Must-Have Company Location Data APIs for 2026

September 15, 2026
Must-Have Company Location Data APIs for 2026

Classify company websites and pin down where those companies are located—right when it matters

Your product team needs to decide whether to accept a new business signup, your ad-ops team wants to verify that inventory aligns with your geo-targeted campaigns, and your data engineering team is racing to enrich millions of domains with organization and location metadata for accurate routing and analytics. In all these cases, a single, reliable source that both classifies a website and returns company location data is essential. That’s exactly the gap a domain intelligence API must fill—and where Klazify delivers comprehensive website categorization alongside business details such as city, state, and country.

This article shows how to classify websites and extract company location data using the Klazify API. We’ll walk through realistic use cases (like lead routing or brand safety), practical guidance for plugging the API response into your pipeline, a complete JSON example, and best practices for accuracy, caching, and taxonomy mapping.

Why Klazify is the best fit for company location data and website classification

When your workflows depend on knowing what a website is about and where its owning company is located, accuracy, coverage, and freshness are non-negotiable. Klazify was designed for this: it analyzes content across the site and returns industry-standard categories, while also extracting key company attributes including location data from the URL. Here’s why this combination excels for company location data APIs in 2026:

  • Accurate website categorization using AI: Klazify analyzes full website content, not just metadata. This enables precise, niche identification (for example, differentiating between local B2B distributors versus multinational SaaS providers) and ensures the category context you use to gate signups, assign sales territories, or audit ad placements is trustworthy.
  • Global coverage: Many businesses operate across regions and languages. Klazify’s approach is built to analyze websites globally, which is crucial when you’re enriching a database spanning multiple countries and need consistent location signals like city, stateCode, and countryCode.
  • Real-time classification: Rather than depending on static or outdated datasets, Klazify emphasizes up-to-date content analysis. That means geographies and industries associated with a domain reflect what’s on the site now—vital when territories change or a company opens new offices.
  • Industry-level categories using IAB taxonomy: You get IAB taxonomy mapping to line up with standard ad-tech and brand safety practices. This allows you to easily pair location data with recognized industry categories for campaign targeting, content filtering, and compliance workflows.
  • Simple API integration: A developer-friendly REST endpoint provides website classification, company information retrieval (including location), logo URL extraction, and domain signals from a single call—shortening implementation time and reducing moving parts in your enrichment pipelines.
  • Superior compliance and filtering: Strong categorization paired with business and location context supports precise filtering—such as whitelisting companies by region and vertical, segmenting outreach by territory, and enforcing content policies by country.

What you can build with company location data and website classification

1) Enrich signups in real time

When a user signs up with a corporate email or domain, you can instantly classify their website and retrieve company location. This powers:

  • Sales routing: Assign leads to the right regional team using city, stateCode, and countryCode.
  • Risk scoring: Combine IAB categories with location to decide if a signup meets your compliance criteria (e.g., blocking risky categories or restricted geos).
  • Personalized onboarding: Tailor onboarding steps or resources by region and industry category.

2) Brand safety and ad placement auditing

Use IAB-aligned categories and company location data to ensure your ads appear on appropriate sites. Validate whether a site’s content category and the company’s home country match your brand’s safety and regulatory requirements for each campaign territory.

3) Content filtering and compliance

Map content categories to your internal policies and factor in company location to comply with geo-specific regulations. This is especially relevant for finance, healthcare, or government-related filtering where location can determine policy enforcement.

4) CRM and lead enrichment at scale

Bulk-enrich a domain list with categories, logo URLs, and location information. Enriched fields—like city, stateCode, and countryCode—enable better segmentation, territory analysis, and faster attribution across your data warehouse or CDP.

5) Cybersecurity triage

Complement reputation and threat detection workflows by combining content context with organizational location, increasing the reliability of automated allow/block decisions and incident response enrichment.

How the Klazify API works for company location data and classification

Klazify’s main endpoint is purpose-built for website classification and content categorization, with additional company and domain signals returned in a single response:

  • Endpoint: https://www.klazify.com/api/categorize
  • Purpose: Website classification and content categorization, with company information retrieval (including location data), logo URL extraction, domain registration data, technology detection, and similar domains in the same call.

From a single request to this endpoint, you can obtain:

  • Website classification: Hierarchical categories and IAB mapping.
  • Company information: Including name, city, stateCode, countryCode, employeesRange, and revenue.
  • Logo URL: Useful for UI/UX and data visualization.
  • Domain registration data: Age and expiration, valuable for risk analysis.
  • Similar domains: Helpful for clustering and competitor intelligence.

Example request (curl)

The following demonstrates a direct call to the classification endpoint:

curl -X POST "https://www.klazify.com/api/categorize"

In your integration, send the target URL or domain to this endpoint and parse the JSON response to extract categories and company location attributes. You’ll operationalize those fields in your enrichment logic, routing rules, and analytics layers as shown in later sections.

Example response and fields to extract

Below is a complete, realistic example you can use for parsing logic, data modeling, and testing.


{
    "domain": {
        "categories": [
            {
                "confidence": 0.92,
                "name": "/Computers & Electronics/Consumer Electronics",
                "IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
            },
            {
                "confidence": 0.89,
                "name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
            }
        ],
        "social_media": null,
        "logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
    },
    "success": true,
    "objects": {
        "company": {
            "url": "https://www.apple.com/",
            "name": "Apple",
            "city": "Cupertino",
            "stateCode": "CA",
            "countryCode": "US",
            "employeesRange": "100K+",
            "revenue": 274515000000,
            "raised": null,
            "tags": [
                "E-commerce",
                "Consumer Electronics",
                "Mobile",
                "B2C"
            ],
            "tech": [
                "omniture_adobe_analytics",
                "atlassian_confluence",
                "successfactors",
                "apache_apex",
                "talend",
                "oracle_peoplesoft",
                "salesforce",
                "stripe",
                "dell_boomi_atomsphere",
                "gigya",
                "sage_50cloud",
                "quickbooks",
                "webmethods",
                "apache_tomcat",
                "alteryx",
                "tibco_rendezvous",
                "atlassian_jira",
                "..."
            ]
        }
    },
    "domain_registration_data": {
        "domain_age_date": "1987-02-19",
        "domain_age_days_ago": "13026",
        "domain_expiration_date": "2030-02-20",
        "domain_expiration_days_left": "123"
    },
    "similar_domains": [
        "bestbuy.com",
        "icloud.com",
        "microsoft.com",
        "macrumors.com",
        "google.com",
        "samsung.com",
        "twitter.com",
        "hp.com",
        "bhphotovideo.com",
        "dell.com"
    ]
}

How to interpret the data for location-centric workflows

  • objects.company.city / stateCode / countryCode: The key location attributes used for territory routing, geo-based personalization, and compliance checks.
  • domain.categories[].name and optional IAB-632-596 mapping: Content categories used for classification, contextual targeting, and brand safety policies.
  • domain.logo_url: A direct logo URL for UI enrichment and reporting dashboards.
  • domain_registration_data: Use domain age for additional trust signals or prioritization.
  • similar_domains: Expand research, competitor analysis, or clustering logic.

Technical approach: mapping and operationalizing company location + classification

Data model planning

Plan for a normalized store of company location data and categories for each domain. This typically includes:

  • domain (string, unique key)
  • company_name (string)
  • city (string)
  • state_code (string)
  • country_code (string)
  • categories (array of strings)
  • iab_mappings (array of strings, where available)
  • logo_url (string)
  • domain_age_date, domain_expiration_date (dates)
  • similar_domains (array of strings)

Field-to-field mapping for enrichment

Klazify field Suggested column Usage
objects.company.city city Lead routing, territory dashboards, geo-based personalization
objects.company.stateCode state_code Regional sales ownership, compliance checks
objects.company.countryCode country_code Geo policies, segmentation, global analytics
objects.company.name company_name CRM identity, reporting
domain.categories[].name categories Classification, targeting, brand safety
domain.categories[].IAB-632-596 iab_mappings IAB-aligned workflows for ad-tech pipelines
domain.logo_url logo_url UI enrichment, dashboards
domain_registration_data.* domain_age_date, domain_expiration_date Risk scoring, priority rules
similar_domains similar_domains Research, clustering, competitor analysis

Minimal parsing example (JavaScript)

The snippet below demonstrates how to parse the response to extract company location and categories. In practice, insert your network call and handle the response JSON accordingly in your pipeline or application layer.

const responseJson = {
  "domain": {
    "categories": [
      {
        "confidence": 0.92,
        "name": "/Computers & Electronics/Consumer Electronics",
        "IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
      },
      {
        "confidence": 0.89,
        "name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
      }
    ],
    "social_media": null,
    "logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
  },
  "success": true,
  "objects": {
    "company": {
      "url": "https://www.apple.com/",
      "name": "Apple",
      "city": "Cupertino",
      "stateCode": "CA",
      "countryCode": "US",
      "employeesRange": "100K+",
      "revenue": 274515000000,
      "raised": null,
      "tags": ["E-commerce","Consumer Electronics","Mobile","B2C"],
      "tech": ["omniture_adobe_analytics","atlassian_confluence","..."]
    }
  },
  "domain_registration_data": {
    "domain_age_date": "1987-02-19",
    "domain_age_days_ago": "13026",
    "domain_expiration_date": "2030-02-20",
    "domain_expiration_days_left": "123"
  },
  "similar_domains": ["bestbuy.com","icloud.com","microsoft.com","dell.com"]
};

function extractEnrichment(data) {
  const company = data.objects && data.objects.company ? data.objects.company : {};
  const categories = (data.domain && data.domain.categories) ? data.domain.categories.map(c => c.name) : [];
  const iab = (data.domain && data.domain.categories) ? data.domain.categories
    .filter(c => c["IAB-632-596"])
    .map(c => c["IAB-632-596"]) : [];

  return {
    company_name: company.name || null,
    city: company.city || null,
    state_code: company.stateCode || null,
    country_code: company.countryCode || null,
    categories,
    iab_mappings: iab,
    logo_url: data.domain && data.domain.logo_url ? data.domain.logo_url : null,
    domain_age_date: data.domain_registration_data ? data.domain_registration_data.domain_age_date : null,
    domain_expiration_date: data.domain_registration_data ? data.domain_registration_data.domain_expiration_date : null,
    similar_domains: data.similar_domains || []
  };
}

console.log(extractEnrichment(responseJson));

Real-world applications for location-aware classification

Signup enrichment and lead routing

As soon as a user submits a domain, enrich it with company location for territory mapping and assign the lead to the right regional queue. Pair this with IAB categories to further refine routing (e.g., send “Consumer Electronics” companies in “US” to a specialized team).

Ad-tech: contextual targeting with geographic governance

Validate whether a publisher’s content category aligns with IAB segments you bid on while confirming the associated company’s country for compliance. Use domain age and similar domains to add extra context to supply path optimization and publisher vetting.

Content filtering and policy enforcement

Map Klazify categories to your internal policy groups and apply geo-overrides using company location. For example, a category may be acceptable in one region but require additional review in another.

Analytics and segmentation

Warehouse enrichment boosts analytics: slice performance by country, category, or both. Analyze market penetration, technology adoption patterns (from tech signals), and competitive positioning (from similar domains) with greater accuracy.

Implementation best practices

1) Caching and TTL strategy

  • Per-domain caching: Store results keyed by domain, including categories and company location fields. Many domains won’t change frequently.
  • TTL per signal group: Consider longer TTLs for company location and shorter TTLs for fast-changing content categories if your use case demands recency.
  • Conditional refresh: Reclassify domains that drive significant traffic or revenue more often to ensure you capture content shifts and organizational updates.

2) Batch processing and concurrency

  • Batch enrichment windows: For large domain lists, run nightly or hourly enrichment jobs and persist normalized results to your data lake or warehouse.
  • Pipeline parallelism: Leverage worker pools and queue-based architectures to scale throughput safely and predictably.
  • Backpressure controls: Implement retry with exponential backoff and circuit breakers to maintain stability during spikes.

3) Schema evolution

  • Versioned models: Keep your enrichment table versioned. If you expand fields (e.g., add additional tags or new IAB mappings), you can reprocess without breaking downstream systems.
  • Null-safe parsing: Some fields may be absent or null (e.g., social_media); design your parsers defensively and maintain sensible defaults.

4) Handling unknown or new domains

  • Quarantine queue: If a domain returns sparse data, queue it for reprocessing after a delay and flag for manual review only if it remains unresolved.
  • Progressive enhancement: Start with available fields (e.g., categories) and gradually add company data when it becomes available.

5) Mapping Klazify categories to your taxonomy

  • IAB-first approach: Use the IAB mapping when present to anchor your internal taxonomy. Store both Klazify’s category path and the IAB string for traceability.
  • Category normalization: Build a lookup table that translates category paths into your standardized segments (e.g., “B2B-Tech”, “Retail-Consumer Electronics”). Keep this table editable and audited.
  • Confidence-aware rules: The category object includes confidence. Make threshold-based decisions (e.g., require higher confidence for automated blocking, lower for gentle personalization).

6) Observability and data quality

  • Drift detection: Monitor changes in category distributions and top locations over time to detect anomalies (e.g., sudden shift in top countries for new signups).
  • Validation checks: Assert invariants such as “countryCode must be two-letter format” or “stateCode only populated for certain countries.”
  • Feedback loops: If end users flag misclassifications, feed corrections into a review process to refine mapping rules.

The Klazify data in context: aligning categories and company location

Klazify’s combination of website classification and company information retrieval from a URL makes it particularly effective for cross-functional use cases. The same response powers your:

  • Sales systems with location-based assignment and lead scoring.
  • Marketing and ad-tech tools with IAB-aligned contextual targeting and brand safety checks.
  • Security stack with richer signals for allow/block logic and incident enrichment.
  • Analytics platforms with better segmentation, reporting visuals (logo_url), and trend analysis.

Operational example: intake → enrichment → action

  1. Intake: Your signup service or data pipeline receives a domain.
  2. Enrichment: Call the Klazify categorize endpoint and persist the returned categories, company location, and logo URL.
  3. Decisioning: Apply routing rules using countryCode/stateCode; enforce content/category policies; store enriched fields for observability.
  4. Feedback: Log outcomes and iterate on thresholds, mappings, and reprocessing intervals.

Deep dive: using the returned fields effectively

Location attributes for territory logic

  • countryCode drives macro routing; pair with stateCode for fine-grained regional assignments (e.g., US state-level territories).
  • city offers local nuance for account matching, especially useful in ABM and proximity-based strategies.

Categories and IAB mapping for compliance and targeting

  • domain.categories[].name provides a hierarchical path, enabling parent/child policy application.
  • IAB-632-596 mapping standardizes your categorization for ad-tech integrations and brand safety tooling.

Domain registration and logo for auxiliary decisions

  • domain_age_date can be a signal of domain maturity; pair with revenue and employeesRange for prioritization.
  • logo_url improves trust in UI and facilitates faster analyst review in internal tools.

Security, privacy, and governance considerations

When integrating any enrichment API into your systems, adopt a governance-first mindset:

  • Minimize data movement: Store only the fields you need for your workflows, especially if you operate across jurisdictions with varying data regulations.
  • Access control: Restrict who can call the categorize endpoint and who can read enriched datasets—particularly location and revenue fields.
  • Auditable pipelines: Keep a log of classification results, mapping versions, and decision thresholds used at the time of action.

End-to-end validation and QA

Benchmarking your mapping strategy

  • Representative samples: Test across geographies, industries, and company sizes. Confirm routing accuracy and policy adherence with real cases.
  • Gold sets: Maintain a small, high-confidence set of domains with verified locations and categories to validate your pipeline after changes.
  • Error analysis: Investigate where categories or location fields don’t align with internal expectations and refine mapping or thresholds accordingly.

Development workflow and documentation

For a smooth integration experience, explore the documentation and ensure your team aligns on the fields you will consume and how you’ll store them. Implement a staging pipeline to test end-to-end behavior with real domains before pushing to production. For more details, refer to the Klazify API documentation: Check out the full Klazify API documentation.

Putting it together: architecture, UX, and data modeling

Suggested architecture for real-time and batch enrichment

  • Real-time: Invoke the categorize endpoint during signup or domain submission, write results to a low-latency store, and route leads immediately.
  • Batch: Periodically re-enrich high-value segments (e.g., top accounts, high-traffic publishers) and backfill analytics tables in your warehouse.

Keep both flows aligned by using a shared library for parsing and normalization of the Klazify response.

Designing for analysts and operators

  • Readable category paths: Render human-friendly category paths with IAB references to speed up internal reviews.
  • Logo display: Use the logo URL in CRM records and dashboards to reduce ambiguity and accelerate manual triage.
  • Explainability: Persist confidence scores where available to support explainable actions (e.g., why a lead was routed to a particular team).

Sample UI and data-flow visuals

Architecture diagram for company location enrichment with Klazify

Mapping Klazify fields to your data model

IAB taxonomy mapping visual for location-focused workflows

Use-case playbooks

Playbook 1: Territory routing for sales ops

  1. Receive domain during lead capture.
  2. Call categorize endpoint; parse company.city, stateCode, countryCode.
  3. Map to territory; assign owner; log action and enrichment snapshot.
  4. Trigger onboarding tailored to region and category (e.g., localized resources).

Playbook 2: Ad placement and brand safety checks

  1. Classify publisher domains and retrieve company countryCode.
  2. Verify domain.categories against allowed IAB-aligned categories.
  3. Apply geo policies based on countryCode; flag mismatches for review.
  4. Store enrichment for reporting: approved/blocked by category and location.

Playbook 3: Content filtering for networks and apps

  1. Classify all requested domains in-line or via a policy service.
  2. Map category paths to internal policy groups; apply country-based exceptions.
  3. Return allow/block decisions with rationale; persist for analytics.
  4. Periodically re-enrich frequently accessed or newly seen domains.

Working with the JSON effectively

Checklist for robust consumers

  • Handle nested structures (domain.categories, objects.company).
  • Treat unknown or null fields safely (e.g., social_media).
  • Support multiple categories per domain and store all relevant paths.
  • Retain both free-form category paths and IAB mappings to future-proof taxonomy shifts.

Normalization tips

  • Lowercase and trim domains consistently to avoid duplicates.
  • Normalize countryCode and stateCode to your standard references.
  • Hash or key by domain for fast read/write access in caches.

Future trends: company location data + classification in 2026

More granular territories

Expect finer-grained regional signals to play a bigger role in routing and compliance. Storing and operationalizing stateCode and city fields positions you well for increasingly precise territory logic.

Context-aware personalization

Combining IAB-aligned categories with location will power dynamic experiences, from onboarding flows to in-app messaging localized by region and industry vertical.

Unified decisioning layers

Teams will consolidate enrichment (classification, location, tech stack, revenue) into a single decision fabric for sales, marketing, and security policies. Klazify’s multi-signal response aligns with this trend, simplifying architecture.

Putting Klazify into practice quickly

Quick start steps

  • Integrate a simple worker or middleware calling the categorize endpoint.
  • Parse company location and categories; store normalized fields.
  • Apply routing and policy rules; log outcomes.
  • Iterate on confidence thresholds and mapping tables.

Environment readiness

  • Set up a secure secrets store for API access credentials.
  • Prepare dev/staging environments for safe testing with real domains.
  • Instrument logging to trace enrichment requests and decisions.

Python parsing example for analytics pipelines

Use this minimal Python snippet to parse the JSON response and prepare fields for your warehouse. Replace the inline data with your actual API call and response handling in production pipelines.

import json

data = json.loads(r'''
{
    "domain": {
        "categories": [
            {
                "confidence": 0.92,
                "name": "/Computers & Electronics/Consumer Electronics",
                "IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
            },
            {
                "confidence": 0.89,
                "name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
            }
        ],
        "social_media": null,
        "logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
    },
    "success": true,
    "objects": {
        "company": {
            "url": "https://www.apple.com/",
            "name": "Apple",
            "city": "Cupertino",
            "stateCode": "CA",
            "countryCode": "US",
            "employeesRange": "100K+",
            "revenue": 274515000000,
            "raised": null,
            "tags": [
                "E-commerce",
                "Consumer Electronics",
                "Mobile",
                "B2C"
            ],
            "tech": [
                "omniture_adobe_analytics",
                "atlassian_confluence",
                "successfactors",
                "apache_apex",
                "talend",
                "oracle_peoplesoft",
                "salesforce",
                "stripe",
                "dell_boomi_atomsphere",
                "gigya",
                "sage_50cloud",
                "quickbooks",
                "webmethods",
                "apache_tomcat",
                "alteryx",
                "tibco_rendezvous",
                "atlassian_jira",
                "..."
            ]
        }
    },
    "domain_registration_data": {
        "domain_age_date": "1987-02-19",
        "domain_age_days_ago": "13026",
        "domain_expiration_date": "2030-02-20",
        "domain_expiration_days_left": "123"
    },
    "similar_domains": [
        "bestbuy.com",
        "icloud.com",
        "microsoft.com",
        "macrumors.com",
        "google.com",
        "samsung.com",
        "twitter.com",
        "hp.com",
        "bhphotovideo.com",
        "dell.com"
    ]
}
''')

company = data.get("objects", {}).get("company", {})
domain = data.get("domain", {})
reg = data.get("domain_registration_data", {})

record = {
    "company_name": company.get("name"),
    "city": company.get("city"),
    "state_code": company.get("stateCode"),
    "country_code": company.get("countryCode"),
    "categories": [c.get("name") for c in domain.get("categories", [])],
    "iab_mappings": [c.get("IAB-632-596") for c in domain.get("categories", []) if "IAB-632-596" in c],
    "logo_url": domain.get("logo_url"),
    "domain_age_date": reg.get("domain_age_date"),
    "domain_expiration_date": reg.get("domain_expiration_date"),
    "similar_domains": data.get("similar_domains", [])
}

print(record)

Benefits of accurate company location and website classification

  • Higher conversion: Route leads correctly and present localized onboarding to reduce friction.
  • Reduced risk: Prevent policy violations by pairing IAB-aligned classification with location-aware rules.
  • Operational clarity: Unify data across sales, marketing, and security teams with a single source of truth.
  • Scalability: One endpoint enriches with categories, company information (including location), and domain signals—fewer moving parts to maintain.

From concept to production: a concise path

  1. Define objectives: e.g., “Route by countryCode; block certain categories by IAB mapping.”
  2. Set up ingestion: Capture domains from signups, forms, or partner feeds.
  3. Call Klazify categorize: Parse categories, location, and logo.
  4. Normalize and persist: Store in a shared enrichment model with versioned mappings.
  5. Apply decisions: Route, block, or personalize; log everything.
  6. Monitor and iterate: Tune thresholds, mappings, and refresh cadence.

FAQ

How does Klazify help classify websites while also returning company location data?

Klazify’s categorize endpoint analyzes website content to produce hierarchical categories mapped to the IAB taxonomy, while also returning company details like city, stateCode, and countryCode—all from a single request. This dual output powers both contextual classification and geo-aware decisioning.

Which fields should I use for territory routing?

Use objects.company.city, objects.company.stateCode, and objects.company.countryCode. Combine these with domain.categories and IAB mappings to refine assignment logic by both geography and vertical.

How can I align Klazify categories with our internal taxonomy?

Store both the category path (domain.categories[].name) and the IAB mapping when present. Maintain a lookup table that translates these values to your internal segments. Keep the table versioned and confidence-aware to support explainable decisions.

What if some fields are null or missing?

Design for null-safe parsing. For instance, social_media may be null, or IAB mapping may not appear for every category. Implement defaults and reprocessing strategies when critical fields are missing.

Can I combine company size or revenue with location for prioritization?

Yes. The company object includes employeesRange and revenue. Use these alongside location to prioritize leads or accounts in key markets and to enhance segmentation in analytics.

How often should I refresh enriched data?

Use a caching and TTL strategy aligned to your needs. Company location typically changes infrequently, while content categories may change more often. Adopt conditional refresh for high-impact domains and scheduled re-enrichment for bulk datasets.

How do I visualize results for analysts?

Leverage the logo_url field and render readable category paths with IAB references. Present location, category, and confidence data together so analysts can quickly validate routing and policy outcomes.

Get started with the all-in-one domain intelligence platform that unifies website classification and company location data. Create an account on the official site at Klazify and start enriching your workflows today.

For more technical guidance and endpoint details, visit Check out the full Klazify API documentation. When you’re ready to integrate, set up a test environment, parse the response fields highlighted above, and plug them into your routing, targeting, and analytics layers with confidence.

Ready to classify websites and enrich company location data at scale? Visit the official site at Klazify and take the next step.

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