Expert annotation services for physical AI, multimodal systems, and LLMs
Vetted domain experts for your task, and an evaluation workflow built around your spec. Encord runs annotation projects for AI teams that need more than just volume.
Volume without quality destroys model performance
Our annotation service is designed to avoid the failures we see in annotation at scale: ambiguous guidelines, inconsistent edge cases, annotators lacking expertise, and a lack of traceability within workflows. At Encord, we align on quality standards early, diagnosing problems at the source.
“A big reason why we decided to partner with Encord was because of the quality bar we saw in doing POCs with a ~dozen companies.”
Devi Parikh
Co-Founder & Co-CEO of Yutori
How we annotate
Phase 1: Quality alignment
We start with a small pilot to find guideline gaps before the full dataset enters the pipeline. Edge cases get documented with visual examples rather than text descriptions.
Phase 2: Expert matching
Clinicians for medical imagery, specialist operators for robotics tasks, native speakers with subject matter background for LLM evaluation - whatever you're working with, we'll find the right people for your data.
Phase 3: AI-assisted execution
First-pass annotation runs through SOTA model integrations like SAM 3 and GPT-4o. Then, human experts handle review and correction - cutting per-task cost while maintaining accuracy.
Phase 4: QA and traceability
Every annotation decision is logged and visible in real-time - so you can keep track of accuracy, approval and rejection rates whenever you want.
One platform.
Every datatype for your pipeline.
No stitching together separate vendors for video, audio, and sensor data.
What you get with every project
Dedicated operations lead managing your project end to end
Encord-certified annotators trained as power users of the platform
Domain specialists from 40+ countries and regions
SOC 2, GDPR, and HIPAA compliant infrastructure
Agile delivery with flexible scaling between batches
Full audit logs and annotation traceability
What this looks like in production
See how 300+ of the best AI teams use Encord
Enterprise-grade.
Built for scale.
Designed for reliable AI.
Built for scale.
Designed for reliable AI.
API/SDK-first. Zero data migration. Your data stays in your cloud.
Visit trust center
Frequently asked questions
Quality targets are agreed upon before each project starts, depending on the use case. SLA-backed benchmarks are available for enterprise projects, alongside live dashboards that surface quality issues before they reach production.
Annotators are matched on domain expertise, clinicians for medical imaging, trained operators for robotics manipulation, native speakers for LLM evaluation, and region-specific specialists for financial services and multilingual audio. For highly specialised work, annotation guidelines are built alongside your subject matter experts before scaling.
Yes, your annotators work on the same platform as Encord's team. Existing annotators can be onboarded with platform training, while Encord's team covers specialist tasks, overflow, or QA.
Yes! SOC 2 Type II, HIPAA, and GDPR certified, with BAAs available for healthcare and clean room setups for financial services and defence. Annotator access controls include biometric or ID-based authentication, restricted personal devices, network isolation, and role-based permissions, with full audit trails on every action.
Yes! model integrations, including SAM 3 and GPT-4o, handle first-pass annotation, with domain experts reviewing and finalising. Your own pre-labelling models can be integrated via SDK or agent workflows, with predictions routed to human review.
Tell us what
you're building
Every project starts with a scoping call. We will review your data, define the task specification, and recommend the right annotator profile and workflow design.