Request intakeApprovalPlanningCore workReviewBilling and handoverAI agentAutomatedAccountable ownerA competitor, redesigned around AIDelivered
Requests / week
130
coming in
Delivered / week
105
the rest waits
Lead time, days
7.8
start to finish
Illustrative example · 12 simulated weeks
Delivered / week
98
before AI 105
Lead time, days
10
before AI 7.8
Cost / request
$427
before AI $398
Illustrative example · an AI agent on request intake, nothing else changed
Lead time, start to finish7.8 working days1.1 being worked on6.7 waitingIllustrative example · 12 simulated weeks at 130 requests a week
Delivered / week
123–132
today 105
Lead time, days
0.8–1.0
today 7.8
Cost / request
$326–350
today $398
Illustrative example · 5th to 95th percentile of 12-week runs
Delivered / week
127
was 105
Lead time, days
0.9
was 7.8
Cost / request
$337
was $398
Illustrative example · same people, redesigned work
Twinorg in plain terms
What is Twinorg?
Twinorg is software for redesigning an organization around AI. It builds an organization twin: a working model of what the organization delivers, the steps that produce it, who or what does each step, and what it costs. Leaders change the twin, simulate the effect, and decide with evidence before anything changes in the real organization.
What is an organization twin?
An organization twin is a digital twin of an organization, built around its work instead of its org chart. It holds the outcomes the organization produces, the value streams that produce them, the activities in each stream, the people, agents and automations that perform them, the human position accountable for each one, and the cost of it all. Every number is marked as observed, estimated or assumed.
Why not just add AI to the organization we already have?
AI takes over tasks, not whole jobs. Speeding up one step often moves the queue to the next person who has to review or approve the work, so output barely changes. The gain comes from redesigning the flow of work around what AI can do, and that is a design question an org chart cannot express.
What can we test in a simulation?
Moving an activity to an assisted, agent or automated mode. Removing or narrowing an approval. Reassigning work, merging teams or removing a layer. Adding or removing capacity. Changes in demand or cost. Twinorg reports the effect on lead time, capacity, cost and risk as ranges, with the assumptions each result depends on. There is no single score.
Does Twinorg replace people or make the decision for us?
No. Twinorg informs decisions and records them; people make them. A named human position stays accountable for every outcome, including work done by agents. Hours released by AI are reported as capacity, not as savings, until someone decides what to do with them. Twinorg models roles and teams and does not monitor individuals.
Who is Twinorg for?
Owners and operations leaders who decide how the organization is shaped, and the people who do the modelling with them: transformation and organization design leads, heads of function, and finance.
Is Twinorg only for one industry?
No. An organization twin is built from your own outcomes, steps and roles, so it is not tied to an industry. The example on this page uses general step names: request intake, approval, planning, core work, review, then billing and handover. A visitor can switch them to the names used in their own industry (manufacturing; professional services; software and IT; healthcare; banking and lending; insurance; public sector). Only the names change; the model underneath is the same.
How do we start?
With one value stream and one decision, not a model of the whole company. Leave a work email and the Twinorg team will set up an isolated organization for you. From there you map the steps of one stream, publish a baseline, and test your first change.
Where do the numbers on this page come from?
They are an illustrative example, not a customer result. The scene plays a small model of one six-step value stream, from a request coming in to the result being delivered, simulated for 12 weeks at 130 requests a week. In the old shape it delivers 103 to 108 requests a week, with a lead time of 6.0 to 9.2 working days and $387 to 407 of labour and tools per request. In the redesigned shape, with the same people, it delivers 123 to 132 requests a week, with a lead time of 0.8 to 1.0 working days and $326 to 350 per request. The core work stays with people. Request intake moves to an AI agent whose output a person reviews, approval applies only above a threshold, billing and handover is automated, and the people released from paperwork move to the core work. Choosing an industry on the page renames the steps and the unit of work. It does not change the model or these numbers.