Otto · Operational discovery

Understand real work before building AI.

Otto is the AI interface employees use to describe their processes, tools, constraints and expectations. The objective is to identify assistants that will genuinely help teams in their daily work.

The challenge

AI assistants fail when they are designed away from users. Otto starts with real work.

Teams do not adopt an AI solution sustainably simply because it performs well technically. They adopt it when it addresses real needs, respects their constraints and improves how they work.

Otto captures these needs across the employees involved, then turns them into clear, prioritized and actionable assistant proposals.

How it works

Otto listens, structures and proposes. With employees.

Discovery is not an isolated stage. It is the starting point for continuous development and adoption.

01

We define the process

Together with management, we define the scope, objectives, stakeholders and success criteria.

02

Employees speak with Otto

Otto asks relevant questions to understand tasks, tools, documents, pain points and acceptable automation limits.

03

Needs are structured

Conversations become actionable information: process steps, dependencies, AI opportunities, adoption risks and success conditions.

04

Useful assistants are proposed

Agentscium formalizes relevant AI solutions while keeping end users central to decisions and further development.

What makes the difference

Why Otto is more than a questionnaire.

Top-down approach
Otto approach
Starting point
A solution chosen before understanding usage
Employees’ real work
Dialogue
A few isolated workshops
Conversations adapted to each role and constraint
Objective
Identify generic automation
Build useful, accepted AI assistants
Adoption
Addressed after deployment
Integrated from the moment needs are understood
What you receive

A clear foundation for development. With users.

A structured understanding of the process

Roles, tasks, tools, documents, decisions, pain points and the expectations of the teams involved.

Prioritized AI use cases

Assistant proposals assessed according to practical value, feasibility and user acceptance.

A defined operational solution

For each assistant: expected capabilities, outputs, useful data, usage rules and process integration.

A starting point for Otto

Employee conversations and feedback inform development, user support and progressive improvement.

Once needs are understood, Agentscium builds with users.

Explore business AI assistants →
First use cases

Explore how Otto can speak with your teams.

During this 30-minute call, we will review your processes, priorities and the first use cases that could be relevant to your teams.

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