Whisp: AI assistant for manufacturing
Access manufacturing knowledge faster with a local AI assistant
Ask questions in natural language and get answers based on your company documents without searching through folders, files and long instructions.
See the current status of every production station, detect disruptions faster and give your teams the information they need to act.

What is explitia.Whisp?
explitia.Whisp is an AI assistant for manufacturing available in the Production Portal that operates locally, without online access. Users ask questions in natural language, while the module prepares answers using the selected scenario, conversation history and knowledge contained in your company documents.

Natural-language questions
Ask for the information you need instead of searching through folders and documents.

Company knowledge
Use information stored in the organisation’s knowledge base as context for answers.

Conversation context
Continue asking follow-up questions without starting the search again.

Configured AI scenarios
Define the assistant’s role, response method and AI model settings for different use cases.
The benefits of an AI assistant for manufacturing
Reduce the effort required to find technical and operational information scattered across company documentation.
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Start with a question instead of searching through multiple files.
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Find semantically related information in company documentation.
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Continue a topic within the same conversation.
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Make technical and operational knowledge easier to access.
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Support recurring questions with configured AI scenarios.
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Shorten the path from a question to useful manufacturing knowledge.

React before a small disruption becomes a production loss

Faster access to information
Find relevant knowledge without knowing the exact document name or location.

Less manual searching
Reduce the need to browse folders, files and individual document pages.

Better use of company knowledge
Make documented know-how easier to access for employees who need it.

Less dependence on individual experts
Support recurring questions without always starting by contacting a specialist.
How does explitia.Whisp work?

Build the knowledge base
An administrator adds company documents to the knowledge base and configures the conversation scenario.


Ask a question
The user opens explitia.Whisp and describes the problem in natural language.


Find relevant knowledge
The module takes the conversation history into account and semantically searches for matching fragments of available documents.


Generate a contextual answer
The selected AI model prepares an answer using the relevant knowledge found in the documents.


Continue the conversation
The answer is displayed to the user, the conversation is saved and the topic can be continued with follow-up questions.
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What does explitia.Whisp include?

AI chat


Conversation history


AI scenarios


Company knowledge base


Document support


AI model configuration


AI chat
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Natural-language questions
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Standard and streaming responses
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Response cancellation
Discover other modules of the Production Portal



Conversation history
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Persistent conversations
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Saved messages
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Context maintained between questions
Discover other modules of the Production Portal



AI scenarios
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Defined assistant role
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Configurable response behaviour
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Model settings
Discover other modules of the Production Portal



Company knowledge base
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RAG-based knowledge retrieval
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Semantic search
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Company documentation as answer context
Discover other modules of the Production Portal



Document support
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TXT and Markdown
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PDF and Word
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Excel
Discover other modules of the Production Portal



AI model configuration
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Configurable AI model profiles
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Integration with a local Ollama environment
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Core independent of a single model provider
Discover other modules of the Production Portal


Integrations

Production Portal

Local LLM

Document repositories

Internal knowledge bases

Company file storage

Manufacturing documentation systems
These connections can help bring company knowledge into one accessible environment and make it easier for users to find relevant information.
AI in manufacturing
Continue reading
Continue reading

See how to prepare your company for AI implementation and assess whether a project is ready for a pilot.
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Evaluate the business value of the AI use case.
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Check whether the required production data is available.
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Define how data will be processed and controlled.

Topic
AI in manufacturing

Key areas
Business value, data, control

Content type
Practical guide
Elements of explitia.Whisp

AI Chat
Lets users ask questions in natural language and receive contextual answers.

Knowledge Base
Makes selected company documents available as context for answers.

Semantic Search
Finds relevant information based on meaning rather than exact wording alone.

Conversation History
Keeps previous messages so users can continue a topic without starting again.

AI Scenarios
Define the assistant’s role, expected response method and model settings.

Local LLM
Allows the AI model to run on your infrastructure.
FAQ: AI Assistant for Manufacturing
An AI assistant for manufacturing helps employees access technical and operational knowledge through natural language questions. explitia.Whisp uses conversation context, configured scenarios and information contained in company documents to prepare answers.
The knowledge base can include company documentation such as TXT, Markdown, PDF, Word and Excel files. The module can search this information semantically and use relevant fragments as context for the AI model.
Potential users include operators, production leaders, maintenance employees, technologists, quality teams and other people who need quick access to technical or operational knowledge. Administrators can manage scenarios, AI models and knowledge base content.
A standard search usually requires users to locate and interpret documents themselves. explitia.Whisp can find semantically related information and use it to prepare an answer that takes the ongoing conversation into account.
Yes. The module maintains conversation and message history, allowing users to ask follow up questions without recreating the full context each time.
Yes. The model can run locally on the customer’s own infrastructure, so prompts and company data do not need to be sent to external systems.
No. The module currently has an advisory role. It does not independently monitor machines or perform physical actions on production equipment.
The current version focuses on knowledge stored in documents. Automatic access to live production data is not part of the current scope.
No. The module supports access to information, but answers should still be assessed by the user and actions performed according to applicable procedures.
The documented scope includes TXT, Markdown, PDF, Word and Excel files.
RAG allows the module to find semantically relevant fragments of company documentation and provide them as context to the AI model before an answer is generated.
It can make documented organisational knowledge easier to access and support recurring questions without requiring users to start by contacting a specific expert.
Yes. The module supports configurable scenarios that define the assistant’s role, expected way of answering and model settings.
No. Answers are based on the available documentation, and their quality depends on how complete and up to date it is. We recommend verifying answers before making decisions.
Make manufacturing knowledge easier to access
Ask questions, find relevant information and keep the context of your conversation directly in the Production Portal.

Ask naturally
Start with a question.

Find Company knowledge
Access relevant information from company documents.

Continue in context
Ask follow up questions within the same conversation.


