Fabric
Understand work. Augment people. Measure productivity. Learn continuously.
Know → Execute → Measure → Learn: the loop runs for every role, not for a generic user.
See FabricAI Strategy · People
What AI would you putin the hands ofevery employee?
Don't give everyone the same AI. Give everyone an AI that knows their work.
01 The question
- ChatGPT?
- A copilot?
- Agents?
- Your own AI?
Each one is a tool. None of them, alone, answers the question.
02 The problem
A generic AI knows language.It doesn't necessarily know the work.
What it is missing is everything that makes a job a job:
- Role
- Activities
- Rules
- Knowledge
- Process
- Authority
03 The shift
Generic AI → Work intelligence
The value isn't in the model everyone already has. It's in the context only your company has.
04 The framework
Start from the work,not from the tool.
Each role breaks down into activities; each activity into the skills, rules and knowledge it needs to run.
- Role
- Activities
- Skills
- Rules
- Knowledge
- Execution
05 How Onni puts this into production
Fabric puts thisframework to work.
Every person gets an AI that knows their role, executes what it can, measures the gain against the baseline and learns from real use.
- Know
- Execute
- Measure
- Learn
06 Human + AI
Not human or AI.Human + AI.
AI
AI executes where it can.
Reading, drafting, checking, searching, filling in: the repeatable part of the activity.
Person
People decide where judgment matters.
Approvals, exceptions, relationships and accountability stay with whoever answers for them.
07 Measurement
Measure fromday zero.
Without a baseline, productivity is an opinion.
- Baseline
- Execution
- Time
- Quality
- Adoption
- Value
Your AI isn't your LLM.
- It's your knowledge.
- Your processes.
- Your rules.
- Your data.
- Your capabilities.
- Your agents.
- Your decisions.
- Your architecture.
- It's your enterprise intelligence.
· Your AI
Discover how AI can understandhow your organization works.
Go deeper
Questions, industries and articles that build on this decision.