PartSpace is an AI-powered procurement platform that analyzes technical drawings and 3D models. It extracts key details like materials, tolerances, and processes, links them with ERP and purchasing data, and delivers actionable insights for cost savings and supplier optimization.

Procurement managers, cost engineers, supply chain leaders, design engineers, and C-level executives benefit from faster decisions, reduced costs, and stronger supplier strategies.

PartSpace is used by manufacturing-driven industries such as aerospace, automotive, machinery, electronics, robotics, and medical technology.

Unlike generic e-procurement systems, PartSpace understands technical drawings and connects them directly to procurement and cost data, making decisions based on facts rather than assumptions.

Both. Mid-sized companies benefit from quick cost savings, while large enterprises use PartSpace for supplier benchmarking, cost engineering, and global sourcing strategies.

PartSpace, PartSpace’s AI, is trained on real drawing and procurement data, not synthetic data. It interprets technical details like an expert cost engineer.

It supports them. PartSpace provides data-driven insights so procurement professionals can negotiate better, save time, and make strategic decisions.

Key sectors include aerospace , automotive, machinery, electronics , robotics, and medical technology.

Most clients see a return on investment within 2 months due to immediate procurement savings.

Savings of more than 10% on drawing-based components are common, with some cases reaching up to 21%.

It benchmarks part data against historical purchasing, supplier databases, market references and technical features to generate fact-based target prices.

Yes. It reduces waiting hours, streamlines supplier selection, and automates analysis, saving both labor and operational costs.

Yes. Automated analysis and supplier matching speed up RFQs and cut waiting time in procurement cycles.

It detects duplicates, identifies opportunities for volume bundling, and suggests supplier consolidation strategies.

Yes. AI-powered clustering identifies variants and duplicates, helping reduce complexity and costs.

Yes. It breaks down costs by material, processing, and volume, giving clear should-cost transparency.

Yes. It provides supplier-specific and market-wide benchmarks to reveal cost drivers and negotiation opportunities.

It transforms procurement into a data-driven strategic advantage that reduces risk, optimizes supply chains, and ensures competitiveness.

PartSpace is the AI core of PartSpace, trained to understand technical drawings and supplier data like a cost engineer, but at scale.

It automatically extracts materials, dimensions, tolerances, and processes to calculate costs and suggest alternatives.

Technical drawings (2D/3D), purchasing history, supplier lists.

Yes. The AI structures and enriches messy data, improving overall quality.

Yes. It connects with existing systems to sync purchasing and product data.

No. Drawings can be uploaded directly and analyzed without special CAD plugins.

Yes. It was built for enterprise-scale datasets with thousands of components.

Yes. Each company gets a custom-trained AI model based on their own data.

The more data it analyzes, the better its predictions, clustering, and supplier matching become.

It identifies suppliers by comparing part similarities and production capabilities, improving accuracy with each dataset.

It compares supplier prices, lead times, and capabilities against peers to highlight savings, based on their technical features, not just meta data.

Yes. AI-driven matching suggests suitable alternatives, reducing risk.

Yes. It provides insights into price trends, capacity, and cost competitiveness.

By mapping similar suppliers globally and offering diversification strategies.

Yes. With data-backed target prices and benchmarks, procurement has stronger leverage.

Yes. It flags cost anomalies and dependency risks based on data.

Yes. It identifies overlaps and suggests bundling to reduce complexity.

Yes. It analyzes costs by material, volume, and processing.

By comparing both internal and external data to create transparent benchmarks.

Yes. Transparent costing builds trust and efficiency in buyer-supplier collaboration.

Typically a few weeks, without disrupting ongoing operations.

No. Minimal IT effort is needed — even a PoC can run without IT.

Yes. A PoC with ~500 parts can prove measurable savings within weeks.

Your team uploads part data, PartSpace trains PartSpace, and results are delivered via dashboards.

No. It’s designed to be intuitive for procurement professionals.

It’s a modern, intuitive UI optimized for procurement workflows.

By showing quick, measurable ROI and providing easy-to-use features.

Yes. Both teams can view insights and align on cost and supplier choices.

Yes. It is cloud-based, supporting multi-location collaboration.

Yes. Real-time dashboards visualize costs, suppliers, and savings.

PartSpace uses enterprise-grade encryption and security standards.

Yes, it fully complies with European data privacy laws.

In secure data centers located in Germany.

Yes. Each client has a separate, custom-trained model.

Yes, it is ISO 27001 and ISO 9001 certified.

Regularly, including by external audits and global enterprise clients.

It automates should-costing and cost driver analysis, freeing engineers from manual work.

Yes. By comparing in-house vs. external supplier costs.

Engineers can upload early designs and receive cost estimates instantly.

Yes. It detects redundant variants and helps reduce part complexity.

Yes. Duplicate detection is one of its strongest features.

By analyzing complex parts with strict tolerances, it helps cut supplier costs while meeting standards.

Yes. Faster supplier identification and pricing shorten development cycles.

Yes. Engineers can test design alternatives early for cost impact.

Yes. It evaluates materials and processes for greener alternatives.

Yes. It maps suppliers worldwide and benchmarks regional costs.

Flexible and transparent — tailored to company size, dataset, and needs.

Subscription-based, ensuring continuous updates and AI improvements.

Yes, larger datasets and more users affect the license cost.

Yes, many companies start with a PoC to validate ROI.

Often within weeks, thanks to fast onboarding.

2D Model (two-dimensional model) is a representation of an object that only has two dimensions, length and width, but no depth (height). In mechanical engineering, this is used in applications such as design and manufacturing, for example in the creation of technical drawings for parts or in the mechanical processing of contours.

3D Model (three-dimensional model) is a representation of an object in all three spatial dimensions: length, width, and depth (height). In mechanical engineering, applications include, for example, the creation of prototypes or the manufacture of complex and lightweight components.

AI (Artificial Intelligence) is a technology that enables computers and machines to simulate human abilities such as learning, understanding, problem solving, decision making, creativity, and independent action. Systems with AI can recognize and identify objects and are used in a wide range of areas, including image and speech recognition, semantic language processing, pattern analysis, and process optimization.

Bill of Materials is a structured list of all raw materials, components, parts, and assemblies required to manufacture a product. It typically includes details such as part names, quantities, and part numbers.

Bottom-Up Analysis is a detailed method of cost calculation that starts with the basic components of a product or service. The costs of individual components, materials, and work steps are recorded and then gradually combined until the total costs are determined.

Computer-Aided Design refers to computer-assisted design, which helps architects, engineers, and other professionals to digitally create, analyze, and modify 2D and 3D models.

CAD Model is a digital 2D or 3D design created using CAD software. It replaces manual drawing methods and allows products to be created, analyzed, and visualized virtually before they are physically manufactured.

Cost & Value Engineering describes a structured approach to product optimization in which functions and costs are systematically examined in order to increase value without compromising key performance characteristics. It combines value engineering, which aims to maximize functionality and quality at minimum cost, and cost engineering, which ensures accurate cost calculation and consistent cost control throughout the entire development process.

Cost Analysis is a central component of cost management. It involves the structured recording, evaluation, and analysis of all costs associated with a product, with the aim of identifying potential savings and creating a sound basis for decision-making.

Cost Breakdown describes the structured breakdown and detailed analysis of all cost components of a product. The aim is to create full transparency regarding costs, identify key cost drivers, and identify opportunities for potential savings and more efficient negotiations.

Data Analysis in purchasing involves the structured evaluation of purchasing data to enable informed decisions, reduce costs, and make processes more efficient. It helps to identify potential savings, ensure the stability of supply chains, reduce risks, and increase performance by examining supplier, price, and market information. The methods used range from classic statistical procedures to modern, AI-based analysis techniques.

Deep Learning is a subfield of machine learning based on multilayer artificial neural networks. Its goal is to identify and process complex structures and patterns in large amounts of data. This technology enables computers to perform tasks that previously required human intelligence, such as image and speech recognition and natural language processing.

Design-to-Cost is a concept in product development in which costs are specifically considered and controlled at an early stage. The aim is to design products in such a way that a specified cost structure is adhered to. The focus is on achieving a balance between quality, functionality, and cost-effectiveness.

Enterprise Resource Planning refers to software systems that integrate and simplify a company's central business processes using a uniform database and automation. This enables efficiency gains, informed decision-making, and a transparent overview of the entire organization - from finance and human resources to supply chains, production, and sales.

Identical Part Search refers to a process for analyzing and identifying completely identical 3D CAD models, components, or drawings, i.e., duplicates. In contrast, similarity search aims to identify elements with the same or very similar shapes, but which may differ in size or other properties.

Machine Learning is a field of artificial intelligence in which computer systems learn independently to identify patterns by evaluating large amounts of data and make predictions or decisions based on this information - without having to be explicitly programmed to do so. With growing experience and an increasing database, the systems continuously improve and develop models that perform tasks with increasing efficiency.

NLPP (Non-Linear Performance Pricing) is a method for price analysis and cost optimization. It is used in areas such as purchasing, development, and sales to determine optimal target prices for products and services. Companies benefit from the opportunity to identify potential savings, compare prices with best practice benchmarks, and make informed decisions about suppliers and make-or-buy strategies.

Optical Character Recognition is a technology that converts text from images into machine-readable form. This makes scanned or photographed documents, which were originally only available as image files, searchable, editable, and reusable.

Product Lifecycle Management is a strategic approach to managing data, processes, and stakeholders throughout the entire lifecycle of a product - from the initial idea through development, production, and distribution to service and disposal. Using a central data source improves collaboration and transparency, accelerates time to market, and sustainably increases product quality.

Quoting in procurement describes the process of obtaining price quotes from potential suppliers for products or services. Common procedures include Request for Quotation (RFQ) – a formal request for detailed prices and terms – and Request for Proposal (RFP), in which the supplier's technical expertise and experience are evaluated in addition to the price. Another, different process relates to the management of sources of supply through quotations and determines what proportion of a requirement is to be covered by which source.

Arithmetic Mean Roughness Value is a crucial parameter in manufacturing and surface technology that describes the smoothness or unevenness of a surface. It is a measured value that indicates the average deviation of surface profiles from a center line.

Regression Analysis refers to a statistical analysis method that, for example in procurement, examines the relationship between a dependent variable (e.g., purchase price of a product) and one or more independent variables (e.g., order quantity, delivery time). It enables patterns to be identified, forecasts to be made, and data-driven decisions to be made.

Should Costing is a strategic analysis method for calculating optimal costs for products or services, in which the actual production or service costs are determined on the basis of all cost components involved. The result is a target price that reflects the costs under efficient market conditions and serves as a basis for evaluating supplier offers and price negotiations.

Similarity Search is a method for analyzing and identifying identical or very similar 3D CAD models, components, or drawings. Existing data is automatically compared with each other based on geometric features and displayed in a structured similarity hierarchy. Elements can vary in size or other properties - in contrast to identical part search, which targets exact duplicates.

Sourcing refers to the strategic procurement process for goods, services, and resources. It encompasses the identification, evaluation, and selection of suitable suppliers, as well as the negotiation of contract terms. The overarching goal is to achieve a balance between cost, quality, and delivery times.

Target Costing is a cost management method in which a predetermined price determines how high the production costs may be. The concept is usually applied during the development phase of new products and serves to control costs.

Total Cost of Ownership (TCO) is a holistic cost analysis of products or services that takes into account both acquisition costs and ongoing direct and indirect costs over the entire life cycle.

Value Engineering is a systematic method for optimizing the cost-benefit ratio of a product. The goal is to maximize functionality and quality while minimizing total costs over the entire life cycle.