Your operational day-to-day with artificial intelligence
AI does not know how your company works
It is not enough for AI to access your data; it must know what to do with it
Generic AI does not understand your vocabulary, your criteria or your unwritten rules
AI needs your logic, judgment and methodology to really add value
What information do you prioritise?
How do you assess risk?
What procedures do you follow?
What precedents do you apply?
At iAutomator we work with you to build the layer that speaks your firm's language;
we formalise your business logic and embed it into your AI agent, so it responds according to your criteria:
With your policies for pricing, with the right clients prioritised, with the exceptions you would make
The challenge is not showing AI your data; it is showing AI how your company functions
We digitise your context and operational logic for AI
We develop two disciplines that work in parallel so that your AI agent functions as another member of the team
1. Context engineering:
It manages the AI's field of view so that it considers only relevant, up-to-date and reliable information
It tunes infrastructure and data flows to improve the conditions in which the AI operates:
- With the right information
- At the right moment
- With less noise and more signal
2. Playbooks:
Your process guides are translated into the language of AI to enable:
- Standardised execution
- Enforced criteria
- Consistent decisions on which data sources or tools are used
- Minimisation of errors and omissions
Playbooks reduce improvisation so that the AI executes in a consistent, repeatable and auditable way.
AI advisory board:
Strategic questions also arise; for these we can add a multi-model board to your agent, made up of ChatGPT, Claude, Gemini and Grok
Each AI model analyses the matter separately, weighs the others' arguments and contributes to a final synthesis
You get different perspectives, critical reviews and less reliance on a single AI provider