We collect large-scale datasets for training and fine-tuning models — text, images, video, audio, and structured records. Everything is gathered from open sources for your task, cleaned and preprocessed, and delivered in ML-ready formats.
Teams that need large, clean datasets for model training — when collecting and preparing them in-house is slow and expensive.
Track competitor prices, assortment, and stock, populate product listings, and enforce MSRP.
Build datasets on markets, prices, and demand for reports, models, and well-grounded decisions.
Receive data as a stream or via API without running your own scraping infrastructure, proxies, and maintenance.
Find companies and contacts, and track ads, reviews, and brand mentions across the web.
Monitor competitor prices and rankings, new products in your niches, and demand dynamics across platforms.
Populate catalogs, price comparison sites, and listings with data from dozens or hundreds of sources.
Three formats to fit the task: a one-time dataset, recurring data delivery, or a custom solution. We calculate the exact cost for your sources, volume, and frequency — with an estimate before we start.
Collect and prepare a dataset once — for training or research.
The dataset refreshes on a schedule and grows with fresh data.
Turnkey data as a service: API access, DaaS, or a ready-made interface, dozens of sources, and an SLA.
The total comes down to a few clear factors. No hidden fees — we send an estimate and a data sample before work begins.
Describe the data type, volume, and processing requirements — we'll come back with a cost estimate, timeline, and a dataset sample within one business day.
The quality of an AI/ML model depends directly on the data it's trained on. We collect large-scale datasets for your task — training, fine-tuning, or validating models — and deliver them clean, structured, and ready to load into your pipeline.
We collect data in any modality: text and documents, images, video and audio, tabular data and time series. We bring records to a unified shape, remove duplicates and noise, and verify completeness and class balance.
When needed, we run extra preprocessing: normalization, deduplication, labels and tags, bounding boxes, audio transcription, question–answer pairs, and metadata. Delivery comes in ML-friendly formats: JSONL, CSV, Parquet, media archives, or API access.
You don't need your own collection infrastructure, proxies, or a labeling team. We take on the entire pipeline — from collection to quality control — and, when needed, keep the dataset growing with fresh data on a regular schedule.
We collect only publicly available data, respect source licenses and restrictions, and never handle personal data in circumvention of the law. When needed, we anonymize and filter sensitive content. We work under contract.
We've been collecting data for e-commerce and analytics since 2015 — and we know a dataset is only valuable when it's large, clean, and correctly labeled.
Text, images, video, audio, tables, and time series — collected to fit your task.
Our own collection infrastructure and proxies: millions of records and terabytes of media on sensible timelines.
Deduplication, noise filtering, class balance, and validation — data you can trust.
Cleaning, deduplication, normalization, and a unified schema tailored to your task.
JSONL, CSV, Parquet, media archives, or API access — whatever suits your pipeline.
Public sources, license compliance, and anonymization of sensitive content.
A transparent process: we prepare an estimate and send a data sample before work begins. No hidden fees, no surprises.
You send a link to the source and the list of fields you need. A short task description is enough.
We scout the source, estimate cost and timeline, and send a data sample in your target format.
We configure collection, build an interface to your requirements or issue API access, and agree on update frequency.
You work in the interface or via API. We maintain the service, refresh the data, and watch quality.
The output is a training-ready dataset: clean, labeled, and in an ML-friendly format.
A structured set — JSONL, CSV, or Parquet matching your schema.
Images, video, and audio with metadata and an index.
Plug the dataset straight into your training pipeline — no manual exports.
Cleaning, deduplication, normalization, and a unified schema tailored to your task.
Deduplication, noise filtering, class balance, and data validation.
We keep the dataset growing with new data and hold quality steady.
Data delivery is part of a larger data operation. We'll assemble and configure the right track for your task.
Daily dynamics of competitor prices and assortment.
Enforcement of recommended prices across platforms.
Reviews and ratings for reputation management and analytics.
The largest top-100 marketplaces and other platforms.
If you don't see the answer you need — send a request, and we'll reply within one business day.
Text and documents, images, video and audio, tabular data and time series, question–answer pairs. We build the dataset around your training task: a single modality or a mixed corpus.
Base pricing starts at $150. The final price depends on the number of sources, data volume, update frequency, protection complexity, and extra processing. We send an exact estimate and a data sample before work begins.
JSONL, CSV, Parquet, media archives (images, video, audio) with an index and metadata, or API access. We fit the field schema to your pipeline.
Maintaining and adapting collection is our responsibility and is included in the plan. We watch quality and restore the data promptly when sources change — the interface and API keep working.