FAQ Bot
Reliably answers the 20–50 most common questions. Fed from your existing FAQs, documents, and process knowledge. Ideal as a starting point.
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Chatbots & Support Automation: Reliably intercept recurring questions.
An AI-powered chatbot automatically answers standard questions, prioritizes emails, and creates structured tickets — around the clock. Your team only handles the cases that truly require human attention.
Target Audience
Who is this for?
A good fit if...
- Your support team repeatedly answers the same questions (60%+)
- Emails are reviewed, sorted, and answered manually
- Customers are waiting for answers outside of business hours
- You have an FAQ page, but no one uses it
- You run a service, IT, trades, or e-commerce business
Less suitable if...
- Every request is highly individual and complex (e.g., legal advice)
- You receive fewer than 20 support requests per week
- There are no documented answers for standard questions
Three Variants
Not all Chatbots are the same
Depending on the initial situation, I implement one of three variants — or combine them.
Support Assistant
Goes beyond FAQ: Captures requests, creates structured tickets, classifies by urgency, and routes them to the right person.
For teams of 5+Email Prioritization
Analyzes incoming emails, detects request intent and urgency, suggests reply templates, and automatically sorts into categories.
Highest time savingsBusiness Impact
Measurable Results for Customer Service
The bot resolves the majority of standard questions upon the very first contact.
Wait times are eliminated completely. Customers receive precise feedback immediately.
Automation significantly lowers operational costs.
Faster and consistent answers measurably boost customer satisfaction.
Architecture & Approach
The End-to-End Process: From Request to Resolution
A transparent workflow ensures the bot gracefully hands over complex cases to a human.
Understand Request (NLU)
The customer asks a question via Web, WhatsApp, or Email. The AI detects the intent, extracts entities, and analyzes context.
Retrieve Knowledge (RAG)
Relevant info is queried in real-time from your knowledge bases (Vector DB), FAQs, and connected systems.
Generate & Validate Answer
Based on your documents, the LLM (e.g., GPT-4o) formulates the reply. Built-in guardrails verify accuracy and compliance.
Action & Seamless Handover
The reply is sent or a backend action is triggered. If the system detects a critical request, a seamless handover occurs (including chat history) to a human agent.
Under the Hood
Technical Setup
No black-box service — you understand what’s behind it.
Retrieval-Augmented Generation (RAG)
The bot doesn't make things up freely, it searches for relevant text passages from your knowledge base first. This minimizes hallucinations and guarantees answers are driven by true company data.
Embedding & Vector Search
Documents are transformed into semantic vectors and indexed in a vector DB (e.g., Pinecone, pgvector). This helps the bot understand meaning — not just keywords.
LLM Orchestration
Base models like GPT-4o, Claude, or Open-Source — depending on privacy, latency, and budget requirements. Context window management enables multi-turn conversations.
Guardrails & Security
Output filters block unwanted answers. The bot stays on-topic and admits "I don't know" instead of hallucinating. GDPR-compliant data processing.
Multichannel Deployment
One core bot logic, multiple frontends: Website widget, email inbox, Slack, MS Teams, or WhatsApp Business. Build logic once, adapt channels.
Analytics & Feedback Loop
Dashboards revealing recognition rates, unanswered queries, and satisfaction. Every unanswered question is capitalized on to improve the knowledge base.
Typical Stack
The exact stack depends on your existing enterprise architecture and privacy needs. Open Source alternatives available for On-Premise deployments.
Frequently Asked Questions
Chatbots — Concrete Answers
Does the bot invent answers?
No — using RAG (Retrieval-Augmented Generation), every answer is rooted in your documented knowledge base. Guardrails prevent hallucinations. If the bot doesn't find a matching answer, it admits so openly and escalates.
How much prep work do I need?
Minimal. I work with what’s available: FAQ pages, support emails, process documents, manuals. I handle formatting and indexing. We verify if the baseline is adequate in the KI-Erstanalyse.
Where is data stored?
GDPR-compliant inside European data centers. Optionally fully On-Premise leveraging Open-Source models. The architecture is documented in the design phase — including data flow mapping.
Can the bot answer emails?
Yes. The email prioritization analyzes incoming emails, categorizes cases, suggests response templates, and can send standard replies purely automated — with approval gateways if preferred.
How much does a chatbot cost?
FAQ Bot inside the Starter Package begins at €2,900. Support Assistant with deeper integrations routinely falls into the Professional Package starting at €6,900. Ongoing API costs range natively depending on usage: €20–150/month.
Chatbot solutions jumpstart with the Starter Package — with fixed deliverables.
Voice AgentsWhen your customers prefer calling rather than typing.
Corporate LLMInternal AI Assistants meant for Knowledge Management.
Next Step