QBIT42 provides a no-code platform for building custom Generative AI applications and agents using enterprise data. The platform utilizes RAG technology to ensure reliable, hallucination-free outputs while maintaining maximum data security with local processing guarantees. This enables teams across all departments to deploy tailored AI solutions that optimize internal processes and enhance customer experiences.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises need to apply generative AI to internal workflows but face unreliable outputs (hallucinations), strict data‑security requirements, and a shortage of in‑house AI development expertise.
Solution
QBIT42 delivers a no‑code platform that lets business users create custom generative‑AI applications and autonomous agents anchored to proprietary data. The system uses retrieval‑augmented generation (RAG) to pull information from secure knowledge bases, ensuring answers are grounded and hallucination‑free. All processing—from prompt ingestion to model inference and response—remains within German‑based, compliance‑certified infrastructure, guaranteeing data residency and preventing external model training. Users build and deploy agents through a visual drag‑and‑drop workflow editor, selecting from multiple large language models without writing code. Fine‑grained permission and role controls isolate data per department, while guardrails enforce content policies. The resulting AI assistants automate support, report generation, and knowledge‑twin functions, delivering measurable efficiency gains across the organization.
Target Audience
Primary customers are enterprise departments such as customer support, knowledge management, and operations that require secure, low‑code AI automation while maintaining strict data‑privacy compliance.
Features
- Retrieval‑augmented generation (RAG) engine that indexes proprietary documents and returns source‑grounded answers, eliminating hallucinations
- No‑code visual workflow builder with drag‑and‑drop components for orchestrating LLM calls, data retrieval, and post‑processing logic
- Multi‑LLM support allowing selection of optimal models per use case, all hosted on secure German data centers with end‑to‑end encryption
- Role‑based access control and configurable permission matrices that isolate knowledge bases and agent outputs by team or department
- Built‑in guardrails and policy templates to restrict sensitive topics and enforce compliance automatically
- Pre‑packaged agent templates (e.g., AI support desk, multilingual report generator, digital knowledge twin) that can be customized via a chat‑style interface
- API and webhook integrations for connecting agents to existing CRM, ERP, or ticketing systems without additional development
- Continuous learning loop that captures user feedback to refine knowledge base relevance and improve response accuracy over time