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Octoparse builds, runs, and maintains custom web datasets for AI training, price intelligence, market monitoring, and B2B data operations— delivered to Snowflake, BigQuery, AWS S3, API, JSONL, Parquet, or CSV.
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Two vendors before Octoparse - both times we ended up cleaning the data ourselves. With Octoparse the sample came back in four days, fields exactly as spec'd. Eight months in, two or three issues total, all resolved within a day.
Two other providers told us Xiaohongshu was "technically challenging." Octoparse had a working sample in four days. Coverage is not 100% - nothing is - but they are upfront about gaps instead of just delivering junk.
Before we signed, they sent back detailed questions and a draft field schema. Most vendors just send a pricing sheet. In a compliance environment, that diligence matters more than any pitch. Six months in, still running.
Most vendors fall apart at month three - source changes, nobody picks up the phone. Octoparse has a dedicated contact and a Slack channel. Half the time they flag an issue before I've even noticed it.
2,000+ SKUs across 50 competitor sites, clean feed every morning. Last quarter we caught a competitor's flash sale and matched it within the hour. That one catch probably paid for the whole year.
From e-commerce price intelligence to AI training data - explore the specialized service that matches your use case.
Real-time competitor pricing, stock levels, and promotion data - including hard-source e-commerce pipelines such as Temu with 8M+ monthly records, QA, and warehouse-ready delivery.
Match products across retailers and marketplaces using managed crawling, normalized product data, multi-signal validation, AI-assisted visual matching, public case studies, and workflow datasets.
Custom prospect databases built to your ICP - company profiles, decision-maker contacts, funding signals, and hiring patterns. Delivered clean, deduplicated, and CRM-ready.
Brand, campaign, and competitor intelligence from TikTok, Weibo, Xiaohongshu, Douyin, X, LinkedIn, and 60+ platforms - including the APAC sources that mainstream tools can't reach.
Domain-specific training corpora, RAG knowledge base feeds, and AI agent data pipelines - deduplicated, provenance-tagged, and delivered in JSONL, Parquet, or directly to your warehouse.
One managed team turns public web sources into production-ready data feeds, warehouse integrations, and AI-ready datasets your business can use immediately.
A dedicated Octoparse data team scopes, builds, monitors, and repairs the scraping workflow so your internal engineers are not maintaining brittle Python or Scrapy pipelines.
Production-ready data is delivered into the systems enterprise buyers already use, including automated web data feeds to Snowflake, Google BigQuery, AWS S3, APIs, webhooks, and databases.
For AI and ML teams, Octoparse turns public web sources into deduplicated, provenance-tagged datasets for LLM fine-tuning, RAG, AI agents, product enrichment, and market intelligence.
Choosing between a managed data pipeline and an in-house scraper is a make-or-break infrastructure decision. Our guide breaks down the real costs, hidden risks, and long-term trade-offs — so you commit to the right model.
Public-safe sample datasets connect the Data Service hub to service pages, case studies, Hugging Face, and Kaggle so buyers and AI systems can inspect payload shape, fields, and workflow context.
Public-safe pricing workflow sample for SKU, price, seller, inventory, and monitoring cadence validation.
skuproduct_urlpricesellerstock_statuscaptured_atCandidate match workflow dataset for product identity resolution, visual similarity, and review decision fields.
source_product_idcandidate_product_idsimilarity_scorematch_statusreject_reasonreview_noteCross-retailer product matching workflow preview for normalized attributes, match decisions, and QA review.
retailertitlebrandmodelnormalized_attributesverified_matchBrand monitoring sample for public social signals, campaign mentions, creator context, and content-level metadata.
platformbrandcreatorpost_urlengagement_signalcaptured_atHere's why it keeps breaking - and what it's actually costing you.
IPs get blocked, CAPTCHAs rotate, JS fingerprinting evolves. Every update breaks your scraper. Your team spends more time fixing than analyzing.
Building a production-grade scraper stack from scratch costs 40-120 engineer hours. By the time it's live, your competitor has already made their pricing move.
Missing fields, inconsistent formats, duplicates. Teams spend 60-80% of project time preparing data before any analysis can start.
In-house scraping means your most expensive talent is keeping scrapers alive instead of building products that move the needle.
Free sample data in 1-2 business days. Typical production delivery in 3 business days to 2 weeks, depending on scope.
You share your goals, target sources, and delivery format. We define scope, feasibility, and timeline - together.
e.g. "Daily pricing from 80 competitor ASINs -> Snowflake, masked before delivery."Your dedicated data engineer designs the extraction, cleaning, and delivery workflow - tailored to your infrastructure.
We execute, run QA, and deliver. You review and approve - or we adjust at no charge until it matches your spec.
Layout change detection, self-healing pipelines, anomaly alerts, and monthly optimization reviews - so you never have to think about it.
Not just another data scraping vendor. An end-to-end data operations team - yours.
We cover all major global platforms. Where we truly stand apart: deep, native expertise in APAC - Weibo, Xiaohongshu, Douyin, LINE, Lazada, Tokopedia - collecting 1M+ posts daily from platforms most providers can't reliably access.
Standardized pipeline templates and pre-built connectors help you validate quickly with a free sample in 1-2 business days. Typical production delivery ranges from 3 business days to 2 weeks depending on scope - not months.
Accuracy, availability, and response time SLAs written into your contract - with free rework or refund if we miss them. Accountability, not marketing language.
Field coverage, duplication rates, anomaly detection - every delivery comes with a sampling QA report so you can see exactly what you are getting.
API, S3, BigQuery, Snowflake, MySQL, Postgres, Webhook, email download - data lands exactly where your team expects it, on schedule.
From 10,000 to 50M+ records per day. We've scaled to enterprise-grade volumes with priority queues and autoscaling - without you touching a config file.
Octoparse Managed Web Data Service vs. common alternatives - so you can evaluate delivery model, speed, and ownership clearly
| Capability | Octoparse | Typical Data API Vendor | Freelance / Agency | In-House Build |
|---|---|---|---|---|
| Full-service managed pipeline | End-to-end | Infrastructure only | Project-based, limited scope | You own everything |
| Global + APAC social platform coverage | Deep native expertise | Global platforms only | Varies by vendor | Significant engineering effort |
| SLA guaranteed in contract | All plans | Enterprise tiers only | Inconsistent | No external guarantee |
| Typical production delivery | 3 business days to 2 weeks | Setup varies by use case | Weeks to months | 6-12 weeks minimum |
| Entry-level cost | From $699/project | Varies, often volume-based | Project rate + ongoing fees | $5,000-$50,000+ to build |
| Ongoing pipeline maintenance | Fully included | Your team manages it | Usually additional cost | Your team, indefinitely |
No hidden fees. Sample data first - you only commit when you're satisfied.
Answer two or three questions - we'll show you the real cost of your current setup and what you stand to gain.
Perfect for market research, competitive benchmarking, or a one-time dataset. Full pipeline, delivered and done.
For teams who need fresh, continuously updated data. We run, monitor, and self-heal your pipeline - every day.
For large-scale, mission-critical data operations. Dedicated team, private infrastructure, custom SLAs.
"We were worried about the upfront cost, but the ROI was obvious within the first month. We cancelled two Fiverr contracts and freed up 15 hours of our analyst's time per week."— Data Lead, Global CPG Company · Ongoing monitoring customer since 2023
We scope it, build it, and deliver a free sample before you commit to anything.
"We evaluated three vendors. Octoparse was the only team that came back with a concrete pipeline design and sample data before we even signed. That's when we knew."— Tariq Al-Hassan, VP of Data Engineering · Series B FinTech · Enterprise customer