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Company context for AI: how to build and maintain it

Build company context for AI from confirmed information about your offer, buyers and communication rules. Start with sources, distinguish facts from hypotheses, assign owners and test it on a real task.

Daniel Siwek, Founder of SyncGrowth · Updated:

Found an error in this guide? kontakt@syncgrowth.pl. We correct the text and publish a new review date.

01

Begin with sources

Collect the website, proposals, presentations, product descriptions, customer conversations, project documentation and expert statements. Keep a source and date for each fact, especially numbers, features and outcome claims.

02

Short checklist or maintained resource?

Start with a company description for one task. As sources grow, assign owners to facts, record their origin and set an update routine. If nobody owns this work, implementation support can cover the structure and testing on a real task.

03

Separate facts from interpretation

A fact is an existing feature, signed agreement or completed project. An interpretation is a differentiator, brand character or assessment of audience needs. Both layers matter and should be marked clearly.

04

Describe audiences and the buying process

For each audience, document the problem, trigger, decision participants, objections, selection criteria and trust-building proof. Avoid personas based only on age or job title.

05

Add language and constraints

Context should include preferred words, prohibited phrases, tone, product name rules and examples of strong and weak copy. Record promises the company will not make without evidence.

06

Design the update process

Assign owners for products, projects, customers and communication. A new fact should enter the context as soon as it is confirmed.

07

Test with real tasks

Ask two people or tools to prepare an asset using the same context. If they must guess or ask the same questions, fill the missing areas. Strong context reduces revisions without removing human decision making.

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