Applied Materials vs Encord

Fab software that uses machine learning to predict metrology measurement values in real time with confidence scores, reducing reliance on physical measurement and auto-retraining models when drift is detected.

Software that augments existing run-to-run process control with machine learning models that recommend recipe parameter adjustments for high-mix, low-volume and nonlinear processes.

AI-based fab software that automatically detects and classifies wafer inspection images into more than 100 defect categories, replacing manual and rule-based defect review.

Brightfield optical wafer inspection system whose third-generation ExtractAI technology pairs its scan data with SEMVision eBeam review to separate yield-killing defects from millions of nuisance signals.

Integrated die-to-wafer hybrid bonding system for HBM, AI accelerators and co-packaged optics, with an AIx-powered software suite providing predictive maintenance, die-level traceability and multi-binning.

Cold field emission eBeam defect review system that integrates deep learning AI to automatically extract and classify yield-killing defects from wafer inspection data.

Modular wafer-processing platform holding four to twelve mixed ALD, CVD, epitaxy and etch chambers, instrumented with thousands of sensors that feed Applied's AIx software for machine-learning recipe acceleration.

Merlin is Encord's agentic intelligence layer, letting teams build, observe and optimise their data infrastructure through conversation. It creates complete labeling setups from prompts or documents, reports data metrics and coverage gaps on demand, and surfaces issues affecting model performance. It is reachable inside Encord or from external tools over Model Context Protocol, including Claude and Slack.

Data Agents automate Encord data pipelines by integrating humans, state-of-the-art models and a customer's own models into data workflows. They handle tasks such as pre-labeling, object segmentation and tracking, video captioning, audio transcription and sentiment analysis, combined with human-in-the-loop quality assurance.

Encord Active is Encord's model and data evaluation product. It evaluates and validates models against their data to surface, curate and prioritise the most valuable data for training and fine-tuning, covering model robustness checks, drift and failure-mode detection, automated label-error detection, and active learning workflows across images, video, 3D/LiDAR, audio and documents.

Encord Annotate is Encord's multimodal data labeling product, used to annotate and review images, video, audio, text, documents, DICOM, LiDAR and geospatial data. It provides AI-assisted labeling, customizable ontologies, human-in-the-loop review workflows and quality-control tooling for managing large annotation teams.

Managed annotation service: Encord supplies vetted domain experts for a customer's task and runs the projects, with an evaluation workflow built around the customer's own spec rather than volume alone.

Managed collection of real-world training data for physical AI: in-field operators, teleoperation facilities and configurable lab environments gathering the embodied, egocentric and sensor data a robotics model needs.

Encord Index is Encord's multimodal data curation and management product. It lets teams search datasets with natural language and similarity search across video, image, audio, LiDAR, text, document, geospatial and HTML files, filter by 40+ data metrics and custom metadata, visualise outliers on embeddings plots, and remove duplicates and poor-quality data via Collections. Data stays in the customer's own cloud with 'zero data migration required'.

End-to-end data service for robotics, autonomous systems and embodied AI: data collection (in-field operators, teleoperation), curation, LiDAR/point-cloud/multi-camera annotation, VLA/VLM action-captioning, and post-deployment feedback loops, with on-prem/VPC deployment.