The buyer's case for sovereign AI — the outcomes, the risks it removes, and where it fits. Need the architecture? Switch to the engineering view.
DouJou is the librarian that lives inside your own environment and briefs every AI agent you’ll ever hire — your operational knowledge, your workflows, your systems, your decisions — before any of them say a word to your business. Most AI companies skip this work because they’ve never had to live with the consequences.
Deploy DouJou directly from AWS Marketplace with one-click VPC deployment and integrated billing.
GCP Marketplace deployment option launching Q3 2026. Join the waitlist for early access.
Microsoft Azure Marketplace integration coming Q4 2026 / Q1 2027. Private preview available for enterprise customers.
Regional implementation partner for UAE-based enterprises. Contact for local deployment support.
DouJou deploys inside your own cloud — your account, your keys, your perimeter. AWS live now; GCP Q3 2026; Azure Q4 2026 / Q1 2027. Nothing transits to our servers.
Copilot, Claude, Amazon Q, your custom agents — DouJou feeds them better context. It makes the tools you've bought reliable. It doesn't replace them.
Built on MCP — the emerging standard that lets AI agents from different vendors finally read from the same complete picture of your business.
If two or more of these sound familiar, you don’t have an AI problem. You have an infrastructure problem.
Fewer than 1 in 20 enterprise AI pilots reach production. The failure is almost never the model — it's the infrastructure gap between demo and production.
CRM, ERP, support tickets, shared drives, legacy systems. Your AI is only as good as the context it can reach — and right now it sees a fragment.
A customer-support AI inventing a refund policy, a procurement AI misreading a contract — that's not a tech glitch. It's exposure to customers and regulators.
Marketing bought one tool, HR another, IT is building a third. Five systems, five data arrangements, no shared context — five separate liabilities.
Your legal team won't allow customer data off-premises. That rules out most SaaS AI platforms. It does not rule out DouJou.
The moment your engineers stop building pipes and start building product, the invoice settles itself.
These tools are exceptional — but they cannot know your business: your contracts, your systems, your pricing exceptions, what your team decided three months ago. One person getting a confident wrong answer is a small problem. A hundred people and five agents hallucinating from the same incomplete picture, at scale, is a board-level conversation.
You don’t replace Copilot — you make it reliable. Every query through a DouJou-connected agent is grounded in your complete operational knowledge and comes back with a confidence score. Everything below your threshold is suppressed before it reaches anyone outside your walls.
Context only works when everyone who owns a piece of it contributes. One platform, the right information for the right people.
Your biggest user base — building AI applications on the infrastructure without needing a PhD in ML systems. Finally unblocked from the plumbing.
Your leadership team gets a business view of the same console: financial impact, cost savings, which initiatives are running and how they perform.
Finance, HR, legal, operations annotate their domain — surfacing the institutional knowledge that would otherwise retire with the people who hold it.
Not a vague 'high confidence' — a number (72%, 94%). You set the threshold; anything below it is suppressed before it reaches anyone outside your walls.
Model-agnostic by architecture. Use the best model for each job — premium reasoning where it counts, open source where it doesn't. Pay only what the model costs.
Your VPC, your encryption keys, your access controls. Built as the starting point for regulated industries — financial services, healthcare, government, defence.
DouJou is in private Alpha — open to a small number of organisations with a real AI infrastructure problem, the technical maturity to engage early, and the appetite to shape what gets built next.