polygon1
polygon2

Computer Vision

Data Annotation

& Labeling

Srihsta Technology has labeled, annotated, enriched and segmented over 1 million images and videos that power Computer Vision algorithms. Srishta’s delivery team works with complex edge cases and nuanced taxonomies to give clients an extra advantage.

Hero_Annotation

Pixel-Perfect Labeling for AI Vision in 2026

annotation-workflow

Why Choose Our Annotation Service?

Computer vision annotation refers to the process of labeling images or video frames to train machine learning models to identify and understand visual data. These annotations guide AI algorithms in interpreting the world - whether it’s recognizing a stop sign or detecting a tumor on an MRI scan.
The process involves tagging objects, people, or boundaries in images so that AI systems can learn from them. Without computer vision annotation, machines would be blind to the nuances of the visual world.

  • 99.9% Accuracy Guarantee
  • 500+ Expert Annotators
  • ISO 27001 & GDPR Compliant
  • 48-Hour Turnaround

Supported Annotation Types

Bounding Boxes

Srishta Technology Computer Vision experts use rectangular box annotation to illustrate objects and train data, enabling algorithms to identify and localize objects during the ML processes.

1.2M+ boxes

Semantic Segmentation

Images are segmented into component parts, by the Srishta Technology team and then annotated. Srishta Technology Computer Vision experts detect desired objects within images at the pixel level.

850K+ masks

LiDAR Annotation

Srishta Technology teams label images and videos in 360 degree visibility, captured by multi-sensor cameras, in order to build accurate, high-quality, ground truth datasets for use cases including autonomous vehicles.

180K+ frames

Polygon Annotation

Expert annotators plot points on each vertex of the target object. Polygon annotation allows all of the object’s exact edges to be annotated, regardless of shape.

720K+ polygons

PanOptic Segmentation

Coupling instance and semantic segmentation, Srishta Technology enrichment teams identify the pixels in images as belonging to a class and identify what instances of that class they belong to.

400K+ nanoptic

Instance Segmentation

Unique IDs per object instance

980K+ instances

Video Tracking

Frame-by-frame object tracking

320K+ tracks

Keypoints & Skeletons

Pose estimation and facial landmarks

600K+ points

Annotation Tools & Platforms

Custom Web Labeler

In-house tool with AI pre-labeling, QA layers and team collaboration

CVAT Integration

Open-source CVAT with enterprise extensions and API access

Labelbox Sync

Seamless import/export with Labelbox workflows

AI Pre-Annotation

Reduce manual effort by 70% using YOLO, SAM and custom models

Mobile App Review

On-field QA and validation via iOS/Android apps

Audit & Analytics

Real-time quality metrics, annotator performance and drift detection

Top Computer vision annotation services India

Srishta Technology is the top computer vision data labeling company in India, offering comprehensive computer vision annotation services in India for AI and machine learning projects. As the best computer vision data annotation company in India, we provide precise computer vision data labeling services and AI computer vision annotation tailored to diverse industries. Our expertise includes image and video annotation in India, computer vision dataset annotation and computer vision tagging services to enhance model accuracy. We are a trusted computer vision labeling company and CV annotation company, delivering high-quality machine learning data labeling and data annotation for computer vision. With Srishta Technology, businesses can rely on scalable, reliable and professional annotation solutions that power cutting-edge AI applications.

How Srishta Technology Ensures Data Security / Data Safety

Data annotation projects often involve large volumes of sensitive datasets such as images, videos, text, medical records and business data. Protecting this data is extremely important to maintain confidentiality, integrity and compliance. Srishta Technology follows strict security practices and industry standards to ensure that client data remains safe during the annotation process.

Encrypted Data Storage and Transfer

Srishta Technology uses encrypted pipelines and secure storage systems to protect data during transfer and while it is stored on servers. Encryption ensures that unauthorized users cannot access or read the data.

Compliance with International Security Standards

We follow globally recognized data protection regulations such as GDPR, HIPAA and CCPA to ensure proper handling of sensitive and personal datasets.

Secure Access Control

Only authorized team members can access datasets. Role-based permissions ensure employees only access data required for their tasks while preventing unauthorized access.

Confidentiality Agreements (NDAs)

All annotators and employees sign strict Non-Disclosure Agreements to protect client information and prevent data leakage.

Secure Infrastructure and Audit Logs

Our infrastructure includes monitoring systems, audit logs and secure server environments to track and prevent potential threats.

Strict Data Privacy Protocols

We implement strict privacy policies ensuring sensitive datasets remain confidential during the entire annotation lifecycle.

Controlled Annotation Environment

Annotation work is performed in controlled environments where downloads and external copies are restricted and secure tools are used for labeling.

Employee Training and Security Awareness

Srishta Technology regularly conducts data security and privacy training programs for its employees and annotators. These sessions help the team understand data protection, safe data handling practices.

Regular Security Audits and Risk Assessments

The company performs regular security audits and risk assessments to identify vulnerabilities in systems and processes.

Start Annotating with Precision Today

From autonomous vehicles to medical imaging - power your vision AI with gold-standard labeled data.

Request a Demo