Pixel-level accuracy is determined by the annotator holding the tool, not the tool itself. iMerit builds custom annotation workflows for each program, staffs them with domain-trained teams, and applies two-stage QA to every batch. You get labeled images that meet your acceptance criteria. We own the quality, end to end.
End-to-end image annotation services built for accuracy, scale, and seamless integration into your AI pipeline.
BESPOKE WORKFLOWS. MANAGED DELIVERY. QUALITY WE OWN.
Annotators assessed on domain-specific curricula before going live. Teams are trained on your taxonomy during the pilot phase and calibrated against your ground truth before scaling.
Production and QA are separate stages on every program. Custom validation rules catch class errors, missed instances, and boundary inconsistencies before export. You don’t review our mistakes.
Dedicated teams for medical imaging, AV, geospatial, agriculture, retail, and industrial inspection. Domain expertise is built in, not bolted on.
Every image annotation type your computer vision model requires.
Single-label and multi-label classification across custom taxonomies, covering scene understanding, defect classification, crop health scoring, and content moderation programs.
KinaTrax, one of MLB’s primary motion capture vendors, needed to annotate terabytes of pitcher footage captured from twelve simultaneous angles. iMerit extracted still images across all twelve angles and applied precise keypoint annotations to each joint. The result was a skeletal dataset that trained models capable of analyzing pitching mechanics from any viewing angle.
3D pitcher models built from multi-angle motion capture footage
Simultaneous viewing angles annotated per pitcher
Images labeled by iMerit across computer vision programs globally
A bounding box drawn by someone who doesn’t understand your data distribution is wrong in ways that are hard to detect and expensive to fix. iMerit trains annotators on your specific taxonomy, calibrates against your ground truth during a pilot, and runs two-stage QA on every batch. Boundary accuracy is our responsibility.
We design your label taxonomy and annotation rules before a single image is labeled. Edge case parameters are defined upfront so annotators make consistent decisions at scale, not improvised ones.



Images labeled across computer vision programs
Full-time domain-trained annotators
Industry verticals served
SOC 2 Type II · HIPAA · GDPR compliance
Lane detection, object recognition, semantic segmentation, and ADAS perception annotation across diverse real-world driving conditions.
Organ segmentation, lesion detection, radiology image labeling, and DICOM annotation with clinical expert review for diagnostic and surgical AI.
Land use classification, infrastructure detection, vegetation mapping, and change analysis across aerial, drone, and satellite imagery.
Crop and weed labeling, plant disease detection, canopy and field feature annotation for precision agriculture AI.
Keypoint and pose annotation for athlete performance analysis, injury prevention, motion capture processing, and sports AI model training.
Object boundary annotation, depth and spatial relationship labeling, grasp training data, and visual perception datasets for manipulation and navigation models.
What kinds of image annotations do you provide?
iMerit supports bounding boxes, polygons, key‑points, semantic segmentation, panoptic segmentation,3D cuboid annotation, rapid annotation, and image classification, with workflows tuned to your taxonomy and quality targets. We also support polyline and LiDAR annotation.
How do you ensure image annotation quality at scale?
Programs use custom QA processes, reviewer calibration, and multi‑stage validation. iMerit’s Computer Vision teams have labeled 100M+ images and videos, with specific handling for edge cases and nuanced taxonomies.
Do you offer automation or pre‑annotation to speed up projects?
Yes. iMerit combines computer‑assisted/pre‑annotation with expert review to improve throughput while meeting precision targets; this can run in your tools or on Ango. Rapid annotation is also available for suitable file types.
Which industries does iMerit support?
Yes. iMerit has domain-focused teams for autonomous mobility, robotics, medical AI, geospatial, agricultural, government, finance and insurance, commerce/retail, and enterprise companies.
How does iMerit ensure quality at scale?
We combine clear guidelines, calibrated experts, and multi-level QA to meet your acceptance criteria. Quality is tracked through defined metrics (IoU, error rates, per-class performance) and shared in regular reports.
Can you combine image annotation with text or document understanding?
Yes, image tasks can be paired with text annotation for multimodal training (e.g., IDP, image captioning/summarization, product recognition).
Can you work inside our existing tools and MLOps stack?
Yes. We can work directly in your annotation tools or run projects on iMerit’s Ango Hub, with API and plugin-based integrations into your data pipelines and model workflows.
How quickly can you start a pilot, and what does onboarding look like?
We begin with scope and taxonomy alignment, define acceptance criteria and QA, then launch a pilot batch to calibrate quality and throughput before scaling.
How is data privacy and security handled for enterprise projects?
iMerit is certified with SOC 2, ISO 27001/9001, GDPR, HIPAA, TISAX with strict access controls, NDAs, and full audit trails for sensitive projects.