Customer Discovery

Help shape the future of trustworthy manufacturing AI.

We are speaking with manufacturing and technology professionals to understand how engineering teams investigate problems, combine evidence, and make operational decisions.

Who we want to learn from

People closest to manufacturing decisions.

We are especially interested in quality, process, equipment, operations, industrial AI, analytics, MES/factory software, semiconductor, and electronics professionals.

QualityProcess engineeringEquipment engineering OperationsIndustrial AIMES / factory software SemiconductorElectronics manufacturing
Time
Typically 20–30 minutes
Format
Informal customer-discovery conversation
Confidentiality
No confidential information is required
Focus
Experience, workflow, evidence, and decision-making
What we are trying to understand

Real workflow. Real friction. Real trust requirements.

01

Investigation workflows

How are manufacturing problems investigated today, and where does the critical evidence reside?

02

Decision friction

What makes quality, process, and equipment decisions slow, uncertain, or difficult to reproduce?

03

Trust in AI

Where is AI already helping, and what makes engineers trust—or reject—AI-supported recommendations?

This is customer discovery—not a sales pitch.

Abakai’s current customer-discovery work is being conducted in connection with NSF I-Corps. The objective is to learn from practitioners before defining solutions too narrowly.