ExhibitManager / Causasoft
AI-assisted research across extensive collections of legal documents reduces manual search effort and improves access to relevant information.
Practical AI solutions that create value
When AI needs to create real business value in everyday work.
Many companies are investing considerable attention in AI. Yet there is often a significant gap between an interesting proof of concept and a solution ready for productive use.
The key question goes beyond: Where can we use AI?
It is: Where does AI pay off, and how do we put it into production safely, reliably and economically?
BitStone develops AI solutions with a clear business case and integrates them into existing processes, data sources and applications.
Typical starting points
When does an AI solution make sense?
AI is worth exploring when:
- employees spend a lot of time researching, searching or analysing documents,
- large volumes of unstructured information need to be processed,
- knowledge is spread across many systems, documents or data sources,
- recurring tasks can be partially automated,
- existing software needs to be extended with intelligent features,
- better preparation of information can support decisions,
- initial AI experiments exist, but the path to production is unclear,
- concrete AI ideas need to be evaluated for value and feasibility first.
Typical questions from our customers
- Which AI use cases actually create measurable value?
- Which processes are suitable for AI?
- What can usefully be automated, and what should deliberately remain with people?
- What data do we need?
- Can we use existing documents, knowledge bases and systems?
- How reliable do AI results need to be?
- How do we ensure traceability and control?
- How do we integrate AI into existing applications and processes?
- How do we protect confidential business data?
- How do we move from an experiment to a production solution?
What we deliver
Typical AI projects
We develop and integrate solutions including:
- AI assistants
- knowledge-based search and research solutions
- RAG applications
- document analysis and information extraction
- intelligent question-and-answer systems
- AI-assisted process automation
- AI agents
- intelligent product search
- sales and service assistants
- AI features within existing software products
- classification, summarisation and structured preparation of information
We focus on integrating AI into real business processes, beyond standalone experiments.
How we work
Understand the use case. Assess the value. Build the solution. Put it into production.
Understand
We analyse the business process, users, available data and the specific problem.
Evaluate
We assess business value, feasibility, data quality, risks and suitable AI approaches.
Not every technically possible use case is economically worthwhile.
Prototype
Where necessary, we test critical assumptions with a clearly scoped proof of concept or prototype.
Develop and integrate
We develop the production solution and connect it to existing applications, documents, data sources and workflows.
Operate and optimise
AI solutions need to be monitored, evaluated and continuously improved. If required, we also take responsibility for operations and ongoing optimisation.
What makes a good AI solution
Intelligence that serves a useful purpose.
A good AI solution:
- solves a clearly defined business problem
- creates measurable value
- makes effective use of existing data
- is integrated into existing processes
- produces traceable results
- considers data protection and information security
- clearly defines where human control remains necessary
- can be monitored in production
- can be improved and extended over the long term
AI must prove its worth in everyday work.
Customer value
Less manual work. Better access to knowledge. Faster decisions.
Depending on the use case, AI solutions can:
- reduce research effort
- make large volumes of information accessible faster
- automate recurring tasks
- make knowledge centrally available
- improve the quality and consistency of responses
- support employees with complex tasks
- reduce processing times
- substantially enhance existing software
The goal is a measurably better business process.
Technologies and expertise
Depending on the use case, we use technologies and practices including:
- Generative AI
- Large language models
- RAG
- AI agents
- Vector search
- Natural language processing
- Document processing
- Knowledge bases
- APIs
- Cloud AI services
- Human in the loop
- Audit trails
- Security & access control
Technology choices follow the use case, data and requirements for security and reliability.
Relevant success stories
View success story
Hôpital Riviera-Chablais / TumorBoard
Related experience with specialist platforms
Structured digital support for complex medical decision-making processes with demanding requirements for traceability, data protection and security.
Digital Dental Life / Dental Campus
Related experience with specialist platforms
Digital platforms and data-driven applications for sharing and using specialist knowledge internationally.
When is BitStone the right partner?
BitStone is a good fit when:
- the business use case matters more than AI hype,
- AI needs to be integrated into existing processes or software,
- sensitive or business-critical data is being processed,
- a proof of concept needs to become a production solution,
- traceability and human control matter,
- you need a partner with expertise in both AI and software engineering.
Do you have a specific AI use case?
Or are you still exploring where AI can create real value in your company?
Let’s discuss the realistic potential and a sensible next step.
