Private AI Concierge
The power of a senior AI assistant — running entirely within your own environment. No data leaves your infrastructure. No third-party access. No compromise on confidentiality.
Why private AI matters
Consumer AI tools — ChatGPT, Copilot, Gemini — process your queries on third-party servers. In healthcare, legal, finance, and professional services, that creates real confidentiality and compliance risk. A Private AI Concierge runs on your infrastructure, using your data, with no external data transfer.
What it does
- Answers questions against your own policy and procedure library
- Drafts documents, letters, and reports from your templates
- Summarises long documents and meeting notes
- Provides regulatory and compliance guidance grounded in your specific frameworks
- Assists with research and analysis using only approved sources
Who it's for
Healthcare organisations that handle patient data. Legal and professional services firms with client confidentiality obligations. Financial services firms with regulatory data requirements. Any organisation where the question "where does my data go?" has a non-trivial answer.
How we build it
We deploy a custom AI system using open-source or enterprise models that run on-premise or within your cloud tenancy. We connect it to your document library, configure appropriate access controls, and hand it over fully documented. No ongoing dependency on us or any third-party AI provider.
Common questions
What is Private AI Concierge?
A fully private, self-hosted AI environment deployed on your own infrastructure. No data leaves your environment, no third-party AI provider processes your information, and no usage logs are retained outside your control.
How much does Private AI Concierge cost?
From £10,000 as a fixed fee for the initial build and deployment. Ongoing infrastructure costs are determined by your hosting environment — we do not charge a subscription or per-query fee.
Who is Private AI Concierge for?
Organisations that cannot send data to commercial AI APIs due to governance, clinical data classification, or contractual restrictions — including NHS providers operating under strict DSPT requirements, legal firms with privilege constraints, and financial services organisations with regulatory data restrictions.
What AI models can be run privately?
We deploy open-source models including Llama 3, Mistral, and Qwen, selected based on your performance requirements. These run entirely within your infrastructure — on-premise servers, Azure Private, or AWS VPC — with no external API calls.
Is private AI less capable than cloud AI?
For most enterprise use cases, modern open-source models match or exceed cloud API performance. Where a task genuinely requires frontier model capability, we design a hybrid architecture that keeps sensitive data on-premise while routing only sanitised inputs to external APIs.
Every engagement starts with the Operations Reduction Audit.
No matter what you need from us, the audit comes first. It tells us exactly where you're losing time and money — so we can be certain we're delivering the right solution for your organisation.