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Concept for - Embedded AI Agents in CLM Repository.

Amit Jain, a procurement head at a global telecom firm, logs into the CLM platform to prep for an upcoming quarterly business review.
As he lands on the contract listing page, he activates the AI embedded near TCV column.

Design Details 

Agents are embedded in user's workflows .
it gain user context and help achieve user intended goal efficiently. This makes AI assistance discoverable everywhere, and ensures each interaction feels natural and on‑point.
Chain together multiple context 
for achieving pin pointed context.
Contextual AI initiation.
This create a cohesive experience. Agents are available wherever users needs it to help them in decision making. Largely enhancing overall experience with Application. User research on workflows & deeper understanding of user behaviour will help to take this as much closer to users & increasing impact.
The suggestions are tailored from where user initiates it.
AI Agents are aware of user context so,
Agent's output feels smarter & personalised.

Design detail for embedded AI agents .

AI Agents Performance Evaluation

Design for large Data  -  Human Efficiency - AI and Human 

Image by Sebastian Svenson
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