Hyperion and CADDi Target a Hidden Manufacturing Bottleneck: The Cost of Slow Quotations

Hyperion Materials & Technologies is working with CADDi to centralise engineering data and accelerate quotation workflows, beginning with its Barcelona engineering team

In highly competitive manufacturing markets, winning a customer can sometimes depend on a deceptively simple question: how quickly can a company provide an accurate quotation? For businesses producing highly engineered components, the answer is rarely straightforward. Engineers may need to examine technical drawings, assess manufacturing feasibility, search historical pricing and consult information spread across multiple systems. The process can consume valuable time before a commercial decision can even be made.

Hyperion Materials & Technologies and CADDi are attempting to address that bottleneck through a new technology collaboration focused on engineering data and quotation workflows.

Hyperion, a global provider of advanced materials and precision tooling solutions, has partnered with CADDi, which develops an AI-powered data platform designed specifically for manufacturing. The initial deployment with Hyperion’s engineering team in Barcelona is intended to establish a foundation for broader use across the company’s global operations.

Hyperion serves industries including automotive, aerospace, mining, energy and industrial manufacturing. Its products include hard and super-hard materials such as tungsten carbide and diamond-based solutions used in demanding applications. (Business Wire)

In such environments, engineering information is a strategic asset. Historical drawings, specifications, pricing information and manufacturing knowledge can help companies determine whether they can produce a component, how much it might cost and how competitively they can quote.

The problem is that this information often becomes fragmented.

CADDi’s platform is designed to address that fragmentation by making engineering data searchable and easier to access. Hyperion introduced CADDi Drawer to its Barcelona team, creating a centralised environment for engineering information that had previously been distributed across manual data silos.

The commercial implications are significant. A faster quotation process can allow a manufacturer to respond to more requests while improving the likelihood of winning work. In sectors where customers may be comparing several suppliers, even a modest reduction in response time can influence purchasing decisions.

Hyperion CIO Steve Peale said faster quotation response times can directly improve win rates and that the company expected CADDi Drawer to help align its engineering-to-manufacturing process while allowing new parts to be quoted more quickly. Early usage results indicate that the system is delivering on that objective.

The collaboration illustrates a broader shift in industrial technology. Manufacturers have accumulated enormous volumes of digital engineering information over decades, but simply storing data does not necessarily make it useful.

The value emerges when engineers can retrieve relevant information at the moment they need it.

That is where AI-enabled search and data structuring can make a difference. Instead of forcing engineers to remember where a drawing was stored or manually search through historical records, intelligent systems can help connect information across projects and documents.

For a company such as Hyperion, that could eventually support more than quotations. A unified engineering data platform could potentially assist with product development, manufacturing planning, procurement and customer service.

The Barcelona deployment is therefore being treated as a blueprint rather than an isolated technology project. The objective is to establish a model that can be expanded across additional use cases and manufacturing locations.

This approach also reflects a growing recognition that industrial AI does not always need to involve autonomous machines or dramatic factory-floor automation. Some of the most immediate value can come from improving the flow of information that supports human decision-making.

In manufacturing, that information flow can have a direct commercial impact. If an engineer can identify a comparable component, review historical pricing and assess feasibility faster, the sales team can respond to customers sooner. Faster responses can improve competitiveness without requiring major changes to physical production infrastructure.

The partnership also highlights the importance of domain-specific AI. Manufacturing data is highly technical and often structured differently from information used in general business applications. Platforms built specifically for engineering and manufacturing workflows may therefore have an advantage when companies attempt to extract value from complex technical archives.

For Hyperion, the immediate objective is straightforward: reduce the time required to quote custom components while improving decision velocity.

The longer-term opportunity could be considerably broader.

As industrial companies look to modernise operations, the ability to convert historical engineering knowledge into an accessible digital asset may become a competitive advantage in its own right.

In an industry where speed can influence whether an order is won or lost, making engineering knowledge easier to find could ultimately be as valuable as adding another production line.

More information is available through Hyperion Materials & Technologies and CADDi.