We look closely before we build.

During evaluation we clarify requirements, data situation and responsibilities — and define what your agent should know and be allowed to do. The result is a concrete implementation plan.

We structure what your agent may know — and define what it may do

Your agent's knowledge layers

Soul — the agent's personality & working style

Company wiki — curated, signed company knowledge

Document KB — full-text search across your documents

Vault — secrets, visible to no one

Evaluation checklist

Requirements & goals captured·

Data sources assessed·

Roles & permissions defined·

Cloud or on-premise decided·

Risks classified·

The prototype only starts once everything is clarified.

Simplified view of the knowledge architecture of our platform SNCS Prism.

What happens in this step.

Requirements & processes

We map the process from the AI Check in detail: who does what, which documents flow, where the value is created.

Data & knowledge sources

Which sources may the agent use? Company wiki, file servers, business systems? What is too sensitive and stays out?

Governance framework

Roles, permissions, approval paths and deployment (cloud or on-premise) are defined.

← Step 1: AI Check Step 3: Prototype →

The best entry into evaluation: the AI Check.

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Sparer & Neulinger Consulting & Systems GmbH · Vienna

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