Frontier Process Intelligence for the Future of Materials Synthesis
Get ahead of your technology roadmap with real-time visibility, control, and automation for atomic-scale fabrication.
"I have been waiting for someone to do this for 20 years."
⸺ Staff Scientist, Leading Tool Company
Unlock innovation with real-time visibility,
adaptive process control, and agentic automation.
Capture
Connect, unify, and enrich 100% of your process data into a context-rich intelligence layer that makes every signal available for analysis and decision-making.
Connect your tools
Stream data from tools and instruments for real-time observability of your entire fab.
Unify your data
Combine tool logs, metrology, and characterization to establish a unified record for each run.
Enrich process context
Extract key insights and structure to build a complete understanding of your process for automation.

Understand
Get real-time, continuous visibility into the health of your fabrication with intelligence that surfaces anomalies and accelerates resolutions.
Discover relationships
Identify relationships between your recipes, tools, and growths for optimization and control.
Model material state
Establish models for each growth with a detailed understanding of material state and properties.
Speak to your fab
Query your tools and runs with natural language to uncover new insights and automate analysis.

Improve
Apply adaptive process control that understands and adjusts to how growths are developing to drive higher yields, faster scale-up, and reliable production.
Monitor process health
Gain visibility into material state during live runs for real-time, layer-by-layer feedback.
Diagnose issues
Trace when and how a run drifted, identifying specific variables to accelerate root-cause analysis.
Control synthesis
Adjust runs based on tool state and material responses for precise process control and outcomes.

Stay ahead of your technology roadmap.
Ultimately, manufacturing complex materials reliably requires real-time visibility into material state during growth and the means to respond to it intelligently, both of which are gaps in today's tools and software.
By providing real-time visibility into material state, adaptive process control, and agentic automation, Atomscale allows your organization to manufacture complex materials more reliably, at lower cost, and at the pace your roadmap demands.
Empower every level of your organization with frontier intelligence.
Atomscale integrates into how your organization, data teams, and process teams already operate and gives each new capabilities and leverage.
Your real-time intelligence to understand operations across your fab.
See production performance and risk across your operations in real-time, queryable with natural language. Enable new materials scale-up and integration with frontier process insights.
Get above the engineering problems that pull you down.
From development to production, Atomscale provides the intelligence and infrastructure to unblock and accelerate your engineering operations.
Engaged partnership to develop material outcomes.
We're materials scientists and engineers who've spent our careers applying AI and computational modelling to the frontier of materials problems.
When you choose Atomscale, we don't just throw a product over the wall. We embed into your team to understand your goals, build a shared roadmap, and integrate with your operations — so we can deliver meaningful outcomes both today and tomorrow.












































We handle the technical work of connecting your data sources, configuring models for your process, and validating results against your existing metrology, so your team can focus on running production.
Our engagements are structured around defined success criteria and a shared timeline, so you always know what's been demonstrated, what's next, and what value each stage delivers.
We work with you to establish what AI-native process control looks like for your materials and your operations, defining new capabilities at the frontier of the industry.