Engineerify.AI
AI-Powered Materials Discovery Platform

MatPilot-AI

The GitHub Copilot for Materials Discovery

Accelerate materials research with AI-powered crystal structure prediction, stability analysis, and property optimization. Powered by GNoME (Graph Networks for Materials Exploration) with 2.2M+ predicted crystals and 380,000 stable structures.

What GNoME Technology Does

DeepMind's GNoME is an AI model designed to accelerate the discovery of novel materials by predicting the stability of crystal structures with unprecedented accuracy.

Graph Neural Networks

Uses advanced GNNs to understand crystal structures and predict material properties with high accuracy.

Formation Energy

Predicts formation energy, stability, and crystal structure with DFT-level accuracy at fraction of cost.

Materials Database

Trained on comprehensive databases like Materials Project, OQMD, and AFLOW for maximum coverage.

DFT-Level Accuracy

Delivers density functional theory accuracy while reducing computational costs by orders of magnitude.

SaaS Use Cases

Transform materials discovery across industries with targeted AI solutions

Battery Companies
Next-Gen Energy Storage

Discover new solid-state electrolyte materials for safer, more efficient batteries.

Solid-State Electrolytes
Semiconductor Firms
Advanced Electronics

Find materials with low thermal expansion and high dielectric constants for next-gen chips.

High-K Dielectrics
Materials Labs
Research & Development

Predict stability and formation energy of novel materials before synthesis.

Stability Prediction
Pharma/Chemistry
Drug Development

Predict organic and inorganic crystal structures for pharmaceutical applications.

Crystal Polymorphs

Platform Architecture

Built with cutting-edge AI and modern cloud infrastructure

Backend Stack
Scalable AI infrastructure

AI Model Layer

  • • PyTorch Geometric for GNN models
  • • DGL and Jraph for graph processing
  • • ONNX for optimized inference

Data & Storage

  • • PostgreSQL for metadata
  • • S3 for structure files (CIF, POSCAR)
  • • Redis for caching

Processing

  • • FastAPI for inference APIs
  • • Celery for background tasks
  • • Argo Workflows for DFT orchestration
Frontend Stack
User-friendly interface

User Interface

  • • React.js + Tailwind CSS
  • • CIF/POSCAR file upload
  • • Real-time progress tracking

Visualization

  • • 3Dmol.js for crystal structures
  • • Crystal Toolkit integration
  • • NGL Viewer for complex structures

Integrations

  • • Materials Project API
  • • DFT integration (ASE, VASP)
  • • Export to multiple formats

Choose Your Plan

Start free and scale as your research grows

Free
Perfect for getting started
$0/month
Upload 1 crystal structure
Basic model prediction
3D visualization
Community support
Most Popular
Pro
For professional researchers
$99/month
Unlimited batch predictions
Advanced visualization
Export capabilities
API access
Priority support
Enterprise
For large organizations
$999/month
On-premise DFT runner
Custom model training
Dedicated support
SLA guarantee
White-label options

Success Story

Real results from leading research institutions

TechCorp Materials Division
Accelerating solid-state battery development with AI-powered materials discovery
6 months

vs 18 months traditional research

67% time reduction

85%

reduction in R&D costs

$2.3M saved annually

12

viable candidates identified

3 in production testing

"MatPilot-AI transformed our materials discovery process. We identified 12 promising solid-state electrolyte candidates that we never would have considered before. The AI predictions were validated with 94% accuracy in our lab tests."
Dr. Sarah Chen
Head of Materials Research, TechCorp

MatPilot-AI vs Traditional Methods

See how AI accelerates materials discovery

Traditional Approach
Experimental trial-and-error
18-24 months per material
$500K+ per discovery
Limited exploration space
High failure rate >80%
Resource intensive
MatPilot-AI Approach
AI-powered discovery
6-8 months per material
$75K+ per discovery
Vast exploration space
Low failure rate <20%
Computationally efficient

Ready to Accelerate Your Materials Discovery?

Join leading research institutions and companies using MatPilot-AI to discover the materials of tomorrow. Start with our free tier and scale as you grow.

No credit card required • 14-day free trial • Cancel anytime