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ProcureBase is a shared workspace where engineers, buyers, and vendors manage the entire RFQ process for custom manufactured parts — from file upload through PO handoff. It replaces the email threads, forwarded attachments, and scattered spreadsheets that most hardware teams still use to coordinate quoting, DFM feedback, and vendor decisions. AI handles the parts that slow teams down most: reading drawings, identifying manufacturing processes, flagging DFM issues, and normalizing quotes for comparison. One place, one thread, full context — nothing buried in someone's inbox.

ProcureBase helps buyers move faster by turning engineering packages (CAD/drawings/notes) into a structured sourcing request, and using AI to route it to the right manufacturer—so procurement isn’t manually translating drawings into “who should quote this.” It also normalizes quotes and flags outliers (price, lead time, assumptions), cutting the back-and-forth that drags cycles

Cleaner RFQs, fewer ambiguous requirements, fewer redundant clarifications, and faster decisions resulting in higher cost savings. Shops can also demonstrate expertise through DFM suggestions that are visible to the real decision-makers—not buried in forwarded chains.

ProcureBase is based in Boston, MA and is built by a team of hardware and software engineers with experience at Amazon Robotics, Oracle, and LexisNexis. We're building the system we wished existed, because we've lived the workflow pain firsthand.

Modern multi-model architectures - combining computer vision, spatial reasoning, and domain-specific language models — can analyze the unstructured files manufacturing teams actually work with: CAD models, drawings and spec sheets.

The email-and-spreadsheet workflow was always inefficient, but it functioned when you had a handful of vendors and simple parts. Today's teams manage more vendors, tighter tolerances, faster revision cycles, and growing compliance requirements — all through the same inbox. The process didn't scale, and the cost of lost context (buried DFM feedback, tribal knowledge walking out the door, RFQs sent to the wrong shop) is now measurable in real dollars and missed deadlines.

AI is proving productivity gains, not just generating hype. The shift isn't that companies are adopting AI — it's that the ones applying it to structured workflows are seeing concrete results: shorter cycle times, fewer revision loops, less manual data entry. Manufacturing procurement is one of the last major enterprise workflows still running on email, which makes it one of the highest-ROI places to apply these tools.