---
type: "Page"
title: "Services"
description: "Data annotation and labeling services for AI and ML teams: image, video, text, audio, LiDAR and LLM data, three-layer QA, certified security and a free pilot."
resource: "https://www.annotera.ai/services/"
timestamp: "2026-08-20T12:41:17+00:00"
---
# Data Annotation Services for AI and Machine Learning
Annotera provides data annotation services for AI and machine learning teams that need training data they can trust. Domain-trained annotators label text, image, video, audio, LiDAR and LLM data to your guidelines, with three-layer QA and certified security. Start with a free 48-hour pilot on your own data.
[Start Your Annotation Project ](/okf/page/get-a-quote.md)
## Data Labeling Services Built for Production AI
A model is only as reliable as the labels it learns from. Annotera turns raw, unstructured data into consistently labeled training, validation and test sets, so ML teams spend their time on models instead of managing labelers and repairing datasets.
Our data annotation services are used by computer vision, NLP, speech and generative AI teams at startups and enterprises, across autonomous vehicles, healthcare, retail, financial services and robotics. Every program runs with dedicated, employed annotators trained on your guidelines and scored against your gold set, not an anonymous crowd. If you are new to the topic, our guide to [what data annotation is](/okf/article/what-is-data-annotation.md) explains the main types, the process and how quality is measured.
Annotera is part of Fusion CX, with 17,000 people across 40 delivery centers in 13 countries. Teams that want a fully managed, dedicated operation can use our [data annotation outsourcing services](/okf/page/data-annotation-outsourcing.md), with onshore, nearshore and offshore delivery.
## ServicesAnnotation Services for Every AI and ML Data Type
No two AI projects need the same labels. Choose a single annotation service or combine several in one program; each page below covers the methods, use cases and QA approach for that data type. Specialist work includes [LiDAR and 3D point cloud annotation](/okf/page/lidar-annotation.md), [speech transcription](/okf/page/speech-transcription.md), [content moderation](/okf/page/content-moderation.md) and [named entity recognition](/okf/page/named-entity-recognition.md).
[
### Text Annotation
Transform unstructured text into structured AI training data through entity labeling, sentiment analysis, intent classification, and semantic annotation to improve NLP models, chatbots, and large language models.
](/okf/page/text-annotation.md)
[
### Image Annotation
Accurately label images using bounding boxes, polygons, segmentation, and keypoints to train computer vision models for object detection, image classification, and visual recognition applications.
](/okf/page/image-annotation.md)
[
### Audio Annotation
Annotate speech and sound data through transcription, speaker identification, intent labeling, and audio classification to build accurate speech recognition and conversational AI systems.
](/okf/page/audio-annotation.md)
[
### Video Annotation
Deliver frame-by-frame video annotation with object tracking, event detection, activity recognition, and temporal labeling for autonomous vehicles, surveillance, robotics, and video analytics solutions.
](/okf/page/video-annotation.md)
[  ](/okf/page/llm-genai-annotation.md)
[
### LLM & GenAI Annotation
Support generative AI development with RLHF, prompt-response evaluation, preference ranking, instruction tuning, and AI safety annotation to improve large language model performance and reliability.
](/okf/page/llm-genai-annotation.md)
[  ](/okf/page/robotics.md)
[
### Robotics Data Annotation
Label multi-sensor robotics datasets, including teleoperation, egocentric video, sensor fusion, and robot actions, enabling autonomous navigation, manipulation, and intelligent robotic decision-making.
](/okf/page/robotics.md)
[  ](/okf/page/multilingual.md)
[
### Multilingual Annotation
Create high-quality multilingual datasets by annotating text, speech, and documents across multiple languages, helping AI models understand regional context, linguistic nuances, and global user interactions.
](/okf/page/multilingual.md)
[  ](/okf/page/multilingual.md)
[
### AI Data Collection
Source and capture model-ready training data, from egocentric and exocentric video to images, audio, text, sensor streams and synthetic datasets, built to your specification.
](/okf/page/ai-data-collection.md)
##### 3
QA Layers
Annotator, lead and independent review
##### 40
Delivery Centers
Across 13 countries
##### 28+
Languages
Text and audio annotation
##### 48 hr
Free Pilot
On your own data
\*Delivery centers and countries refer to the Fusion CX delivery network.
## ProcessHow a Data Annotation Project Works
Every engagement follows the same sequence, so quality is proven before volume arrives and stays visible after it does.
### 1. Scope and Pilot
We review your data, label set and guidelines, then annotate a sample, usually within 48 hours, and score it against your gold set and acceptance criteria.
### 2. Calibrate and Ramp
Edge cases, accuracy thresholds and turnaround are agreed in writing. Annotators are trained and certified on your guidelines before production starts.
### 3. Deliver, Measure, Scale
Batches ship with quality reports. A named delivery manager tracks accuracy and throughput every week, and the team grows or shrinks with your volume.
## AI-AssistedAI-Assisted Data Annotation With Human Review
Our AI data annotation services combine model-assisted labeling with human judgment. Where a model is reliable, it pre-labels routine items such as common objects, steady video motion or clear speech, and trained annotators review and correct every suggestion. Low-confidence and high-risk items go straight to senior annotators, and gold sets are labeled without pre-labels so accuracy is always measured against the truth, not against the model.
The result is faster turnaround on routine work without the quality loss that comes from annotators simply accepting what a model proposes. We can use your own models for pre-labeling, which focuses human effort on exactly the errors your model makes. Our guide to [pre-labeling and AI-assisted annotation](/okf/article/pre-labeling-model-assisted-annotation.md) explains how to measure whether it is working.
## Why AnnoteraWhy AI Teams Choose Annotera for Data Labeling
Labeling at scale only works if quality, security and continuity hold up after the pilot. These are the commitments behind every program.
### Domain-Trained Teams
Employed annotators assigned to your project and trained on your domain, from clinical text to LiDAR scenes, so knowledge builds instead of resetting with every batch.
### Three-Layer QA
Annotator self-review, team-lead checks and independent QA validation, scored against gold sets with accuracy reported per class and per error type.
### Certified Security
Operations certified to ISO/IEC 27001:2022, SOC 2 Type II, HITRUST CSF and PCI DSS 4.0.1, with HIPAA-compliant workflows and role-based access.
### Flexible Delivery
Onshore, nearshore and offshore teams, or a blend of all three. See our [**data annotation outsourcing**](/okf/page/data-annotation-outsourcing.md) models.
### Your Tools or Ours
We work inside your annotation platform or in established commercial tools, and deliver in the formats your training pipeline expects.
### Pilot Before You Commit
A free 48-hour pilot on your own data, so you judge quality on evidence before signing anything.
## **Connect** with an **Expert**
Industry \*Security & SurveillanceAutonomous DrivingRoboticsRetailHealthcareOther
Area of Interest \*Text AnnotationImage AnnotationAudio AnnotationVideo Annotation
Preferred Location \*OnshoreNearshoreOffshore
Attach RFx Document
(\*.docx, .pdf, .zip only)
## IndustriesIndustries We Support
Annotation teams are organized by domain, so the people labeling your data understand the context behind it.
**[Autonomous Vehicles](/okf/page/autonomous-vehicle.md)**
Object, lane and LiDAR labeling for perception, ADAS and autonomous delivery programs.
**[Healthcare](/okf/page/healthcare.md)**
Medical imaging, clinical text and clinical audio annotation in HIPAA-compliant workflows.
**[Retail and Ecommerce](/okf/page/retail.md)**
Shelf monitoring, product recognition and cashierless checkout data at SKU level.
**[Financial Services](/okf/page/financial-services.md)**
Document extraction, entity recognition and transaction data for risk and fraud models.
**[Legal](/okf/page/legal.md)**
Contract entity recognition, clause classification and document review datasets.
**[Security and Surveillance](/okf/page/security-and-surveillance.md)**
Video analytics, person and vehicle tracking, and event detection.
**[Agriculture](/okf/page/agriculture.md)**
Crop, livestock and aerial imagery labeling for yield, health and monitoring models.
**[Robotics](/okf/page/robotics.md)**
Egocentric video, teleoperation and multi-sensor data for robot learning.
## Case StudiesData Annotation Programs in Production
Annotation and human-in-the-loop programs running today for retail, public safety and autonomous delivery clients.
**Autonomous retail**
Annotation partner since 2020 to a global cashierless-store technology company, delivered from India, the Philippines and Albania for stores and live-event venues across the U.S. and Europe.
[Read the autonomous retail case study →](/okf/case-study/real-time-annotation-for-autonomous-retail.md)
**Wildfire monitoring**
A 100+ person human-in-the-loop team went live on April 10, 2025, met every KPI by week four and reached 100% certification on real wildfire scenario simulations.
[Read the wildfire monitoring case study →](/okf/case-study/building-a-scalable-wildfire-monitoring-workforce-an-annotera-success-story.md)
**Autonomous delivery fleet**
A Watcher and Resolver workforce supported a global ride-sharing leader’s autonomous delivery operations: 656,000+ sessions, zero accidents and 3x capacity growth in under six months.
[Read the robot and AV operations case study →](/okf/case-study/cost-efficient-robot-av-operations.md)
## FAQQuestions About Our Data Annotation Services
Straight answers on scope, quality, pricing, security and how to get started.
#### What are data annotation services?
Data annotation services provide the trained people, processes and tools to label your raw data (images, video, text, audio, LiDAR or LLM outputs) so machine learning models can learn from it. A managed provider such as Annotera refines the guidelines with you, labels the data, runs quality assurance and reports accuracy against agreed targets.
#### What types of data can you annotate?
Text, images, video, audio, LiDAR and 3D point clouds, and LLM and generative AI data such as prompts, responses and preference rankings. We also [collect new training data](/okf/page/ai-data-collection.md) when you do not have enough of your own, and multilingual work is done by native speakers.
#### How do you ensure annotation quality?
Every program uses written guidelines, a gold set and three-layer QA: annotator self-review, team-lead checks and independent QA validation. Accuracy is reported per class and per error type, not as one overall score, and recurring errors are fed back into the guidelines.
#### How is pricing for data annotation services calculated?
Pricing depends on the data type, the annotation method, the expertise required, quality targets and volume; simple image classification is priced very differently from 3D LiDAR or clinical text. Most programs are priced per unit (per image, minute of audio or record) or per dedicated annotator. A pilot on your own data gives an accurate quote before you commit.
#### How quickly can a project start?
A pilot on a sample of your data is usually delivered within 48 hours of receiving the data and guidelines. Production ramp time depends on team size and how specialized the work is, and is agreed with you during the pilot.
#### Is our data secure?
Yes. Work runs inside Fusion CX operations certified to ISO/IEC 27001:2022, SOC 2 Type II, HITRUST CSF and PCI DSS 4.0.1, with HIPAA-compliant workflows and role-based access. We work only with client-provided data and never resell datasets.
#### Can you work in our annotation tool?
Yes. We work in your in-house or commercial annotation platform, or provide established tools if you do not have one, and deliver in the export formats your training pipeline expects.
#### What is the difference between data annotation services and data annotation outsourcing?
Data annotation services can be anything from a one-off labeling project to a long-running program. Data annotation outsourcing usually means handing the whole labeling operation to a dedicated external team over the long term. Annotera supports both; see our [data annotation outsourcing services](/okf/page/data-annotation-outsourcing.md) for the managed model.
## Our BlogsInsights from the
World of Data Annotation
[More Blogs ](/okf/page/blog.md)
- November 13, 2026
### [BIO, IOB2, and CoNLL Explained: Text Annotation Formats for NLP](/okf/article/bio-iob2-conll-nlp-annotation-formats.md)
- November 12, 2026
### [Image Annotation Tools Compared: Open-Source vs. Commercial vs. Managed Services](/okf/article/image-annotation-tools-comparison.md)
- November 11, 2026
### [Text Annotation Tools Compared: Label Studio, Prodigy, doccano, and Managed Services](/okf/article/text-annotation-tools-comparison.md)