Meet the world's first AI supply chain coordination platform.

At PVD Products, we manage a diverse, global supply chain with over 300 active suppliers. We rely on a myriad of Excel macros to pull data out of our ERP into static reports, which makes data mining very manual and tedious. For example, rolling up costed BOMs is done by hand, and determining a component's cost history requires heavy spreadsheet manipulation. This gets further complicated when part numbers change due to form, fit, and function rules, clouding our cost history visibility.

nesen's agents have greatly simplified our access to good, accurate data. Now, I just ask the analyst agent, and it does the digging for me.

Because nesen's agents aren't reliant on indexing data by part number alone, I can extract and compare cost data of similar components based purely on the part function description. Mapping out cost history is super simple via a text-based prompt. I've also been able to define the impact of tariffs just by prompting the analyst, and then have it project out future costs based on shifting tariff policies. Ultimately, manual Excel work has now been replaced by prompting a nesen agent, which provides me with insightful analysis along with an explanation of how it was derived.