OUR SERVICES

The people and processes behind better AI data.

We help AI teams move from a clear project brief to organized, human-reviewed datasets through coordinated recruitment, training, execution, quality assurance and delivery.

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PeopleLocal expertise

DataReal-world signals

QualityHuman reviewed

ScaleGlobal delivery

END-TO-END SERVICES

From project brief to delivery-ready dataset.

We can support individual stages or coordinate an end-to-end workflow, depending on project scope, task complexity and acceptance requirements.

01 / DESIGN

Project design & task planning

Translate the use case into task instructions, contributor profiles, technical specifications, sampling plans and acceptance criteria.

02 / PEOPLE

Recruitment & onboarding

Source, screen and onboard participants, native speakers, annotators and field teams against project requirements.

03 / ENABLEMENT

Training & calibration

Provide examples, task guidance, device checks, practice rounds and reviewer calibration before scaled execution.

04 / EXECUTION

Collection & annotation

Coordinate voice, text, image, video, egocentric, robotics and other data tasks with ongoing operational support.

05 / QUALITY

Human-in-the-loop QA

Use automated checks where appropriate alongside human review, issue tagging, feedback and correction loops.

06 / DELIVERY

Packaging & reporting

Organize approved outputs, track completion and provide delivery status aligned to the agreed project plan.

HOW WE WORK

Hire. Train. Execute. Review. Complete.

A clear operating sequence keeps contributors supported and makes quality visible throughout the project.

Hire the right people

Match language, location, environment, skill and equipment needs.

Train for the task

Explain instructions, demonstrate examples and confirm readiness.

Get the work done

Run collection or annotation with operational monitoring and support.

Human review

Check quality, flag issues and provide actionable feedback.

Complete the project

Resolve open issues, package accepted data and report completion.

HUMAN IN THE LOOP

Quality moves in a loop — not a straight line.

Review findings feed back into training, instructions and execution. That continuous feedback helps teams correct issues early and protect consistency through delivery.

Collect → check → coach → correct → validate → deliver.

SERVICE FAMILY 01 / MULTILINGUAL AI

Language data services across text, audio, image and video.

Build, refine and evaluate multilingual datasets with native-language contributors, trained annotators and human review workflows.

Data collection

Text corpora, prompts, responses, speech recordings, conversational data, image datasets and video content.

Data annotation

Classification, entity and intent tagging, sentiment, speaker labels, timestamps, captions, visual labels and event tags.

Transcription

Audio and video transcription, verbatim or clean-read formats, speaker diarization and timestamping where required.

Translation & localization

Translation, transliteration, locale adaptation, terminology alignment and cultural-context review.

Proofreading

Spelling, grammar, fluency, consistency, formatting, terminology and meaning-preservation checks.

Model evaluation

Human evaluation of model responses for relevance, helpfulness, instruction following, factuality, safety and language quality.

Content evaluation

Text, audio, image and video review for accuracy, relevance, completeness, quality and project-defined content standards.

Quality assurance

Guideline adherence, annotation audits, sampling, reviewer calibration, error categorization and corrective feedback.

SERVICE FAMILY 02 / PHYSICAL AI

Real-world data for robotics and embodied AI.

Support perception, action understanding and physical task learning with structured collection, annotation, evaluation and quality operations.

Egocentric data collection

First-person, head-mounted and body-worn recordings of task-based human activity in approved environments.

Robotics data collection

Human demonstrations, robot interactions, manipulation tasks, navigation scenarios and task execution recordings.

Egocentric data annotation

Action segmentation, task steps, hand-object interaction, object state, temporal events and scene context.

Object & scene annotation

Detection, classification, tracking, bounding boxes, polygons, segmentation and spatial relationships.

Activity & motion annotation

Human action recognition, gestures, pose and movement labels, task sequences and activity boundaries.

Multimodal QA & curation

Video and image validation, metadata checks, sensor-linked sequence checks where supplied, dataset organization and delivery QA.

MODALITY COVERAGE

Services mapped to the data type.

Text

Collection • Annotation • Transcription of text from media • Translation • Proofreading • Model and content evaluation • QA.

Audio

Speech collection • Transcription • Translation • Speaker and segment annotation • Audio content evaluation • QA.

Image

Image collection • Captioning • Classification • OCR • Object annotation • Content evaluation • Visual QA.

Video

Video collection • Transcription • Subtitle review • Scene and action annotation • Temporal labels • Content evaluation • QA.

Physical AI programs may also include task-specific spatial, motion or sensor-linked data workflows when the required data and technical specifications are part of the project scope.

REGIONAL DELIVERY

LATAM. APAC. EMEA.

Both Multilingual AI and Physical AI programs can be scoped for these regions, subject to country-level feasibility, contributor availability, language requirements, environment access and project specifications.

LATAM

Language and locale programs, native-speaker recruitment, commercial and residential capture environments, annotation and QA.

APAC

Multilingual and multimodal data programs, egocentric collection, robotics-related workflows, annotation and regional coordination.

EMEA

European, Middle Eastern and African language programs, real-world data collection, annotation, evaluation and quality operations.

NEXT STEP

Let’s build better AI data together.

Tell us what you are building and where human data can help.

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