Lean R&D - Building effective, rapid, and efficient R&D processes, bringing products to market faster

MaterialsZone's Solution:
  • Streamline all your lab data across your entire R&D organization
  • Share key insights across teams, in real-time
  • Use advanced AI & Machine Learning to predict & optimize formulations
  • Stay compliant & secure – confidently store sensitive data

R&D of materials-based products struggles with complex workflows, manual tasks, high complexity and data silos. This slows progress and impacts business results. MaterialsZone solves this by streamlining processes, connecting teams, and unifying data - resulting in Lean R&D.

Improved Efficiency

Lean R&D leads to shorter product development cycles, better management of multiple projects, and optimal utilization of available resources.

Enhanced Quality

By focusing on continuous attention to quality, Lean R&D helps in detecting and correcting quality issues early in the development process, preventing costy delays and rework.

Accelerated Time to Market

Companies can reduce the time required to bring new products or technologies to market, gaining a competitive edge through quicker product launches.

Materials Knowledge Center

Make data available, accessible, accurate, timely

A centralized platform to gather data from both internal and external sources, leveraging GenAI for accelerated data ingestion. The platform serves as a repository for the organization’s knowledge, preserving data, processes, and insights for researchers, engineers, and decision-makers, making it easy for everyone in the organization to quickly find what they need.

Collaborative Framework

Improve coordination through sharing, notifications and other collaboration tools

Cloud-based, cross-departmental, real-time collaboration with permission-based access control, facilitating seamless interaction among different teams, regardless of their physical location, and, at the same time, ensuring that sensitive information remains protected, accessible only to authorized personnel.

Co-Active Visualizer

Gain and share insights from analytical visualizations specialized in the materials domain

Facilitating cross-organizational, multi-dimensional analysis, allowing teams to view and interpret complex data, enhancing the ability of the organization to uncover correlations and trends, and identify patterns within the R&D process, making informed data-driven decisions.

Predictive Co-Pilot

Leverage AI/ML to improve outcomes and reduce iterations of product discovery

Accelerating the product discovery process by employing machine learning and AI to model the entire R&D process, predicting experimental results, and substantially reducing the number of iterations required to achieve desired outcomes.

The Lean R&D Materials Informatics Platform

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