Adding documents may still leave AI unable to use the information a case requires. SYSLABO traces documents, records, business terms and past decisions to define which versions apply. We also decide who can view the information, and who updates it and when. Without waiting for all company data to be ready, we first prepare the information the target work needs and develop the system so AI can be used in that work.
We examine actual questions, retrieved information and logs. We investigate whether information is missing or where the problem lies among reading documents, search and answer generation, separating confirmed findings from points that need further investigation.
We identify the documents, records, contract terms and decision history a workflow needs. We define which versions apply to which cases and periods, then agree where to start.
We define fields that link quotations, business partners and contracts, combining document references with record retrieval. Where terms conflict or information is missing, we build in a way to request human review.
We apply user access permissions to the information AI can reference. We agree who updates and approves information, who makes it available to AI and how changes and deletions are checked.
We test routine and exceptional cases, different permissions and behavior after updates. We identify missing information and unresolved issues, then agree the initial scope and priorities for further work.
We review your existing servers and the cloud services you use, and consider with you where information is processed, what is sent outside and which model to use. What needs checking differs between running a model in house and using a cloud AI service.
The AI model runs on servers or in a cloud environment that you manage. For example, OpenAI's open weight models can be run in an environment you manage. Information can be processed without sending it to an external AI service, and we also check the equipment needed, the processing speed and how it will be operated.
You use an AI service offered by a cloud provider. For example, Claude provided through Amazon Bedrock runs in an environment managed by AWS. We check what information is sent, the region where it is processed, whether and how long it is stored, and whether it is used for training.
How each AI model is offered, and where it can run, differs by model. We check the conditions before proposing a setup, and build it with you, including connections to existing systems and how it is operated.
See how we choose the AI and setupTell us where your current AI is not giving the results you expect, and about the related documents and records. Taking your budget and team into account, we decide with you what to investigate first and the work needed to make them usable by AI.
You can contact us before your questions or documents are fully organized.
