E-commerce
Shopping assistants that answer product questions, help with sizing and look up order status. They access the product catalogue directly, make relevant recommendations and take load off the service team at the same time.
AI chatbots
AI Chatbot Development: Chatbots That Know Your Business
In AI chatbot development, we build chatbots that understand questions in natural language, answer from your own documents and complete tasks such as booking appointments or creating tickets. Context Studios, an AI-native development studio in Berlin, develops website chatbots, internal knowledge assistants and customer service bots with hand-over to your team.
Answers from your company knowledge (RAG)German, English, French, ItalianHand-over to your teamGDPR-compliant & traceable
- Workshop
- Setup
- Sprint
- Build & Support
Fixed price after scoping · proposal within 48 h
Last updated:
(01)
What is an AI chatbot?
AI service
An AI chatbot is a dialogue system based on large language models such as Claude or GPT that understands natural language, recognises intent and accesses company knowledge through retrieval-augmented generation (RAG). Unlike rule-based bots with fixed decision trees, it also answers unexpected questions and cites the sources of its answers.
- Specialisation
- Conversational AI, RAG chatbots, customer service, internal assistants
- Technologies
- Claude, GPT, open-weight models, Vercel AI SDK, vector databases
- Target group
- Customer service teams, marketing, HR, internal knowledge management
- Project duration
- Typically 3–8 weeks, depending on the knowledge base and depth of integration
- Compliance
- GDPR-compliant, content filters, logged conversations
AI AutomationConversational AI DevelopmentAI Customer ServiceAI Assistant DevelopmentRAG Development
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What sets our AI chatbots apart?
Six qualities that matter for a business chatbot
(01)
Natural conversation
Our chatbots understand context, remember earlier statements in the conversation, ask follow-up questions when something is unclear and adapt their tone to the situation. No rigid menu that users have to click through.
(02)
Company knowledge via RAG
Through retrieval-augmented generation, the chatbot accesses your knowledge sources: product catalogues, FAQs, technical documentation and internal policies. Answers are based on your company data and cite the source, which significantly reduces misinformation.
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Multilingual & culturally aware
We set up chatbots for German, English, French and Italian. They detect the user's language automatically and respect forms of address and date formats; we check quality per language with test questions.
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Smart hand-over
If the chatbot cannot answer a question reliably or the user asks for a person, it hands the conversation over to the right colleague together with the history and a summary. Nobody has to repeat their request.
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Proactive suggestions
Instead of only waiting for questions, the chatbot offers relevant help: related articles, product suggestions or next steps. We define together with you which prompts make sense and measure their effect.
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Conversation analytics
Conversations are analysed anonymously: frequent topics, drop-off points and unanswered questions. This shows you what moves your customers and where the knowledge base, products or processes should be improved.
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How is a production-ready AI chatbot built?
From the initial call to a live chatbot in four steps.
- (01)
Initial call
Free 30-minute initial call by video. We clarify purpose, knowledge sources, channels and integrations and give you a first assessment of feasibility and timeline.
30 minutes - (02)
Proposal and planning
You receive a written proposal with scope, timeline and fixed price, plus a plan for the knowledge base, conversation rules and hand-overs to your team.
after scoping - (03)
Development and testing
Agile development with weekly demos. Goal: a first testable version in approx. 2 weeks and a ready-to-use chatbot in approx. 4 weeks, tested with real questions from your day-to-day business.
Goal: approx. 4 weeks - (04)
Launch and optimisation
Production deployment with complete documentation and 30 days of free bug fixing from final delivery. Optimisation based on real conversations and further development by agreement.
afterwards
Frequently asked questions about AI chatbot development
(01)How do modern AI chatbots differ from older chatbot systems?
Older chatbots work with rigid decision trees and keyword matching; they only understand pre-programmed questions. Modern AI chatbots are based on large language models and understand natural language, context and nuance. They respond to unexpected questions, recognise connections and phrase clear answers. For users this means they write the way they speak instead of clicking through menus.
(02)How does the chatbot avoid giving wrong information?
With RAG, answers are based on your verified company data rather than the general knowledge of the language model, and every answer cites its source. We also set confidence thresholds: if the chatbot is unsure, it says so openly and hands over to a person instead of guessing. Before launch we test with a catalogue of real questions from your daily business.
(03)Which platforms can the chatbot run on?
The chatbot can run on your website as an embedded widget or full-screen chat, in mobile apps, on WhatsApp, in Slack, in Microsoft Teams or as a standalone web app. The chatbot logic is platform-independent; for each channel we only adapt the interface. That way you maintain one knowledge base that gives the same answers everywhere.
(04)How does the chatbot learn our company knowledge?
We connect your sources: website content, FAQs, product catalogues, PDFs, manuals and internal policies. This content is indexed in a vector database and updated regularly. For every request, the RAG pipeline retrieves the most relevant passages, and the chatbot phrases an answer from them with a source reference. The language model itself does not need to be trained for this.
(05)What does an AI chatbot cost?
Costs depend on the size of the knowledge base, the number of channels, integrations with CRM or helpdesk and the requirements for data protection and hosting. On top come running costs for model calls, which depend on conversation volume. We calculate the development after a short scoping: fixed price after scoping, proposal within 48 hours.
(06)Can the chatbot take actions, not just answer?
Yes. Through tool use and API connections, the chatbot can book appointments, look up order status, create tickets, update CRM records or fill in forms. It turns from an information source into an assistant that gets things done. We define together with you which actions are allowed and when a confirmation is required.
(07)How is data protection ensured?
GDPR compliance is standard: conversations are stored encrypted, users are informed transparently about the use of AI, and consent is obtained where required. Personal data can be pseudonymised automatically. If you wish, we run the chatbot on European servers or with open-weight models on your own infrastructure.
(08)How long does it take until the chatbot is live?
The goal is a first version for internal testing after approx. 2 weeks and a ready-to-use chatbot with a basic knowledge base after approx. 4–6 weeks. Extensive knowledge bases or many integrations take correspondingly longer. After launch we keep optimising based on real conversations until answer quality and hand-overs work the way you need them to.
(09)Can the chatbot also be used internally for employees?
Yes, that is one of the most useful applications. Internal chatbots for knowledge management, IT support, HR questions or onboarding new employees make knowledge accessible that would otherwise stay hidden in documents and wikis. With roles and permissions we make sure that every person only sees the content they are allowed to access.
(10)Chatbot or live chat – which is better?
Both have their place. An AI chatbot answers recurring questions instantly and around the clock; for complex issues, negative sentiment or on request it hands over to a person and passes on the conversation history. The combination works best: the chatbot handles the volume, your team handles advice and special cases.
(11)Can the chatbot speak several languages?
Yes. Current language models handle all common languages. By default we set up chatbots for German, English, French and Italian; further languages are possible. The language is detected automatically. What matters is that the knowledge base also works in the target languages, which we check per language with dedicated test questions.
(12)Can I customise the chatbot myself?
Yes. You maintain content via your existing sources or a simple interface; changes are available to the chatbot after the next update. We define tone of voice, conversation rules and hand-over criteria together with you and document them. For new features or integrations we are available as a development partner by agreement.
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What do we build chatbots with?
(01)
AI models
ClaudeGPTGeminiLlamaMistralQwenDeepSeek
(02)
Knowledge & RAG
Vector DBs (Pinecone, Weaviate)EmbeddingsHybrid SearchMCP (Model Context Protocol)
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Channels
Web-WidgetWhatsAppSlackMicrosoft TeamsMobile Apps
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Integration & operations
Vercel AI SDKREST & WebhooksCRM & HelpdeskConvexMonitoring & Logging
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In which industries do AI chatbots help?
SaaS & software
Support chatbots that answer technical questions, guide onboarding and collect feature requests. Connected to the product documentation, the chatbot provides step-by-step instructions and resolves common problems on its own.
Healthcare
Patient chatbots for appointment booking, organisational questions and information about treatment procedures. GDPR-compliant architecture with strict separation of medical and administrative data. Not a substitute for medical advice, but relief for the practice team.
Insurance
Chatbots for claims that capture information in a structured way and accept photos, as well as policy chatbots that explain contracts and record change requests. For complex cases they always hand over to a person.
Universities & education
Student advisory chatbots that inform about degree programmes, state application deadlines and guide through enrolment, as well as library and campus chatbots for research and questions about student life.
Tourism & hospitality
Concierge chatbots that give guests recommendations, make reservations and share local tips in the guest's language. Plus hotel chatbots for check-in information and requests, and tourism chatbots for trip planning and booking.
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Examples of AI chatbot projects
Examples we can deliver with you. Stated results are targets.
Customer service
Service chatbot with hand-over to the support team
A chatbot that understands customer requests in natural language, answers from the knowledge base and hands difficult cases over to the support team with a summary, around the clock.
Goal: automated first response · Multilingual · Available 24/7
Knowledge management
Internal knowledge assistant
An assistant for employees that searches manuals, policies and wiki pages and delivers answers with source references, respecting access rights.
Source-based answers · Roles and permissions · Goal: faster onboarding
Services
Chatbot with appointment booking
A website chatbot that answers questions about services, checks free slots in the calendar and books appointments directly; special requests go to the team.
Calendar integration · Confirmation by email · Goal: fewer phone enquiries
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AI chatbot development in Berlin-Charlottenburg
- Founder AI-native since
- 2024
- Address
- Kaiser-Friedrich-Str. 6, 10585 Berlin
- Phone
- +49 30 96610664
- info [at] contextstudios [dot] ai
Related pages
Which chatbot fits your service?
Discuss purpose, knowledge sources and channels in a free 30-minute call directly with the founder. You get an honest assessment of whether a chatbot is worthwhile for you.
- First call: 30 minutes by video
- Directly with the founder, Michael Kerkhoff
- Free of charge, no obligation
Context Studios · Kaiser-Friedrich-Str. 6 · 10585 Berlin