Put AI to work in your company Keep data in your environment
Run documents, the index and model on company hardware Start with real questions and find the right deployment
What does this document say?
An answer, with its sourceCHECK THE ORIGINALIllustrates the local query path; external services and connectivity are assessed separately
Start with your needs Then decide where AI runs
On-premise is not the default for every project When data location and operations matter, plan them explicitly
Specific data-location needs
You want files and queries handled internally, with a defined data scope
An internal use case
Colleagues frequently search catalogues, specifications or operating guides
A plan for ongoing operation
You can assign owners for updates, backups and hardware beyond installation
From files to answers A path you can understand
Select a step to see how information is used This is an illustration and does not upload documents
Start with familiar files
Place files in the agreed environment and confirm formats, sources and search scope
When something connects outside Make the boundary clear
Local querying is one path; external features are a separate choice. Before connecting LINE, a cloud model or another service, define its purpose and what data it receives
Documents, the index and model run in your environment. Installation and update connectivity still need review
Run a trial first Before buying equipment
Start with ten representative documents Use real questions to assess ingestion, answers and usage needs
Bring these to the first discussion
Check what you already have. We can clarify the rest together
Can the files be read?
Check file quality, scans and table processing
Are answers supported?
Review real questions, answers, sources and missing information
Does it fit everyday use?
Assess response speed, concurrent usage and ongoing operations
After delivery Keep it working
Deployment is more than installing a model Agree the responsibilities and scope of everyday operation
Update documents
Define who supplies new information and when it is processed and indexed
Back up and maintain
Agree backups, hardware maintenance and incident ownership
Review answers
Sample common questions and review quality after data or model changes
Questions before deployment
Is this the same as In-house Data Lookup?
In-house Data Lookup defines how colleagues search documents. On-premise deployment defines where documents, the index and model run. It is an optional setup assessed for each project
Do we need new hardware first?
Share your existing hardware first. Trial representative documents and questions before deciding on new equipment. Model size, users and response requirements affect the plan
Does local deployment mean no internet is needed?
The local document, index and model query path can run in your environment. Installation, updates and connections such as LINE or external APIs require a separate network and data-flow review
Who handles updates, backups and maintenance?
Agree the company owner and maintenance scope before delivery, including file updates, backups, re-indexing and answer reviews. Hardware, external channels and service fees are scoped separately
Bring your requirements Let’s plan the setup
Files, usage and existing equipment Assess the fit before implementation and pricing
Optional deployment; hardware, external channels and maintenance are scoped separately