Smart work with AI: How intelligent assistants are changing everyday working life<\/h1>\n<\/div>As part of several customer projects, BITS has developed modern AI assistance solutions<\/strong> that make day-to-day work noticeably more efficient. The aim was to enable employees to securely access internal company information and documents<\/strong> via large language models (LLMs)<\/strong>, thereby accelerating the exchange of knowledge.<\/p>\n<\/div>![\"smart](\"https:\/\/www.mybits.de\/wp-content\/uploads\/2025\/10\/smart_work_ki_automatisierung_titel.png\" "\\"smart")
<\/span><\/div><\/i><\/span><\/div>40% faster information search<\/h2><\/div><\/div>RAG-based AI facilitates access to company knowledge<\/div><\/div><\/div><\/i><\/span><\/div>Significantly shorter familiarization times<\/h2><\/div><\/div>Onboarding assistants speed up the integration of new employees<\/div><\/div><\/div><\/i><\/span><\/div>Greater transparency & compliance<\/h2><\/div><\/div>Monitoring and audit logs create trust and security<\/div><\/div><\/div><\/div><\/div>The solutions support a wide range of use cases – from onboarding new employees<\/strong> and formulating emails<\/strong> in Outlook to creating documents and presentations<\/strong> as well as targeted information searches<\/strong>.<\/p>\nData sources such as SharePoint, Confluence, Jira<\/strong> and proprietary systems were connected via a Retrieval Augmented Generation (RAG)<\/strong> concept and processed securely via Azure AI Services<\/strong>. Users can interact with the AI via a browser-based chat interface <\/strong>or integrations in Outlook<\/strong>, Windows and MacOS<\/strong>. <\/p>\nA particular focus was placed on monitoring and audit logs<\/strong> in order to make the use of AI transparent and traceable. This enables companies to evaluate usage, track audit trails and continuously optimize the effectiveness of AI solutions.<\/p>\n<\/div><\/div><\/div><\/div><\/div>Challenge<\/h2>\n<\/div>Various technical and organizational challenges had to be overcome during the introduction of AI assistance systems:<\/p>\n<\/div>
- <\/i><\/span>\n
Heterogeneous data landscapes:<\/strong> Company knowledge was distributed in different systems such as SharePoint, Confluence and Jira.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Confidentiality & compliance:<\/strong> Data residency requirements in the EU and compliance with the EU AI Act had to be taken into account.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Model diversity:<\/strong> Different use cases required different LLMs (e.g. GPT-4\/5, Llama 3\/4, Claude, Mistral, Gemini, DeepSeek).<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Multimodal content:<\/strong> In addition to text, information from PDFs, Office documents and images also had to be processed.<\/p>\n<\/div><\/li><\/ul><\/div><\/div>- <\/i><\/span>\n
Monitoring & governance:<\/strong> Transparency regarding the use of AI was a key component for audits and compliance.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
User acceptance:<\/strong> Employee training and workshops were crucial to using AI productively and safely in everyday life.<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Scalability:<\/strong> The solutions had to be flexibly adaptable to different company sizes and expansion stages.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div><\/div><\/div>Realization<\/h2>\n<\/div>BITS developed a modular AI architecture<\/strong> that adapts flexibly to existing system landscapes in order to realize the different use cases of the customers. The central element of the solution is RAG-based knowledge access (Retrieval Augmented Generation)<\/g>, which structures information from sources such as SharePoint, Confluence, Jira and internal systems and prepares it for use by Large Language Models. This allows employees to interact with company knowledge in natural language – be it via a browser-based chat, directly in Outlook or via a Windows Assistant. <\/p>\nThe technical basis is the Azure AI infrastructure with data storage in the EU<\/strong>, supplemented by the mybits.ai backend<\/strong>, which integrates various models such as GPT-4\/5, Llama, Claude, Mistral, Gemini and DeepSeek. This flexible choice of model makes it possible to achieve the optimum balance of performance, data protection and costs for every use case. In addition, feedback mechanisms<\/strong> and usage monitoring<\/strong> ensure continuous improvement in response quality and transparency in daily use. <\/p>\nThe technical implementation was flanked by holistic change management<\/strong>. Employees were specifically introduced to the productive use of AI<\/strong> in workshops<\/strong>, training courses <\/strong>and joint use case sessions<\/strong>. This resulted not only in a functioning technical solution, but also in sustainable acceptance and expertise in dealing with AI assistance systems<\/strong>.<\/p>\n<\/div>- <\/i><\/span>\n
Central knowledge access<\/strong>: via RAG-based architecture with direct source linking<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Secure cloud infrastructure<\/strong>: based on Azure AI Services with EU data storage<\/p>\n<\/div><\/li><\/ul><\/div><\/div>- <\/i><\/span>\n
Flexible model integration<\/strong>: different LLMs for different use cases<\/p>\n<\/div><\/li>- <\/i><\/span>\n
Monitoring & feedback loops<\/strong>: for optimization, transparency and governance<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div>Conclusion<\/h2>\n<\/div>The projects impressively demonstrate how AI assistance systems<\/strong> can be established as an integral part of modern working environments<\/strong>. The combination of technical innovation<\/strong>, data protection compliance<\/strong> and organizational support<\/strong> has created a solution that combines productivity, transparency and security. <\/p>\n\n- Smart work with AI means reducing routine work, making knowledge available more quickly and relieving employees.<\/strong><\/li>\n
- The modular architecture enables individual adaptations for different company sizes and industries<\/strong>.<\/li>\n
- Monitoring and audit logs ensure trust<\/strong> and traceability<\/strong> in use.<\/li>\n
- Workshops and training courses ensure the successful use of AI in the company<\/strong> in the long term.<\/li>\n<\/ul>\n
Turning technology into real added value: smart work with AI – for more efficiency, transparency and innovation in everyday working life<\/strong>.<\/p>\n<\/div><\/i>\nOur aim was to integrate AI safely and practically into everyday working life. The projects clearly show that when technology, data and people work together harmoniously, the result is real smart work – efficient, transparent and future-oriented.<\/p>\n<\/div><\/div><\/span><\/blockquote>![\"theresa](\"data:image\/svg+xml,%3Csvg%20xmlns%3D%27http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%27%20width%3D%27800%27%20height%3D%27800%27%20viewBox%3D%270%200%20800%20800%27%3E%3Crect%20width%3D%27800%27%20height%3D%27800%27%20fill-opacity%3D%220%22%2F%3E%3C%2Fsvg%3E\")
<\/span>Theresa Herbig<\/strong>, <\/span>Chief of Staff & AI Initiatives, BITS GmbH<\/span><\/span><\/div><\/div><\/div><\/div><\/div><\/div>Project roles at a glance<\/h2>\n<\/div>BITS experts took on the following roles in this project.<\/p>\n<\/div><\/div><\/div>\n
- <\/i><\/span>\n
IT-Consulting\/Consulting<\/p>\n<\/div><\/li>
- <\/i><\/span>\n
IT Project Management<\/p>\n<\/div><\/li>
- <\/i><\/span>IT and AI system architecture<\/div><\/li>
- <\/i><\/span>\n
RAG-Engineering<\/p>\n<\/div><\/li><\/ul><\/div><\/div>
- <\/i><\/span>\n
Fullstack development<\/p>\n<\/div><\/li>
- <\/i><\/span>\n
Prompt\/context engineering<\/p>\n<\/div><\/li>
- <\/i><\/span>Infrastructure \/ Operation<\/div><\/li>
- <\/i><\/span>DevOps<\/div><\/li><\/ul><\/div><\/div>
Tools & Technologies<\/h2>\n<\/div>The following tools and technologies were used in this project.<\/p>\n<\/div>
As part of several customer projects, BITS has developed modern AI assistance solutions<\/strong> that make day-to-day work noticeably more efficient. The aim was to enable employees to securely access internal company information and documents<\/strong> via large language models (LLMs)<\/strong>, thereby accelerating the exchange of knowledge.<\/p>\n<\/div> The solutions support a wide range of use cases – from onboarding new employees<\/strong> and formulating emails<\/strong> in Outlook to creating documents and presentations<\/strong> as well as targeted information searches<\/strong>.<\/p>\n Data sources such as SharePoint, Confluence, Jira<\/strong> and proprietary systems were connected via a Retrieval Augmented Generation (RAG)<\/strong> concept and processed securely via Azure AI Services<\/strong>. Users can interact with the AI via a browser-based chat interface <\/strong>or integrations in Outlook<\/strong>, Windows and MacOS<\/strong>. <\/p>\n A particular focus was placed on monitoring and audit logs<\/strong> in order to make the use of AI transparent and traceable. This enables companies to evaluate usage, track audit trails and continuously optimize the effectiveness of AI solutions.<\/p>\n<\/div><\/div><\/div><\/div><\/div> Various technical and organizational challenges had to be overcome during the introduction of AI assistance systems:<\/p>\n<\/div> Heterogeneous data landscapes:<\/strong> Company knowledge was distributed in different systems such as SharePoint, Confluence and Jira.<\/p>\n<\/div><\/li> Confidentiality & compliance:<\/strong> Data residency requirements in the EU and compliance with the EU AI Act had to be taken into account.<\/p>\n<\/div><\/li> Model diversity:<\/strong> Different use cases required different LLMs (e.g. GPT-4\/5, Llama 3\/4, Claude, Mistral, Gemini, DeepSeek).<\/p>\n<\/div><\/li> Multimodal content:<\/strong> In addition to text, information from PDFs, Office documents and images also had to be processed.<\/p>\n<\/div><\/li><\/ul><\/div><\/div> Monitoring & governance:<\/strong> Transparency regarding the use of AI was a key component for audits and compliance.<\/p>\n<\/div><\/li> User acceptance:<\/strong> Employee training and workshops were crucial to using AI productively and safely in everyday life.<\/p>\n<\/div><\/li> Scalability:<\/strong> The solutions had to be flexibly adaptable to different company sizes and expansion stages.<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div><\/div><\/div> BITS developed a modular AI architecture<\/strong> that adapts flexibly to existing system landscapes in order to realize the different use cases of the customers. The central element of the solution is The technical basis is the Azure AI infrastructure with data storage in the EU<\/strong>, supplemented by the mybits.ai backend<\/strong>, which integrates various models such as GPT-4\/5, Llama, Claude, Mistral, Gemini and DeepSeek. This flexible choice of model makes it possible to achieve the optimum balance of performance, data protection and costs for every use case. In addition, feedback mechanisms<\/strong> and usage monitoring<\/strong> ensure continuous improvement in response quality and transparency in daily use. <\/p>\n The technical implementation was flanked by holistic change management<\/strong>. Employees were specifically introduced to the productive use of AI<\/strong> in workshops<\/strong>, training courses <\/strong>and joint use case sessions<\/strong>. This resulted not only in a functioning technical solution, but also in sustainable acceptance and expertise in dealing with AI assistance systems<\/strong>.<\/p>\n<\/div> Central knowledge access<\/strong>: via RAG-based architecture with direct source linking<\/p>\n<\/div><\/li> Secure cloud infrastructure<\/strong>: based on Azure AI Services with EU data storage<\/p>\n<\/div><\/li><\/ul><\/div><\/div> Flexible model integration<\/strong>: different LLMs for different use cases<\/p>\n<\/div><\/li> Monitoring & feedback loops<\/strong>: for optimization, transparency and governance<\/p>\n<\/div><\/li><\/ul><\/div><\/div><\/div> The projects impressively demonstrate how AI assistance systems<\/strong> can be established as an integral part of modern working environments<\/strong>. The combination of technical innovation<\/strong>, data protection compliance<\/strong> and organizational support<\/strong> has created a solution that combines productivity, transparency and security. <\/p>\n Turning technology into real added value: smart work with AI – for more efficiency, transparency and innovation in everyday working life<\/strong>.<\/p>\n<\/div> Our aim was to integrate AI safely and practically into everyday working life. The projects clearly show that when technology, data and people work together harmoniously, the result is real smart work – efficient, transparent and future-oriented.<\/p>\n<\/div><\/div><\/span><\/blockquote> BITS experts took on the following roles in this project.<\/p>\n<\/div><\/div><\/div>\n IT-Consulting\/Consulting<\/p>\n<\/div><\/li> IT Project Management<\/p>\n<\/div><\/li> RAG-Engineering<\/p>\n<\/div><\/li><\/ul><\/div><\/div> Fullstack development<\/p>\n<\/div><\/li> Prompt\/context engineering<\/p>\n<\/div><\/li> The following tools and technologies were used in this project.<\/p>\n<\/div><\/span><\/div>40% faster information search<\/h2><\/div>
Significantly shorter familiarization times<\/h2><\/div>
Greater transparency & compliance<\/h2><\/div>
Challenge<\/h2>\n<\/div>
Realization<\/h2>\n<\/div>
Conclusion<\/h2>\n<\/div>
\n
![\"theresa](\"https:\/\/www.mybits.de\/wp-content\/uploads\/2025\/06\/theresa_bits.png\")
Project roles at a glance<\/h2>\n<\/div>
Tools & Technologies<\/h2>\n<\/div>