Encord vs Siemens Healthineers

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.

The multimodal data layer for physical AI: one platform for managing, curating, annotating and aligning sensor, video, image and text data at petabyte scale. The modules a buyer licenses — Annotate, Index and Active — are recorded separately.

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.

Multi-modality imaging decision support that pre-reads CT and MR studies — highlighting findings and taking measurements automatically — delivered as extensions on the teamplay digital health platform.

Deep-learning MR image reconstruction software that denoises and super-resolves acquisitions to accelerate MRI scans while maintaining or increasing resolution.

Varian's radiotherapy treatment-planning system, covering photon, proton, electron and brachytherapy dose calculation. Its AI Contouring is embedded rather than bolted on: deep-learning structure delineation that generates contours from CT and MRI for over 200 anatomical structures, including organs-at-risk, lymph nodes and brain metastases, built on RTOG, ESTRO and DAHANCA guidelines. The v18.1 release that carries AI Contouring is CE marked with its 510(k) pending, and is not sold in the US or in all markets.

Varian's adaptive radiotherapy system, marketed as an Adaptive Intelligence solution: AI segmentation contours the day's anatomy and AI planning re-optimises the treatment while the patient is on the couch, so the plan follows the tumour rather than the plan made weeks earlier.

AI imaging chain for Artis angiography systems that applies deep-learning noise reduction to live fluoroscopy and DSA in real time, delivering higher-quality low-dose images during image-guided procedures.

Knowledge-based treatment planning inside Eclipse: models learned from a clinic's own prior plans estimate the achievable dose-volume histogram for a new patient, so a planner benchmarks against past practice instead of starting from scratch. Pre-loaded DVH estimation models from named institutions ship with it.

AI-guided scanner operating interface that turns clinical questions into optimized acquisition and reconstruction parameters, with an AI-powered Autosuite (AutoAlign, AutoBolus Detection, AutoLabeling) across CT, MR, radiography and SPECT/CT systems.

AI-based software for coronary CT angiography that automatically segments and labels the coronary tree and quantifies plaque types to support coronary artery disease management and PCI planning.