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Industry case study / Internal knowledge & productivity

Morgan Stanley

Useful knowledge. Human-reviewed answers.

Based on reporting from OpenAI customer story.

Silver laptop with a knowledge-search interface and source documents

The brief

The challenge.

Advisors need to find relevant internal knowledge and turn client conversations into useful follow-up work.

The work

The approach.

Morgan Stanley developed an internal AI assistant and used expert feedback and evaluations to test its responses. Its Debrief tool uses meeting recordings, with client consent, to prepare notes and draft follow-ups for advisors to review and edit.

Reported outcome

Human review

advisors review and edit AI-generated meeting outputs

The published story describes AI support for knowledge retrieval and meeting administration, with advisors reviewing and editing generated meeting outputs.

Source article (opens in a new tab)

Digitbite perspective

What this means for your project.

A knowledge assistant needs more than a search box. Define approved sources, access permissions, an evaluation set and the decisions that must stay with people.

Your next step

Have a similar challenge?

Share the workflow or customer experience you want to improve. We will discuss the right scope, the evidence to measure and a practical next step.

What happens next?

  1. Review your priorities

    We review the goal, current tools and the problem you want to solve.

  2. Clarify the right fit

    We follow up to discuss requirements, constraints and open questions.

  3. Agree the next step

    Scope, delivery stages and costs are agreed before implementation.

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