Accelerate proposal creation by matchingRfQs with real product data
Transform incoming, unstructured requirements into structured, connected knowledge by linking them directly to product architectures, variants, and historical data. This enables teams to instantly identify reusable components, estimate costs based on actual project history, and make confident, fast decisions while reducing redundancy and variant complexity across offers and product lines.

What can you achieve with this use case?
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Smart Matching to Historical Projects
AI-supported matching compares each incoming requirement set with real engineering data, not just BOMs, to identify reuse potential, functional overlaps, and cost-driving changes. Enables faster, more accurate proposals based on validated history.


Traceability Across Systems and Variants
Links requirements to existing product data, making impact, gaps, and reuse options visible. Supports confident decision-making and prevents overengineering and quality issues downstream.

Smart Effort Estimation and Routing
Uses historical engineering data to estimate cost and effort, and routes requirements to the right expert based on past ownership and domain relevance. Eliminates redundant validations and enables faster collaboration.

Engineering success in action
confidently and unlock innovation with SPREAD.


How to
get started
1
Jointly scope
use cases
We bring practical expertise to understand your challenges and scope the right solutions with you.
2
Deploy solutions
rapidly
Within weeks we deploy our platform, integrate the required product data and configure the defined solutions.
3
Rollout across
the company
We train users across teams, scale company-wide, and support you continuously on the way.