Dataiku vs Encord

Dataiku — Application · Private · $3.7B valuation · 4 of 4 figures sourced  |  Encord — Infrastructure · Private

Relationship

Assembled from the recorded fields for this pair, not hand-checked. The comparison below is read from each company’s own profile.

Aligned comparison

FieldDataikuEncord
Size$3.7B valuationnot disclosed
Employees1,250—
Founded2013—
StatusPrivatePrivate match
CategoryApplicationInfrastructure
Stack layerAI agent, Agent platform, Infrastructure service, PlatformAI agent, Agent platform, Data service, Platform
HeadquartersNew York, USALondon, United Kingdom

Capability overlap

Shared · 4

Agent orchestrationData analysisEvaluation and observabilityWorkflow automation

Not verified for Encord · 4

Data securityGuardrails and safetyModel inferenceModel training

Recorded for Dataiku. Encord’s product records say nothing either way — a missing record is not a missing capability.

Not verified for Dataiku · 3

Data labellingMedical imaging analysisVector search

Recorded for Encord. Dataiku’s product records say nothing either way — a missing record is not a missing capability.

Products, side by side

Algorithmic pairing — assembled from recorded fields, not hand-checked

Dataiku

AI agent

Dataiku CobuildAI agent

AI building agent that turns a business objective written in plain language into a governed Dataiku project of data pipelines, models, agents and applications rendered as an editable visual workflow.

Agent platform

Dataiku Agent HubAgent platform

Centralised control plane inside the Dataiku platform for creating, orchestrating, deploying and tracking AI agents across teams.

Dataiku E2AAgent platform

Expert-to-Agent engine that converts subject-matter-expert know-how into governed AI agents grounded in enterprise data with structured reasoning and human oversight.

Platform

DataikuPlatform

Platform for building, deploying and governing data, machine-learning and agent workflows across an organisation.

Encord

AI agent

MerlinAI 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.

Agent platform

Data AgentsAgent 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.

Platform

EncordPlatform

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.

No counterpart

Dataiku sells these in a stack layer with no product recorded for Encord yet — nothing on the other side to compare them against.

Infrastructure service

Dataiku Agent ManagementInfrastructure service

Cross-platform governance product that discovers every AI agent an enterprise is running -- on Microsoft Copilot Studio, Azure Foundry, Salesforce Agentforce, AWS Bedrock, Google Vertex, Databricks, Snowflake Cortex, n8n or Dataiku itself -- measures each agent's business and technical performance, and flags the ones that pose the greatest risk. Announced 2026-09-24; distinct from Dataiku Agent Hub, which creates and operationalizes agents rather than discovering and governing agents built anywhere.

Dataiku LLM Guard ServicesInfrastructure service

Control layer over the Dataiku LLM Mesh that caps LLM spend, screens prompts and outputs for sensitive or malicious content, and scores model output quality.

Dataiku LLM MeshInfrastructure service

Centralised gateway that routes, meters and governs an organisation's connections to multiple LLM providers from inside the Dataiku platform.

Encord sells these in a stack layer with no product recorded for Dataiku yet — nothing on the other side to compare them against.

Data service

Encord ActiveData 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.

Encord AnnotateData 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.

Encord Data AnnotationData 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.

Encord Data CollectionData 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.

Encord IndexData service

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'.

Physical AI DataData 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.