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National Instruments Leadership Forum

AI Event Co-host System

A live AI voice assistant built in four days to co-host an enterprise leadership forum with scripted segments, listening mode, waveform monitoring, and guarded responses.

84% line accuracy during the live flow and 94% attendee usefulness rating.

Challenge

The problem that had to be made measurable.

The event needed an AI co-host that could stay on script, respond to cues, and feel polished in front of an enterprise audience without creating live hallucination risk.

Build window

4 days

Live line accuracy

84%

Attendee usefulness

94%

Primary risk controlled

Off-script responses

Approach

1

Built a controlled script-and-cue interface instead of a free-form chatbot.

2

Added listening mode, waveform monitoring, and guarded response states so the operator could see when the system was active.

3

Prepared scripted fallback responses for predictable event transitions and sponsor moments.

4

Kept the live system narrow: co-hosting and Q&A support, not open-ended enterprise advice.

Project timeline

1

Scope and script

2

Voice/response prototype

3

Operator interface

4

Live rehearsal

5

Event run

Case study packet

Downloadable evidence brief.

Generated packet for sales follow-up, client review, and future replacement with approved screenshots, raw artifacts, and final metrics.

Evidence cards

4

Risk items

4

Canonical page

/case-studies/ai-event-cohost

Manifest

/reports/case-study-packets/manifest.json

Risk register

Audio routing failure
Hallucinated sponsor detail
Latency during handoff
Operator overload

Consulting pattern

Prototype quickly, then turn the demo into an evaluation surface.

The reusable Edxperimental pattern is to make the workflow measurable: inputs, expected output, acceptable failure, operational risk, and a repeatable benchmark before production expansion.

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