Private AI Document & Knowledge Assistants
Make sensitive knowledge easier to use within defined boundaries.
Build a knowledge assistant within an agreed private deployment and access model.
The opportunity
The problem we help you solve
Your team needs answers from internal documents, but an unrestricted AI tool is not an acceptable place to put the information. The result can be a choice between slow manual search and a tool that lacks the context to help.
Voxd builds document assistants within an agreed private deployment and access model. We connect selected sources, test the retrieval and answers, and keep references available for checking. The deployment boundary and the knowledge experience are designed together so the assistant can be both usable and appropriate to the information.
What changes for your team
Bring approved knowledge within reach
Let authorised staff ask practical questions of the selected information without manually searching every source.
Make the data paths explicit
Assess processing and access across retrieval, model serving and the surrounding application.
Keep evidence attached to answers
Help users check the source and recognise when the available material does not support a confident response.
What we deliver
What Voxd can deliver
Source and access assessment
Review documents, users and the boundaries that the assistant needs to enforce.
Private assistant implementation
Build the agreed retrieval, model and user-access arrangement.
Answer and permission testing
Evaluate representative questions, unsupported requests and access boundaries before wider use.
Why Voxd
Infrastructure connected to the application it serves.
Voxd combines AI integration and custom software capability with infrastructure design. We consider how users will access the service, how it will retrieve information and how the surrounding application will behave when a dependency is unavailable.
We can help compare options before hardware is purchased and stay involved through deployment and operation. The goal is a usable business service with an appropriate hosting model, not a model running in isolation.
How we work
Prove the workload before committing to the infrastructure
- 01
Define the boundaries
We establish the use cases, data requirements, users and operating expectations, including the systems and dependencies around the model.
- 02
Evaluate the options
We test suitable models and deployment approaches against representative tasks, comparing quality, performance and likely total operating cost.
- 03
Build the environment
We configure the infrastructure, access and application connections, then test the complete workflow and its operational controls.
- 04
Prepare to run it
We agree monitoring, maintenance, recovery and ownership, with handover or ongoing management matched to your team’s capacity.
Before you get started
Before you get started
Is this different from a standard knowledge assistant?
The user need is similar, but the hosting and information-processing requirements shape the architecture and model choices. We evaluate those constraints explicitly.
Will a private model understand our documents well enough?
That needs testing on your tasks and material. We compare suitable options and make quality limitations visible before committing to a wider rollout.
Make internal knowledge more accessible without ignoring its boundaries.
Tell us what staff need to find and how that information must be handled.