CADDi Raises $114M for Manufacturing Decision Memory

CADDi has raised a $114M Series D at a stated $1.2B valuation to expand its AI data platform for manufacturing. The September 15, 2026 financing brought together 8 new and existing investors and gives the Tokyo- and Chicago-based company more capital for product development, North American expansion, and hiring.

The company is trying to make manufacturing knowledge usable after it has been scattered across drawings, CAD files, quality records, supplier histories, ERP systems, spreadsheets, and the memories of experienced employees. CADDi's bet is that AI becomes materially more useful in a factory when it can reason across that context instead of treating every document as an isolated file.

The round arrives as manufacturers are being asked to move faster without relaxing the constraints that make physical production difficult. A model can generate an answer in seconds, but a new part still has to survive design review, sourcing, prototyping, production, quality control, and the consequences of an expensive mistake.

What CADDi's Series D includes

The $114M Series D includes Moore Strategic Ventures, Coreline Ventures, Salesforce Ventures, Woven Capital, and HR Tech Fund. Existing backers Atomico, Globis Capital Partners, and JPS Growth funds also participated. No lead investor, primary-versus-secondary allocation, board change, ownership level, or other deal term was disclosed.

CADDi says the financing brings total equity funding to $234M. That current company figure does not cleanly reconcile with every earlier dollar-denominated financing report, so it should be treated as CADDi's stated total rather than rebuilt through independent arithmetic. The company raised an $89M Series C in 2023 and announced a ¥4B equity extension plus ¥5.1B of long-term debt in March 2025. Fortune described the equity extension as $38M and reported a $470M valuation, making the new $1.2B figure more than twice that earlier level.

The syndicate is also a useful map of CADDi's expansion. Woven Capital brings an automotive connection through Toyota, Salesforce Ventures is backing a manufacturing-specific enterprise data layer, and Coreline Ventures has emphasized the opportunity to connect structured business data with the information buried inside drawings.

From drawing search to manufacturing context

Co-founder and CEO Yushiro Kato and co-founder and CTO Aki Kobashi started CADDi in 2017. The company first built a procurement platform for custom-manufactured parts, an operating model that exposed the team to quoting, supplier selection, quality defects, inspection, and the work required to get physical components delivered correctly.

CADDi later turned that experience into CADDi Drawer, a product designed to search technical drawings and help manufacturers find similar parts, previous purchases, and related quality information. The product is now called CADDi Explorer and sits inside a larger AI data platform for manufacturing.

The platform ingests manufacturing data, structures it, connects records through a semantic layer, and makes the resulting context available to search tools and AI agents. CADDi Agent supports analysis and decision work, while 6 workflow products extend the system into design review, production readiness, cost analysis, quoting, design reuse, and asset lifecycle management.

That expansion changes the product's job. Drawing search helps a user find an existing file. A connected manufacturing data layer has to explain how the drawing relates to suppliers, defects, costs, prior decisions, and the downstream effect of changing a design.

Why the implementation layer matters

CADDi says it uses proprietary AI for manufacturing-specific information such as 2D drawings and 3D CAD, while using general-purpose language models for documents and spreadsheets. The distinction is important because geometry, tolerances, and design relationships do not become safe engineering context merely because a language model can describe them.

The harder problem is organizational. Fortune reported that CADDi has more than 100 customer-success employees and is adding forward-deployed engineers to help manufacturers change real workflows. That level of support is expensive, but it reflects what happens when a customer is asked to place sensitive design, procurement, and quality data inside a new operating layer.

CADDi's security materials state that the platform supports ISO/IEC 27001, SOC 2 Type II, ITAR access controls, GDPR requirements, encryption, MFA, SSO, IP restrictions, daily backups, audit logging, and regular third-party security assessments. Those controls do not complete the trust conversation, but they establish the baseline for customers whose data can affect production, cost, export control, and product safety.

The evidence behind CADDi's expansion

CADDi says sales are more than doubling year over year, its customers operate in 22 countries, and more than half of Japan's 100 largest manufacturers use the platform. Revenue and customer count remain undisclosed, which makes those figures company-reported indicators rather than a complete financial picture.

Salesforce Ventures names Subaru, Kawasaki Heavy Industries, Amerequip, and DCC Automation as customers. CADDi-hosted reporting also identifies Yanmar and YKK. The company presents selected case studies showing 100,000 hours saved for an automotive OEM, more than a 90% reduction in time spent investigating regulated-substance use, and a 30% annual procurement-cost reduction for an industrial-machinery manufacturer. Those outcomes are useful examples, but they have not been independently benchmarked in the sources reviewed here.

The Series D will support more products, manufacturing-specific AI models, hiring, and global growth centered on North America. CADDi currently reports more than 910 employees, up from about 600 in early 2025, giving the company more capacity to sell and implement a platform that touches multiple manufacturing functions.

What this financing signals for industrial AI

Recent industrial-software funding has moved beyond generic copilots toward systems that can act on domain-specific operational data. Rapta's manufacturing-intelligence financing centers quality assurance on the production line, while Magentic's procurement-AI round targets the purchasing decisions surrounding industrial operations. CADDi is pursuing a broader data and workflow layer that spans design, procurement, production, and quality.

That scope creates both opportunity and responsibility. A shared semantic foundation can reduce duplicated work and make prior decisions easier to reuse, but the system has to preserve permissions, context, and the difference between a useful pattern and an unsafe shortcut. CADDi's valuation reflects investor confidence that this layer can become durable infrastructure for manufacturers rather than a collection of isolated tools.

The next evidence will come from repeatable adoption outside CADDi's home market. The company has capital, named global customers, a wider product suite, and a large implementation organization. It still has to show that manufacturers in North America and other regions will change how they handle engineering knowledge, expand usage across departments, and keep enough value inside the platform to justify the operational work.

CADDi is financing a handoff from individual memory to shared manufacturing context. If that handoff works, the value will appear in fewer repeated mistakes, faster design decisions, better sourcing choices, and knowledge that remains usable after the person who carried it leaves the room.