Read, translate and transcribe
Turn documents, languages, images and audio into material you can work with.
Start with one bounded workflow.
Private AI adoption works best when the job, data boundary and success evidence are clear. Choose the work first; the product follows.
Ask, explore and reason
Choose fast focused chat, a complete workspace, or a dedicated reasoning flow.
Write, speak and make images
Move from a draft or prompt to usable words, speech and visuals on your own device.
Serve private AI to a team
Host models centrally and add the identity, policy and audit controls IT needs.
For organisations
Keep the workflow. Change the operating boundary.
Move from a local proof of value to centrally hosted models without asking teams to relearn familiar OpenAI-compatible tools.
See the organisation path- 1Prove one job
Pick a bounded workflow and evidence that matters.
- 2Host the model
Run AI Server inside your chosen infrastructure.
- 3Add control
Introduce identity, policy, entitlement and audit as demand grows.
Common starting points
Match the boundary to the work.
Answers with a route back to evidence
Use AI PDF Reader for individual work, or AI Server embeddings and chat APIs for a controlled shared workflow.
Translate without a default upload
Use local translation for everyday material and make any optional cloud route an explicit user choice.
Speech-to-text inside the boundary
Transcribe on a workstation with AI Dictation or provide central speech APIs through AI Server.