AI Data

Collect new data, source raw datasets, or annotate data you already own. Build structured datasets for model training, search relevance, recommendation systems, and LLM evaluation.

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Data Collection

Collect new image, video, audio, and text data against your task spec. Define the geography, contributor profile, device requirements, environment, volume, and output format. Receive data structured to your schema and ready for annotation, training, or evaluation.

POV & Egocentric Datasets

First-person image and video captured from wearable, mobile, or mounted devices. Build datasets for robotics, computer vision, navigation, activity recognition, and human-object interaction across defined environments, actions, and contributor profiles.

Off-the-Shelf Datasets

Start with data that already exists. Use raw, licensed, off-the-shelf, or client-owned datasets as your base. We clean, filter, deduplicate, structure, and enrich them against your model requirements, schema, and quality thresholds, ready for your training or evaluation workflow.

Multimodal Data Labeling

Annotate image, video, audio, and text against your task spec. Bounding boxes, segmentation, keypoints, event tagging, transcription, classification, NER, and sentiment. Works on data we collect, your raw files, or off-the-shelf datasets. Output structured to your schema, ready for training or evaluation.

Search & Relevance

Side-by-side ranking, NDCG relevancy, and query intent tagging. Contributors evaluate result quality against your defined relevance criteria, capturing the judgments that train and benchmark ranking models. Built for search, recommendation, and retrieval systems.

RLHF / Preference

Preference ranking, safety evaluation, and tone and accuracy grading for LLMs. We capture human judgment on model outputs against your rubric, the feedback signal that shapes model behavior. Scales from small preference sets to large ongoing alignment pipelines.

Why Acquirox

The managed layer AI teams are missing

Fully managed, from data spec to delivery
Define the dataset requirements, contributor profile, capture conditions, annotation rubric, quality thresholds, and output format. Acquirox handles collection, preparation, labeling, validation, QA, and delivery. Your team scopes the project once and receives structured, model-ready data.


Works with your existing stack
Use your current storage, labeling environment, and delivery workflow. Acquirox supports Label Studio, V7, CVAT, and proprietary annotation environments, with output in JSON, CSV, COCO, XML, or Parquet. No platform migration required.

 

Verified contributor network
Every collection submission and annotation task is completed by a verified contributor. Hardware fingerprinting, task-level checks, contributor performance history, and QA controls reduce bot activity, duplicate submissions, and inconsistent output.

 

Elastic collection and labeling capacity
Adjust volume as dataset requirements change. Run a targeted collection project, an ongoing annotation pipeline, or bursts of up to 1M+ tasks without building a fixed workforce or restarting contributor recruitment.

How we work

From first brief to model-ready data in three steps — validated on a pilot before full delivery.

1. Brief

Define the dataset requirements, contributor profile, capture conditions, annotation spec, quality thresholds, volume, and output format.

2. Pilot

Run a small-scale collection, preparation, or labeling batch to validate instructions, contributor fit, and output quality before scaling.

3. Scale & Delivery

Scale collection or annotation to the required volume. Final QA is completed before delivery in your preferred format or direct export to your pipeline.

Your data team has better things to do

Acquirox handles data collection, dataset preparation, labeling, QA, and delivery — so your engineers stay focused on model development.

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FAQ

Custom data collection, POV and egocentric datasets, off-the-shelf and raw dataset preparation, multimodal labeling, search and relevance, and RLHF and preference work. You define the task, we handle contributor deployment, QA, and delivery, and return structured output to your schema.
Both. We collect new data to spec, and we prepare, structure, or enrich datasets you already hold. Labeling runs on data we collect, your raw files, or off-the-shelf sets — so collection and annotation come from one vendor.
Verified human contributors from a network of 18M+ across 150+ countries, concentrated in Asia, Latin America, and Africa. Every contributor is verified and every item is checked before it reaches you. Tasks are scoped to what a distributed network handles reliably — no bots, no synthetic data.
Human in the loop on every batch. 2-3 contributors cross-check each item, automated integrity checks run before review, and senior Acquirox reviewers set the golden standard on flagged and edge-case items. Quality holds as volume scales.
Real. Every item is produced by a verified contributor, not scraped, automated, or generated. The provenance of every item is documented and traceable — which keeps you clear of the copyright and quality risks that come with public web data.
Yes. We clean, filter, deduplicate, structure, and enrich raw, licensed, off-the-shelf, or client-owned datasets against your schema. This is the faster path when you already hold data but need it standardized, labeled, or brought to your quality threshold.
Bounding boxes, segmentation, keypoints, and event tagging for image and video; transcription and diarization for audio; classification, NER, sentiment, and summarization for text. What we take on depends on the required annotation level and contributor capability — higher levels are scoped case by case.
Yes. Preference ranking, safety evaluation, tone and accuracy grading, side-by-side ranking, and query intent tagging. Contributors assess outputs against your rubric, producing structured human feedback for search, recommendation, retrieval, and LLM alignment.
Defined upfront. Project-based or exclusive licensing, with documented provenance and contributor consent, agreed before work begins.
JSON, CSV, COCO, XML, or Parquet, via API push or direct export. Output is matched to your pipeline, so the dataset arrives ready to use without reformatting on your end.
Priced per hour of data, with the rate reflecting exclusivity, technical requirements, capture device, and complexity. No seat licenses, no retainers — we return a scope-based quote against your brief.

Where verified human action meets measurable output

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