Maintain Market Visibility
Observe selected products, listings, properties, jobs, publications, travel records, and public market signals.
Home / Services
Managed web data servicesWeb Data Services Built for Real Business Decisions
Collect, structure, validate, enrich, and continuously deliver eligible web and application data through a managed pipeline designed around your business requirements.
✓Custom data schemas✓Managed infrastructure✓Documented validation✓Flexible delivery
Source to deliveryOne managed workflow
Custom by defaultFields, schema, cadence, output
Quality controlledProject-defined validation rules
Integration readyFiles, APIs, cloud, databases
Maintenance includedMonitoring and source-change response
Start with the requirement
What kind of data workflow do you need?
Choose the closest starting point. Kvetoiq can combine services when a project needs collection, analysis, monitoring, and delivery together.
Collect from websites
Managed Extraction
Collect selected fields from eligible websites and receive normalized, validated records.
Start with Web Scraping →Crawl at enterprise scaleBroad Source Coverage
Crawl large, complex, or recurring source sets with monitoring and maintenance.
Start with Enterprise Crawling →Integrate into softwareProgrammatic Collection
Request rendered or structured web data from an application or internal pipeline.
Start with the Scraping API →Keep data freshRefresh & Change Detection
Collect on demand, refresh on schedule, or act when selected fields change.
Start with Live Crawlers →Eight connected services
Everything required to turn public web data into a dependable business input.
Each service solves a defined part of the data lifecycle and links to a dedicated page with deeper technical and use-case detail.
01 / COLLECTION
Web Scraping Services
Managed extraction of selected data from eligible websites, with normalization, validation, automation, and structured delivery.
- Custom fields and schemas
- Recurring or one-time workflows
- Documented quality controls
Enterprise Web Crawling
Large-scale recurring collection across complex source sets, deep site structures, dynamic pages, and multi-market environments.
- Distributed crawl architecture
- Source and pipeline monitoring
- Maintenance for structural changes
Web Scraping API
Programmatic access to eligible rendered pages or structured fields for software products, internal applications, and data workflows.
- Request and response workflows
- Synchronous or asynchronous jobs
- Structured JSON delivery
AI-Powered Scraping
Adaptive extraction, matching, classification, enrichment, sentiment, and computer-vision capabilities for complex content.
- LLM-assisted extraction
- Product and entity matching
- Custom AI enrichment
Live Crawler Services
On-demand, scheduled, and meaningful-change collection for workflows where timing affects the decision.
- Freshness timestamps
- Field-level change rules
- Webhook and alert delivery
Custom Data Extraction
Purpose-built extraction around unique sources, schemas, transformations, business rules, and delivery requirements.
- Multi-source datasets
- Custom validation logic
- Business-system integration
AI Training Data Services
Traceable, model-specific datasets for machine learning, LLM fine-tuning, evaluation, retrieval, and updated AI systems.
- Dataset specification and lineage
- Training, validation, and test splits
- Versioned refresh pipelines
App Scraping - Android & iOS
Structured collection from eligible public Android and iOS application sources when equivalent web data is incomplete or unavailable.
- Public mobile application data
- Custom app-specific schemas
- Scheduled structured delivery
Compare services
Choose the right starting point for your data requirement.
The final architecture may combine several services, but each project should begin with its primary operational need.
| Your requirement | Recommended service | Best suited for |
|---|---|---|
| Managed website data extraction | Web Scraping Services | Structured fields, recurring datasets, managed delivery |
| Large or complex source coverage | Enterprise Web Crawling | Broad crawling, scale, monitoring, maintenance |
| Application-level data requests | Web Scraping API | Software products, internal tools, programmatic access |
| Adaptive extraction and enrichment | AI-Powered Scraping | Unstructured content, matching, classification, analysis |
| Fresh or change-triggered records | Live Crawler Services | On-demand collection, refreshes, alerts, monitoring |
| Unique fields and business rules | Custom Data Extraction | Specialized schemas, transformations, integrations |
| Model-ready datasets | AI Training Data Services | ML, LLM, RAG, evaluation, dataset versioning |
| Eligible mobile application data | App Scraping | Android and iOS public application sources |
One connected data lifecycleMap Your Data Workflow →
More than extraction. A managed path from source to action.
Kvetoiq connects discovery, collection, quality, enrichment, delivery, and maintenance so your team can work with the resulting data-not manage crawler operations.
✓Preserve source and observation context.
✓Normalize records into the approved schema.
✓Validate data before downstream delivery.
✓Monitor failures, changes, and freshness.
01Discover sourcesCoverage + feasibility
02Collect dataCrawl + render + retrieve
03Extract and normalizeSchema + types + entities
04Validate and enrichQA + matching + classification
05Deliver and integrateFiles + API + cloud + database
06Monitor and refreshFreshness + changes + maintenance
Business outcomes
Turn web data into an operational advantage.
The value comes from what your team can decide, automate, monitor, or build with the delivered records.
Automate Manual Research
Replace repetitive browsing and spreadsheet collection with a structured, repeatable data workflow.
Feed Internal Applications
Deliver validated records into software, databases, analytics systems, and operational tools.
Improve Data Quality
Normalize fields, control duplicates, validate necessary values, and document known limitations.
Build AI-Ready Datasets
Prepare traceable records for matching, classification, retrieval, evaluation, and machine learning.
Detect Meaningful Changes
Identify relevant updates and route validated events into the workflows that need them.
Business solutions
Combine services around a measurable commercial workflow.
A solution may bring together crawling, matching, validation, change detection, enrichment, and delivery.
Price Monitoring
Track selected prices, promotions, sellers, availability, and historical changes across relevant sources.
Explore solution →MAP Violation Alerts
Detect potential advertised-price exceptions and create evidence-backed review queues.
Explore solution →Digital Shelf Analytics
Measure availability, assortment, content, ratings, visibility, and seller conditions.
Explore solution →Share of Search
Observe selected search positions, presence, competitors, and category visibility.
Explore solution →Product Matching
Connect exact, similar, and variant products across retailers and marketplaces.
Explore solution →Brand Protection
Monitor selected listings, sellers, content, pricing signals, and public marketplace evidence.
Explore solution →Top global platforms
Explore managed data scraping services for leading marketplaces.
Move from the service you need to the exact platform you want to monitor. Every platform page covers available fields, business use cases, delivery options, and related KVETOIQ solutions.
Amazon Data Scraping
Products, sellers, prices, reviews, rankings, and availability.
Explore Amazon data →Walmart Data Scraping
Products, stores, offers, pickup, delivery, and inventory.
Explore Walmart data →Shopify Store Scraping
Catalogs, collections, variants, stock, and merchant data.
Explore Shopify data →TikTok Shop Scraping
Products, shops, sellers, creators, engagement, and trends.
Explore TikTok Shop data →Flipkart Data Scraping
Listings, sellers, pricing, reviews, ratings, and availability.
Explore Flipkart data →eBay Data Scraping
Listings, auctions, sellers, pricing, condition, and shipping.
Explore eBay data →Etsy Data Scraping
Products, shops, prices, reviews, variations, and search position.
Explore Etsy data →Best Buy Data Scraping
Electronics, specifications, prices, offers, and stock status.
Explore Best Buy data →Wayfair Data Scraping
Furniture, variants, pricing, reviews, and availability.
Explore Wayfair data →Alibaba Data Scraping
Products, suppliers, minimum orders, pricing, and trade details.
Explore Alibaba data →AliExpress Data Scraping
Products, stores, prices, shipping, reviews, and promotions.
Explore AliExpress data →Wish Data Scraping
Listings, merchants, discounts, ratings, and delivery data.
Explore Wish data →Newegg Data Scraping
Technology products, specifications, sellers, prices, and stock.
Explore Newegg data →Industry coverage
Web data services shaped around each market’s sources and decisions.
Industry requirements differ in source behavior, entities, fields, freshness, quality rules, and downstream use.
E-commerce & Retail
Products, sellers, prices, content, reviews, availability, and digital shelves.
Explore industry →Grocery & FMCG
Assortment, pack sizes, promotions, delivery availability, and local market signals.
Explore industry →Travel & Hospitality
Properties, rates, routes, schedules, amenities, reviews, and availability.
Explore industry →Food & Restaurants
Menus, locations, items, promotions, reviews, and delivery-market records.
Explore industry →Finance & Legal
Public filings, notices, publications, market events, and company and market data.
Explore industry →Healthcare & Pharma
Eligible public product, trial, publication, provider, and research records.
Explore industry →Real Estate & Local
Listings, properties, agents, amenities, locations, prices, and status changes.
Explore industry →Automotive & Mobility
Vehicles, listings, rentals, routes, parts, availability, and mobility signals.
Explore industry →Media & Entertainment
Titles, catalogs, releases, rankings, engagement, reviews, and public metadata.
Explore industry →Quick Commerce
Rapid-delivery products, local assortments, pricing, offers, and availability.
Explore industry →Emerging Industries
Custom public-source datasets for AI, SaaS, research, and new digital markets.
Explore industry →How Kvetoiq works01 02 03 04 05
Validate the requirement before scaling the pipeline.
A focused process aligns the data, engineering, quality, and delivery expectations early.
Define Requirements
Confirm sources, fields, volume, cadence, purpose, and destination.
Validate Sources
Assess representative targets, availability, behavior, and feasibility.
Design Pipeline
Build collection, schema, normalization, validation, and delivery.
Review Sample
Confirm record structure, exceptions, quality rules, and output.
Launch & Maintain
Monitor production, manage source changes, and refresh as required.
Quality and observability
See whether the pipeline is running-and whether the data is usable.
Operational monitoring and data validation should work together rather than treating a successful request as proof of a correct record.
Schema Validation
Check required fields, types, formats, allowed values, and record relationships.
Duplicate Controls
Identify exact and near-duplicate records using defined business rules.
Volume Monitoring
Compare record counts and distributions to expected source behavior.
Source Timestamps
Record when selected sources were observed and data was extracted.
Failure Alerts
Surface access, rendering, parsing, validation, and delivery exceptions.
Documented Outputs
Provide schema notes, validation context, and known limitations where required.
Delivery and integration
Receive structured data where work already happens.
Choose a delivery method that fits the receiving application, data volume, refresh pattern, and operational workflow.
CSVExcelJSONJSONLParquetAPIWebhookCloud StorageDatabaseData WarehouseCustom Integration
Responsible data collection
Scope the sources, fields, controls, and intended use before launch.
Kvetoiq assesses public-source availability, necessary fields, source conditions, proportional request controls, privacy considerations, retention, and delivery requirements. Project-specific legal questions should be reviewed by qualified counsel.
Review Privacy Policy →✓Public-source and feasibility assessment
✓Necessary-field and purpose limitation
✓Source-aware request controls
✓Privacy, retention, and delivery requirements
✓Documented assumptions and limitations
✓Project-specific review where appropriate
Frequently asked questions
What teams ask about Kvetoiq’s web data services.
What are web data services?
Web data services cover the collection, extraction, normalization, validation, enrichment, delivery, monitoring, and maintenance required to turn eligible web or application sources into structured business data.
Which Kvetoiq service should I choose?
Choose Web Scraping Services for managed extraction, Enterprise Web Crawling for broad source coverage, the Web Scraping API for programmatic access, Live Crawler Services for freshness, AI-Powered Scraping for adaptive extraction, Custom Data Extraction for unique workflows, AI Training Data for model-ready datasets, or App Scraping for eligible mobile sources.
What is the difference between web scraping and web crawling?
Crawling discovers or traverses pages and source structures. Scraping extracts selected information from the retrieved content. Many managed projects use both capabilities together.
When should I use a web scraping API?
An API is appropriate when an application or internal system needs to request rendered content or structured fields programmatically instead of receiving only scheduled batch files.
What is a live crawler?
A live crawler collects fresh data on request, at an agreed interval, or when selected fields and business conditions change. The appropriate freshness model depends on the source and use case.
Can Kvetoiq build a completely custom data pipeline?
Yes. Custom projects can define sources, fields, schemas, transformations, validation rules, cadence, alert behavior, and delivery integrations.
Can you collect data from JavaScript-rendered websites?
Many eligible dynamic websites can be assessed for browser-based rendering before extraction. Feasibility depends on the specific source and required workflow.
Can you collect eligible mobile-application data?
Yes. Kvetoiq can assess eligible public Android and iOS application sources when the required data is available through an appropriate technical workflow.
Can Kvetoiq prepare data for AI and machine learning?
Yes. Services can support collection, normalization, enrichment, matching, classification, lineage, dataset splitting, validation, and versioned delivery for defined AI workloads.
How do you validate extracted data?
Validation may include schema, type, format, required-field, duplicate, relationship, record-count, distribution, and business-rule checks agreed for the project.
Can you maintain a pipeline when a source changes?
Managed workflows can monitor extraction behavior, missing fields, volume changes, rendering failures, and delivery errors so structural source changes can be investigated and addressed.
How frequently can data be refreshed?
Refresh cadence depends on source behavior, complexity, volume, rendering, validation, intended use, and responsible request controls. It is confirmed during feasibility testing.
Which output formats are supported?
Common options include CSV, Excel, JSON, JSONL, and Parquet, with delivery through files, APIs, webhooks, cloud storage, databases, warehouses, or custom integrations.
Can data be delivered directly to our cloud environment?
Yes. Eligible workflows can deliver to agreed cloud storage, database, or data-platform destinations using customer-approved access and security arrangements.
Can we review sample records before production?
In many cases, a representative sample can confirm source coverage, fields, schema, quality rules, exceptions, and delivery format before the workflow is scaled.
What information is needed to scope a project?
Helpful inputs include target sources, required fields, example outputs, expected volume, refresh requirements, geographic or language coverage, quality rules, and delivery destination.
How does Kvetoiq approach responsible web data collection?
Kvetoiq scopes public sources, necessary fields, source conditions, request controls, privacy considerations, retention, intended use, and delivery requirements. Qualified counsel should review project-specific legal questions.
Can Kvetoiq support multiple sources and schemas?
Yes. Multi-source workflows can normalize different source structures into a shared schema or maintain source-specific outputs where the business requirement demands it.
Start with the requirement
Not sure which data service fits your workflow?
Share your target sources, fields, expected volume, refresh requirements, and delivery destination. Kvetoiq will recommend a practical service architecture and the best place to begin.