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About Kvetoiq

We Build the Data Layer Behind Better Decisions

Founded in August 2021, Kvetoiq helps companies collect, structure, validate, and transform publicly available web data into intelligence their teams can use with confidence.

USA-focused partnerships Enterprise-ready delivery Responsible data practices
The Kvetoiq journeyBuilt for durable data operations
Founded August 2021

From web extraction projects to decision-ready data systems.

Kvetoiq began with a practical belief: collecting web data only creates value when that data is accurate, structured, explainable, and connected to a real business decision.

2021FoundationCustom web data collection and extraction.
BuildData OperationsValidation, normalization, QA, and delivery.
ExpandIntelligencePricing, shelf, seller, and market use cases.
TodayAI-Ready DataStructured pipelines for enterprise and AI teams.
2021Founded
200+Clients Served
45+Markets Covered
250M+Records Processed
120+Platforms Mapped
98.7%QA Benchmark
Our story

The problem was never access to more data. It was trust in what came next.

Businesses can find information across thousands of websites, marketplaces, apps, directories, and public sources. The difficult work is turning that changing information into consistent records that can support pricing, research, operations, artificial intelligence, and strategic decisions.

Kvetoiq was founded in August 2021 to solve that operational gap. We started by building custom extraction programs around the exact sources, fields, formats, and schedules businesses needed. The work quickly extended beyond collection into validation, normalization, product matching, pipeline monitoring, and ongoing source maintenance.

Today, Kvetoiq operates at the intersection of web data collection and business intelligence. We build the underlying data systems, then help teams apply that data to commercial problems such as price monitoring, digital shelf measurement, brand protection, product matching, market research, and AI training.

We do not believe a scraping engagement is successful simply because a file was delivered. The real test is whether the data is reliable enough, clear enough, and timely enough to support the decision it was collected for.

Our operating belief

If a dataset cannot be understood, validated, maintained, and used by the people receiving it, collection alone has not solved the business problem.

Our direction

A clear mission today. A larger vision for what web data can enable.

01

Vision

To become a trusted global leader in responsible web data infrastructure, enabling organizations to unlock the full potential of publicly available information for better decisions, stronger products, and meaningful innovation.

Where we are going
02

Mission

To help businesses collect, organize, validate, and transform public web data into dependable business intelligence through secure, scalable, and AI-assisted solutions, with a consistent commitment to responsible collection, data quality, innovation, and customer success.

What we work toward every day
How Kvetoiq creates value

One company. Two connected layers.

Kvetoiq combines the infrastructure required to collect dependable data with the intelligence models required to use it.

The data layer

Collection and Data Engineering

We build and maintain the pipelines that transform changing public sources into structured, validated, and deliverable datasets.

Web Scraping ServicesCustom managed extraction
Enterprise CrawlingLarge-source collection programs
Web Scraping APIProgrammatic web data access
App ScrapingEligible Android and iOS data
AI Training DataStructured datasets for AI systems
Custom ExtractionPurpose-built schemas and delivery
Explore Web Scraping Services →
The intelligence layer

Commercial Data Solutions

We connect collected data to defined business questions, decisions, controls, and measurable operating workflows.

Price MonitoringCompetitive price intelligence
MAP Violation AlertsPolicy monitoring and evidence
Digital Shelf AnalyticsContent, availability, and visibility
Share of SearchOrganic and sponsored presence
Product MatchingCross-source product identity
Brand ProtectionSeller and marketplace risk signals
Explore Data Solutions →
What we bring together

The capabilities required to keep web data useful after launch.

The difficult part of web data is not the first extraction. It is maintaining accuracy, context, delivery, and continuity as sources change.

01 Collect

Source Discovery and Extraction

Map relevant public sources, access paths, fields, schedules, locations, and collection constraints.

Websites, marketplaces, apps, directories, and public sources
02 Structure

Normalization and Schema Design

Transform inconsistent source information into stable fields, types, taxonomies, units, and records.

Custom schemas built around downstream use
03 Validate

Quality Assurance and Evidence

Apply completeness, format, duplication, consistency, reconciliation, and source-context checks.

Reviewable QA rather than hidden accuracy claims
04 Connect

Matching and Entity Resolution

Link products, sellers, locations, businesses, and other entities across changing source systems.

Confidence, reasons, conflicts, and review controls
05 Deliver

Flexible Data Integration

Send usable outputs through files, APIs, webhooks, cloud storage, databases, or data warehouses.

Delivery designed for the receiving team
06 Maintain

Monitoring and Source Change Management

Observe pipeline health, source changes, schema drift, missing fields, and delivery continuity.

Ongoing operations instead of one-time extraction
How we work

Start with the decision. Design the data operation backward from it.

Our process begins by understanding what the data must support, not by forcing a generic crawler or dataset into the project.

Every engagement is scoped around source feasibility, eligible public data, quality requirements, operating cadence, downstream users, and maintenance expectations.
01
Define the business requirementClarify the decision, workflow, users, risks, and success criteria.
02
Map sources and schemaIdentify eligible sources, fields, entities, locations, relationships, and formats.
03
Build and validate a sampleTest extraction, normalization, QA, matching, and output usefulness.
04
Launch the production pipelineConfigure scheduling, routing, monitoring, delivery, and operational controls.
05
Maintain and improveRespond to source changes, quality findings, coverage needs, and evolving use cases.
What guides our work

Principles that matter after the sales call.

Reliable data programs are built through disciplined operating choices, not vague promises.

01
QUALITY

Data Quality Before Volume

More records do not create more value when the schema, identity, context, or validation is unreliable.

Completeness, consistency, traceability, and usefulness
02
ETHICS

Responsible Collection

We design programs around eligible public information, defined business purposes, proportional collection, and appropriate safeguards.

Scope, purpose, access, privacy, and governance
03
CLEAR

Explainable Operations

Teams should understand where data came from, how it was processed, what was inferred, and what requires review.

Source context, rules, reasons, conflicts, and status
04
BUILD

Engineering for Change

Web sources evolve. We design pipelines, validation, monitoring, and delivery with change management in mind.

Maintainability, observability, and controlled updates
05
USE

Business Usefulness

Data must fit the systems, decisions, cadence, vocabulary, and accountability of the people using it.

Outputs shaped by downstream work
06
PARTNER

Customer Success

We treat the long-term reliability and usefulness of the data operation as part of the engagement.

Clear communication, practical support, and improvement
Who we work with

Built for teams whose decisions depend on external data.

Kvetoiq supports organizations ranging from growing digital businesses to enterprise teams operating complex data and intelligence programs.

Enterprise CompaniesLarge-scale, governed data operations
Ecommerce BrandsPricing, shelf, seller, and channel intelligence
Retailers and ManufacturersCompetitive and market visibility
SaaS and Data ProductsReliable external data pipelines
AI CompaniesTraining, enrichment, grounding, and evaluation data
Research and Investment TeamsStructured market and alternative data
Agencies and ConsultantsClient-ready data and intelligence operations
Data and Analytics TeamsFiles, APIs, cloud, warehouse, and BI delivery
Responsible web data

Publicly available does not mean responsibility disappears.

Kvetoiq approaches web data projects through defined purpose, source eligibility, proportional collection, appropriate access practices, privacy awareness, data minimization, security, and clear customer responsibilities. Technical feasibility alone is not the only project consideration.

Defined business purpose and documented scope
Public-source eligibility and access review
Data minimization and field-level justification
Appropriate storage, transfer, and access controls
Clear distinction between observations and inferences
What clients value

Built to support the teams responsible for using the data.

The strongest data partnerships are measured by clarity, reliability, responsiveness, and whether the output improves real work.

Michael Carter, Ecommerce Brand client
Michael CarterEcommerce Brand
Client review★★★★★
“Kvetoiq helped us streamline competitor monitoring with reliable, well-structured ecommerce data. Their solution has become an important part of our pricing strategy.”
Verified client feedback
Sarah Mitchell, Retail Company client
Sarah MitchellRetail Company
Client review★★★★★
“The quality and consistency of the data exceeded our expectations. Their team understood our requirements and delivered a solution tailored to our business.”
Verified client feedback
Daniel Foster, Manufacturing Business client
Daniel FosterManufacturing Business
Client review★★★★★
“Working with Kvetoiq gave us better visibility into marketplace trends and competitor activity. The insights have improved our decision-making process.”
Verified client feedback
Emily Roberts, Market Research Firm client
Emily RobertsMarket Research Firm
Client review★★★★★
“Their custom data delivery saved our team countless hours. We now receive accurate ecommerce data exactly how we need it.”
Verified client feedback
James Wilson, Business Intelligence Team client
James WilsonBusiness Intelligence Team
Client review★★★★★
“Kvetoiq provided a scalable solution that integrated seamlessly into our analytics workflow. The data quality has been consistently reliable.”
Verified client feedback
Company information

A focused data company built for long-term partnerships.

Company foundation

Founded in August 2021

Kvetoiq was established to help businesses turn fragmented public web information into structured, dependable, and useful data operations.

Contact Kvetoiq →
US focused, globally capable

Serving businesses across markets

The United States is our primary market, and our delivery model can also support enterprises, digital businesses, data teams, and technology companies operating across international markets.

Book a Strategy Call →
Build something useful with public web data

Tell us the decision your team needs to make.

We will help you determine the sources, fields, validation, delivery, and maintenance required to turn that question into a dependable data operation.

LET'S TALK

Tell us what market decision you need to make next.

Share the platforms, categories, competitors, SKUs, regions, or business questions you care about. KVETOiQ will help define the right data strategy, output format, and operating cadence.

  • Pricing and promotion monitoring
  • Marketplace and seller intelligence
  • Digital shelf and search visibility
  • Review sentiment and customer intelligence

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