Encord Index
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'.
Find alternatives to Encord Index
No dollar figures published. Index is metered by its OWN data volume quota per tier - Starter 'Up to 500k', Team 'Up to 100m', Enterprise '1bn+' - which is the separate-quota test passed on the vendor's own pricing table. Figures independently re-confirmed by the verification pass 2026-09-05.
What it does
- Vector search
- Data analysis
Sources
- Pricing
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Dedicated 'Index' section in the tier comparison table with its own per-tier volume quota (500k / 100m / 1bn+).
- Description
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Official documentation · 5 Sep 2026
Headline 'Train your AI models with the data that matters'; 'surface and refine only the most relevant AI data from across all of your data sources'; 'zero data migration required'.
- Sold within
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A separately metered section within the Encord platform plans; not sold as a standalone subscription.
- Name
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Official documentation · 5 Sep 2026
'Encord Index empowers AI & ML teams to efficiently create high quality, balanced datasets to improve AI model performance at scale.' NOTE the marketing path is /curation/, not /index/ - encord.com/index/ serves homepage content.
Also from Encord
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Encord Platform
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.
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Encord Annotate Data service
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.
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Encord Active Data service
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.
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Data Agents Agent platform
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.
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Merlin AI agent
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.
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Encord Data Annotation Data service
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.
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Encord Data Collection Data service
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.
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Physical AI Data Data service
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.
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