI) develops from a futuristic concept to an indispensable tool that ...
RAG · enterprise search · GDPR · Made in Germany
AI knowledge base: answers with citations, not document scavenger hunts
For mid-sized companies: RAG with directory-aware access—expertise stays findable and auditable – delivery and project ownership from Germany (Leer/East Frisia), named contacts, no offshore guesswork.
- 250+ delivered projects
- 5.0 stars on Google
- 100% engineering in Germany
Secure valuable company knowledge permanently – before it retires with experienced employees. Our AI-powered knowledge base makes implicit knowledge searchable, usable, and accessible to new generations.
Our Knowledge Base Services
Knowledge Transfer from Experts
Capture and preserve expert knowledge.
- Expert Interviews
- Process Documentation
Intelligent Search
AI-powered search in documents and processes.
- Semantic Search
- Context Understanding
Chatbot Access
Natural language access to company knowledge.
- AI Chatbot
- Quick Onboarding
AI Knowledge Base: Preserving Institutional Knowledge with RAG
The knowledge risk every organization shares
Every organization faces the same invisible crisis. Decades of institutional knowledge sit in the heads of experienced employees. They will eventually retire or move on.
Wikis and manuals capture only part of that expertise. Written content also goes stale quickly.
Our AI-powered knowledge bases use Retrieval-Augmented Generation (RAG). They turn scattered documents, process guides, and expert insight into a living, searchable layer. New team members can query it in natural language from day one.
How our RAG architecture works
We connect large language models to your company data sources. Sensitive information does not need to go to external providers.
We index content from SharePoint, Confluence, file servers, ticketing systems, and databases. Chunking keeps context and relationships intact.
When someone asks a question, the system retrieves the most relevant passages. It generates a precise, source-cited answer. Users can verify it against the original documents.
Access control and security
Access control is critical. Many knowledge base projects overlook it.
Our systems respect permissions from your identity infrastructure. Users only see answers built from documents they may read.
That granular model lets one knowledge base serve multiple departments. You reduce the risk of HR content surfacing in engineering queries or finance data reaching the wrong audience.
Continuous improvement
The value of an AI knowledge base grows over time. It scales with your organization.
Scheduled sync indexes new documents from source systems. User interactions feed signals that improve retrieval.
We build evaluation pipelines that score answers against curated test sets. That helps catch quality drift before users feel it.
For teams facing demographic change or rapid scaling, this turns knowledge preservation into a strategic advantage.
Frequently Asked Questions
FAQ: Leadership-style prompts—clear answers
From leadership & IT (prompt-style questions)
Context: Mid-sized machinery manufacturer, ~120 employees, manuals in SharePoint, troubleshooting knowledge in Jira. / Task: Staff should ask in plain language and get answers tied to specific documents—not classic intranet full-text search. / Question: What architecture is the usual enterprise approach for that?
The usual enterprise standard is RAG (Retrieval Augmented Generation): your content is chunked and indexed with vector embeddings; at query time the best-matching passages are passed to the language model and the reply cites those sources. We connect SharePoint and Jira via connector or API; search honours roles from your directory (e.g. Microsoft Entra ID) so nobody sees more via the AI than in the source system.
Context: HR and customer contracts; none of it must be used to improve public base models (GPT-style). / Question: What technical and organisational levers do you use so our PDFs and tickets do not become provider training data?
You avoid training use by choosing API terms that prohibit providers from training on your inputs and by never uploading raw documents to consumer UIs like free ChatGPT. Technically, chunk stores and metadata stay under your control (EU hosting or on-prem); organisationally we align data flows, roles and audit logging for the EU AI Act and GDPR.
Context: Board budget sign-off; first phase ~1,000 documents plus ticketing integration. / Question: What lower-bound fixed-price band in EUR excl. VAT is realistic for a pilot before I write an RFP?
A pilot with roughly 1,000 indexed documents and typical system integration at Groenewold IT starts from about EUR 15,000 one-off excl. VAT. Narrow the range and monthly follow-on costs in our AI knowledge base cost calculator. Beyond that, budget hosting, operations, support and usage-based LLM API charges.
Context: Business unit supplies prioritised test questions; IT provides API access to Jira. / Question: In what calendar window is a first testable pilot realistic for our internal support team?
With an approved corpus and stable APIs, a first testable pilot in four to six calendar weeks is typical. We use the first third for source approvals and permissions, the second for ingestion and retrieval tuning, the third for user testing and sign-off. Book a binding scope slot via schedule appointment.
Context: Board wants KPIs, not a vague “better search” story. / Question: Which three metrics suit a B2B pilot for an AI knowledge assistant—measurable and comparable?
Use median handling time per ticket (minutes), first-level resolution rate without escalation to tier two, and time to first correct answer in the pilot team; measure a four- to eight-week baseline before go-live and the same metrics for eight weeks after. Add sampled quality checks against a curated question list (correct source, no fabrication).
Clarify scope and sources for your pilot
Concrete next steps—not a slide deck pitch.
Book an intro callUp to 50% of your investment via BAFA/KfW
Use our funding calculator to see which government grants may apply to your project.
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