01
Private deployment
Run in your AWS, Azure or GCP account, or on-premise.
AI across your company, on your terms.
We help larger organisations roll out AI safely, with a shared platform that has access control, audit trails and approved models, deployed in your own cloud.
Planning
Goal
Output
Working…
- Runs in your cloud
- SSO and roles
- Full audit trail
How the platform works
One governed entry point for AI.
- 01
Deploy
Runs in your AWS, Azure or GCP account, or on-premise.
- 02
Connect
Plugs into your single sign-on and data sources.
- 03
Govern
Roles, permissions and policies decide who can do what.
- 04
Route
One gateway sends each request to an approved model.
- 05
Audit
Every request and response is logged for review.
What we build
The controls larger organisations need
02
Access & permissions
SSO, roles and data-level permissions.
03
Model gateway
One governed entry point for every approved model.
04
Audit & compliance
Full logging of prompts, responses and actions.
05
Data connectors
Secure links to ERPs, CRMs, data warehouses and file stores.
06
Adoption & training
Workshops and playbooks so teams actually use it.
Use cases
Where teams use it first
Financial services
Analyst workspace
Research, summarise and draft reports inside a compliant environment.
Manufacturing
Operations copilot
Answers from manuals, maintenance logs and sensor data on the shop floor.
Enterprise IT
Internal AI gateway
One approved platform instead of dozens of unmanaged AI tools.
Platform vs. the alternatives
Why not let each team pick its own tool?
| Capability | Public AI tools | Each team builds its own | Enterprise platform |
|---|---|---|---|
| Data stays in your cloud | No | Varies | Yes |
| Single sign-on and roles | Limited | Varies | Yes |
| Approved models only | No | No | Yes |
| Central audit log | No | No | Yes |
| Cost tracked per team | No | No | Yes |
Platforms we've shipped
Running in production today
Process
From first call to production
01
Scope
A short workshop to pick the use case, define what success looks like and check your data.
02
Prototype
A working demo on your real data within weeks, so you can see it before you commit.
03
Build & integrate
A production build connected to your tools, with guardrails, tests and monitoring.
04
Launch & improve
We go live, track quality and cost, and keep tuning as usage grows.
Built withAWSAzureKubernetesDockerOpenAIPostgres
Questions