Enterprise AI
Your own AI, inside your own infrastructure.
For corporates, institutions and governments that can’t send data to someone else’s cloud. We install Narrations inside your infrastructure: the editor, your approved rules and the models, under your keys. Nothing goes live without a person’s sign-off.
Your deployment
The same platform, inside your walls.
Everything the platform does, running on your own servers or cloud. Your writers use the editor as normal; your IT team sets who can reach what, and every action is logged where you can see it.
For your writers. The same editor, rules and review flow. Drafts are checked against what the company has approved before anyone sees them.
For IT. It runs where you say, under your keys. You set permissions per connection, cap usage by team, and export the log to your own systems.
For compliance. Nothing goes live until a person signs it off, and every draft, edit, approval and agent action is kept in a searchable record.
LiveNarrations / Content
Content editor
Drafts checked against your rules and approved before they ship.
| Draft | Format | Channel | Status |
|---|---|---|---|
| QRQ3 results announcement | Statement | Website | Checking |
| STService terms update | Notice | In review | |
| OGOnboarding guide | Long-form | Intranet | Approved |
In every deployment
Built for institutions and governments.
Six controls that answer the questions your security team asks first: where the data lives, who can reach it, what runs without sign-off, and what gets logged.
Private deployment
Runs on your own servers or cloud, under your own encryption keys. Your data never leaves and never trains a model.
Approval gates
Every action waits for a person's sign-off before it touches a live system. The check comes first; the log records it after.
Permissions per connection
People and agents reach only the sources, tools and rules they need. You set it per connection, not once for the whole platform.
Rules checked at draft time
Your approved rules, including what you decided not to say, are checked as each draft is written, on every part and model.
Audit trail
Every draft, edit, approval and agent action is logged. Search it, export it to your systems, keep it as long as auditors need.
Usage you can see and cap
See adoption, spend and output by team in real time. Set a limit per team before costs climb, and raise it for what works.
Private deployment
Human oversight
Nothing reaches your live systems without approval.
Every change is drafted and tested away from your live systems first. A person, at first an operator, then your own team, checks it before it runs, not after. The approval is recorded, so you can show who signed off.
Operator tests
Version B
Test result
Version A
Test result
How it's delivered
Built with you, then handed over.
An operator runs the deployment from the first rule to the handover. By the end, your team owns the rules and the record and runs it without us.
- 01
Seed
The operator sits with your team and writes down what you've already decided: positioning, claims, terms, pricing. Nothing starts empty.
- 02
Review
Risky drafts go past the operator before they ship. Each approval or correction becomes a rule, so the checks sharpen as the work goes on.
- 03
Train
Your people learn to run each part, set permissions and read the log. The operator reviews less each week as your team takes over.
- 04
Hand over
Your team runs the deployment and owns every rule and its history. Keep an operator on retainer or don't; either way, it's yours.
Let’s scope your deployment.
Tell us where your data has to live, who needs access and what must never go out unsigned, and we’ll scope a deployment inside your own infrastructure.