It remembers.
Goals, decisions, knowledge and evidence are kept as a dated record the company owns, in plain files. Every AI session starts from that record, so nobody explains the business to the machine twice.
DuranteOS · Durante Technologies
AI models are becoming a commodity. Your company's context is not.
Every company can now rent the same models. What almost none of them has is a place where its goals, its decisions, its rules and its proof live, in a form any model can work from.
Today that context sits in the wrong places: in each employee's chat history, in an account the model vendor controls, and in people's heads. So AI at work still looks like this:
- 01Every conversation starts from what someone remembered to paste in.
- 02The company's policies are documents nobody attached.
- 03Nothing checks an answer before it is used.
- 04When a person or a tool changes, the company starts again.
01 · The layer
DuranteOS is the layer that ends this.
It sits between the company and the models. The company's context is the first layer: owned, structured and connected. The model is the second layer: called when there is work to do, and swapped when a better or cheaper one appears.
The companyphone · dashboard · terminal
its people, goals, policies and documents
DuranteOS
the contextual layer: what the company knows, decides and allows
- Record
- Rules
- Work
- Proof
The modelsswapped underneath · cost measured per delivery
- Model A
- Model B
- Model C
The tool is the cheap part now. The record is the part you keep.
02 · What it does
Five things it does.
It governs.
A rule is written once and enforced before anything goes out. On a live demo, a draft post touched politics and the rule stopped it on screen. Messages, publications, purchases and deploys wait for a named person's yes.
It proves.
Work states what done means before it starts and closes on evidence: tests, checks in a real browser, and an audit by a second model from a different vendor.
It runs on any model.
Several AI tools from different vendors work the same board under one rulebook, and the cost of each piece of delivered work is measured. When the best model changes, the company keeps everything it knows.
It learns, under control.
Corrections become written rules. A change the system proposes to its own code, rules or settings waits for a person, who accepts or rejects it.
You reach it from a phone, a dashboard or a terminal.
03 · Why not the model directly
A model answers questions. A company needs more.
| Using a model directly | With DuranteOS |
|---|---|
| The context lives in the vendor's account, as a summary the vendor shapes | The context is a record the company owns, as files |
| A policy is whatever each person remembers to type | A policy is enforced before anything leaves |
| Done means someone said so | Done means evidence, reviewed by a second vendor's model |
| One vendor, and a bill nobody can read | Models swapped underneath, cost measured per delivery |
| A person leaves and their conversations leave with them | The work stays in the record, with the reason it was done |
| Leaving the tool means starting over | The whole record exports, checked by an independent reader |
A company needs something that knows what it decided last month, applies its rules without being reminded, and can show why a piece of work was called finished. That is a layer, and DuranteOS is that layer.
04 · What a business gets
The finished thing, with the proof attached.
The finished thing, from one request.
On a live demo, a restaurant's website was built from a single sentence, and the project started with its own record: what was asked, what was built, what is left. The owner says what the business needs; the layer plans the work, does it and shows the proof.
Knowledge that stays when people leave.
What was decided, and why, sits in the company's record instead of one person's chat history. The next person, or the next tool, starts from it.
Rules that hold without supervision.
The company's policies are applied to the AI's work, and anything that goes out waits for a named person's yes.
AI spend the business can steer.
The cost of each delivery is measured. Routine work goes to cheaper models, judgment to the strongest one.
One view of the work.
What was promised, what was delivered and what is blocked, with the evidence attached.
05 · It already runs a company
Durante Technologies runs on DuranteOS.
Engineering, research, sales material, the books. This page was drafted and fact-checked inside it, and each number below was counted from the system's own files.
1,055work records since 25 August 2026 with their goal and their evidence
259pieces of work audited by a second model, each with its verdict on file
68rules in the rulebook, each citing the incident or decision behind it
54jobs on a schedule, run unattended
Counted on 1 October 2026 from the system's own files: run records holding a goal and their evidence; runs whose audit by a second model recorded a verdict; entries of the operating rulebook that cite the incident or decision behind them; active scheduled background services.
06 · See it work
Thirty minutes with Lucas, and the system doing real work in front of you.
By invitation
Lucas Gertel · lucas.gertel@durante.tech