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Fort Wayne manufacturers describe AI pilots that cut engineering work and sharpen forecasting
Summary
Two Indiana manufacturers described concrete AI applications: Jasper Group used a university partnership to extract part data from JPEG drawings at roughly 90% accuracy, saving about five months of manual work; Heineman Industrial Products said AI is improving inventory forecasting through mapped workflows and Main Street programs.
Two Indiana manufacturers described practical AI deployments at a Fort Wayne event, offering examples of how local businesses are applying machine learning to factory and supply-chain problems.
Chad Harter, identified in the transcript as CIO of Jasper Group, described partnering with Indiana University students through the Analytics IN program to train AI to read thousands of JPEG engineering drawings and extract part information. According to Harter, the system reaches "about 90% accuracy" on tens of thousands of documents and "saves a lot of time" — he said the automation replaced roughly five months of monotonous manual work, freeing engineers to focus on higher-value tasks.
Joe Heineman, owner of Heineman Industrial Products and resistancewire.com, urged smaller manufacturers to map workflows first and apply AI to where decisions are actually made. He described two primary use cases his company is pursuing: market research/business intelligence to evaluate acquisition targets, and inventory management to improve forecasting and purchasing. He credited support from the gBETA Main Street Next program, Generator and local advisors for helping move from experimentation to operational use, and said the result so far has been "faster decisions, better throughput, and the confidence to keep hiring and keep investing in our Indiana business."
Both speakers used the event to encourage other Hoosier manufacturers to explore partnerships with higher education and local accelerator programs rather than pursue off-the-shelf tools without mapping their processes. The examples cited in Fort Wayne illustrate how industry-academic partnerships and small-business networks can translate AI into measurable operational gains.
