{"id":1071,"date":"2025-12-29T13:14:56","date_gmt":"2025-12-29T13:14:56","guid":{"rendered":"https:\/\/pintel.ai\/blogs\/?p=1071"},"modified":"2026-03-27T04:16:26","modified_gmt":"2026-03-27T04:16:26","slug":"best-clay-alternatives-for-better-data-accuracy","status":"publish","type":"post","link":"https:\/\/pintel.ai\/blogs\/best-clay-alternatives-for-better-data-accuracy\/","title":{"rendered":"Clay Alternatives for Better Data Accuracy"},"content":{"rendered":"<div id=\"bsf_rt_marker\"><\/div>\n<p>If you\u2019re running outbound or managing GTM data, enrichment plays a critical role in how effectively your workflows perform. Clay is widely used for building flexible enrichment setups, but it may not always fit as teams scale and processes become more structured.<\/p>\n\n\n\n<p>You might be dealing with increasing complexity, inconsistent data outputs, or a tool that feels expensive.<\/p>\n\n\n\n<p>Whatever the reason, evaluating Clay alternatives becomes a practical next step.<\/p>\n\n\n\n<p>Choosing the right solution isn\u2019t just about adding more data. It\u2019s about finding a platform that delivers reliable outputs, fits your CRM, and supports your workflows without added overhead. The good news is there are strong alternatives, each taking a different approach to accuracy, automation, and usability.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/calendly.com\/aman-garg91\/30min?month=2025-12\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"282\" height=\"82\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/CTA-Button-3.png\" alt=\"\" class=\"wp-image-1073 lazyload\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 282px; --smush-placeholder-aspect-ratio: 282\/82;\" \/><\/a><\/figure>\n<\/div>\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"How_We_Evaluated_Clay_Alternatives\"><\/span>How We Evaluated Clay Alternatives<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Each solution in this guide was evaluated using the same operational criteria, grounded in real GTM workflows. When comparing tools like Clay, we focused on factors that matter once enrichment becomes a critical dependency:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Accuracy of persona, function, and seniority mapping<\/li>\n\n\n\n<li>Stability of enrichment outputs across multiple cycles<\/li>\n\n\n\n<li>Alignment with existing CRM schemas<\/li>\n\n\n\n<li>Reduction in manual SDR research<\/li>\n\n\n\n<li>Reliability when used for routing, scoring, and segmentation<\/li>\n\n\n\n<li><strong>Ease of use for business users without technical training<\/strong><\/li>\n\n\n\n<li><strong>Built-in quality assurance and confidence scoring<\/strong><\/li>\n<\/ul>\n\n\n\n<p>If a tool produces different outputs for the same input over time, it introduces downstream risk\u2014regardless of how powerful it appears on paper. Similarly, if a tool requires dedicated specialists and extensive training just to operate, it creates organizational dependencies that limit scalability.<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Quick_Comparison_Table_for_Top_Clay_Alternatives\"><\/span>Quick Comparison Table for Top Clay Alternatives<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>This table highlights how leading Clay alternatives differ in data accuracy, workflow complexity, and business user accessibility\u2014not just feature breadth. If you&#8217;re looking for tools like Clay that offer workflow-level enrichment, this comparison shows how they stack up operationally:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Tool<\/th><th>Core Focus<\/th><th>User Accessibility<\/th><th>Data Quality Controls<\/th><th>Workflow Automation<\/th><th>Best Fit<\/th><\/tr><\/thead><tbody><tr><td><strong>Pintel<\/strong><\/td><td>Deep workflows with specialized AI agents<\/td><td>High &#8211; Natural language interface<\/td><td>High &#8211; Built-in QA agent with confidence scoring<\/td><td>High &#8211; Auto-generated workflows + prompting agent<\/td><td>Teams needing accuracy without technical overhead<\/td><\/tr><tr><td><strong>Apollo<\/strong><\/td><td>Speed &amp; coverage<\/td><td>High &#8211; Simple interface<\/td><td>Low &#8211; Basic inference<\/td><td>Low &#8211; List building focus<\/td><td>Small teams (&lt;15 employees) needing basic enrichment<\/td><\/tr><tr><td><strong>Clearbit<\/strong><\/td><td>Firmographics<\/td><td>Medium &#8211; RevOps-friendly<\/td><td>Medium &#8211; Conservative approach<\/td><td>Low &#8211; Account-level only<\/td><td>Marketing ops teams focused on firmographics<\/td><\/tr><tr><td><strong>ZoomInfo<\/strong><\/td><td>Contact database with intent<\/td><td>Medium &#8211; Sales-oriented<\/td><td>Medium &#8211; Variable classification<\/td><td>Low &#8211; Pre-AI workflows<\/td><td>Intent-driven outbound teams<\/td><\/tr><tr><td><strong>Cognism<\/strong><\/td><td>Contact database for Europe<\/td><td>Medium &#8211; Sales-focused<\/td><td>Medium &#8211; Regional accuracy<\/td><td>Low &#8211; Contact enrichment focus<\/td><td>European market sales teams<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p><em>Note: This comparison is based on publicly available information, hands-on experience, and user reviews. It\u2019s meant as a high-level operational overview. For the most accurate and up-to-date details, contact the vendors directly.<\/em><\/p>\n\n\n\n<p><strong>What this means for RevOps teams:<\/strong> Most Clay alternatives fall into two categories\u2014simple contact databases (Apollo, ZoomInfo, Cognism) or account-level enrichment only (Clearbit). Only workflow-focused platforms like Pintel address the full operational stack: enrichment accuracy, quality assurance, and business-user accessibility.<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Pintel_%E2%80%94_GTM_Workflows_Designed_for_Business_Users_Not_Only_Engineers\"><\/span>Pintel \u2014 GTM Workflows Designed for Business Users, Not Only Engineers<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"449\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25-1024x449.png\" alt=\"Best Clay Alternatives for Better Data Accuracy\" class=\"wp-image-1075 lazyload\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25-1024x449.png 1024w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25-300x132.png 300w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25-768x337.png 768w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25-1536x674.png 1536w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-25.png 1600w\" data-sizes=\"(max-width: 1024px) 100vw, 1024px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1024px; --smush-placeholder-aspect-ratio: 1024\/449;\" \/><\/figure>\n\n\n\n<p><a href=\"https:\/\/pintel.ai\/\">Pintel<\/a> is built for teams that need GTM workflow-level automation but don&#8217;t want to manage the technical complexity that typically comes with it. Among Clay alternatives, Pintel focuses specifically on making it operable by business users rather than requiring dedicated technical resources. Instead of requiring users to design workflows manually, Pintel generates workflows based on natural language problem descriptions.<\/p>\n\n\n\n<p>The platform is structured around specialized workflows for <a href=\"https:\/\/pintel.ai\/blogs\/lead-enrichment-research-automation-fete-guide\/\">lead enrichment and research automation<\/a>, with separate logic for ICP filtering, <a href=\"https:\/\/pintel.ai\/solutions\/outbound-account-discovery\/\">account research<\/a>, and data quality checks rather than a single general-purpose process. This specialization improves accuracy while removing the need for users to write or optimize prompts themselves.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Why_Teams_Choose_Pintel_Over_Clay\"><\/span>Why Teams Choose Pintel Over Clay<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Teams typically prefer Pintel over Clay when:<\/p>\n\n\n\n<p><strong>Operational overheads seem unsustainable<\/strong><br>When we used Clay, we became the tool&#8217;s IT department\u2014training people on Clay University videos, troubleshooting workflows, and eventually hiring specialists. We spent hours mapping workflows that should have taken minutes to describe. Teams choose Pintel when they need enrichment operable by business users without dedicated technical resources.<\/p>\n\n\n\n<p><strong>They want Quality control<\/strong> <strong>at scale<\/strong><br>The breaking point for us: we had correct-looking data in the CRM, but SDRs still validated every record manually. Clay doesn&#8217;t include built-in QA, so every output needs review. We chose to build specialized agents\u2014separate ones for ICP filtering, account research, and quality assurance with confidence scoring (70-80%+ thresholds). This flags low-quality results automatically instead of requiring cell-by-cell validation.<\/p>\n\n\n\n<p><strong>Faster time-to-value matters along with customization depth<\/strong><br>Pintel inverts Clay&#8217;s model. Instead of mapping workflows and writing prompts, you describe the problem and get a recommended workflow. The upcoming prompting agent asks contextual questions and builds prompts automatically. Teams choose this when they want to solve prospecting problems, not become workflow engineers.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Core_Capabilities\"><\/span>Core Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Natural language workflow generation (describe problem \u2192 get workflow)<\/li>\n\n\n\n<li>Specialized AI agents: ICP filtering, account research, QA with confidence scoring<\/li>\n\n\n\n<li>Automatic flagging of low-confidence results with optimization suggestions<\/li>\n\n\n\n<li>Deterministic persona, function, and seniority classification<\/li>\n\n\n\n<li>Schema-aligned enrichment fields that fit existing CRM structures<\/li>\n\n\n\n<li>Waterfall enrichment across US, Europe, EMEA, APAC data providers<\/li>\n\n\n\n<li>Business-user interface requiring no technical training<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Apollo_%E2%80%94_Contact_Database_with_Basic_Enrichment\"><\/span>Apollo \u2014 Contact Database with Basic Enrichment<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"540\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26-1024x540.png\" alt=\"\" class=\"wp-image-1076 lazyload\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26-1024x540.png 1024w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26-300x158.png 300w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26-768x405.png 768w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26-1536x810.png 1536w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-26.png 1600w\" data-sizes=\"(max-width: 1024px) 100vw, 1024px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1024px; --smush-placeholder-aspect-ratio: 1024\/540;\" \/><\/figure>\n\n\n\n<p>Apollo is a contact database platform that includes list building, enrichment, and outbound execution features. Unlike tools like Clay that focus on workflow automation, Apollo is designed for speed\u2014teams can build lists and start outreach quickly without connecting multiple tools.<\/p>\n\n\n\n<p>Apollo works for small teams (typically under 15 employees) that need straightforward contact enrichment. Workflow capabilities are limited compared to platforms built specifically for complex enrichment tasks. Teams working on multi-step enrichment or custom research often need to export data and work in spreadsheets.<\/p>\n\n\n\n<p>Classification accuracy decreases as use cases become more specific. Seniority and function mapping uses broad inference, which can create noise in segmentation when roles don&#8217;t fit standard categories.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Core_Capabilities-2\"><\/span>Core Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Contact and account database<\/li>\n\n\n\n<li>List building and filtering<\/li>\n\n\n\n<li>Basic enrichment and seniority inference<\/li>\n\n\n\n<li>Native outbound sequencing<\/li>\n\n\n\n<li>CRM integrations<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"When_Apollo_Fits\"><\/span>When Apollo Fits<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Apollo makes sense for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Small teams with straightforward enrichment needs<\/li>\n\n\n\n<li>Teams prioritizing speed over quality<\/li>\n\n\n\n<li>Use cases focused on high-volume outreach rather than precise segmentation<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Clearbit_%E2%80%94_Firmographic_Enrichment_Only\"><\/span>Clearbit \u2014 Firmographic Enrichment Only<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"451\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27-1024x451.png\" alt=\"\" class=\"wp-image-1077 lazyload\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27-1024x451.png 1024w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27-300x132.png 300w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27-768x338.png 768w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27-1536x677.png 1536w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-27.png 1600w\" data-sizes=\"(max-width: 1024px) 100vw, 1024px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1024px; --smush-placeholder-aspect-ratio: 1024\/451;\" \/><\/figure>\n\n\n\n<p>Clearbit focuses on company-level data enrichment with an emphasis on accuracy and governance. It handles firmographic attributes\u2014company size, industry, location, funding\u2014reliably, which makes it useful for teams that need clean account-level data.<\/p>\n\n\n\n<p>Clearbit doesn&#8217;t support custom prospecting workflows or multi-step enrichment tasks. It&#8217;s designed for account enrichment, not contact-level research or complex data operations. Teams needing persona validation, responsibility mapping, or tailored account research need to use additional tools.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Core_Capabilities-3\"><\/span>Core Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Account-level firmographic enrichment<\/li>\n\n\n\n<li>Schema-aligned data appending<\/li>\n\n\n\n<li>CRM integration for automatic enrichment<\/li>\n\n\n\n<li>Focus on data accuracy and governance<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"When_Clearbit_Fits\"><\/span>When Clearbit Fits<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Clearbit makes sense for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Marketing ops and RevOps teams focused on firmographics<\/li>\n\n\n\n<li>Teams that need reliable account-level data<\/li>\n\n\n\n<li>Use cases where contact-level enrichment isn&#8217;t required<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><a href=\"https:\/\/calendly.com\/aman-garg91\/30min\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"704\" height=\"244\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-vs-Pintel-1.png\" alt=\"\" class=\"wp-image-1082 lazyload\" style=\"--smush-placeholder-width: 704px; --smush-placeholder-aspect-ratio: 704\/244;width:986px;height:auto\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-vs-Pintel-1.png 704w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-vs-Pintel-1-300x104.png 300w\" data-sizes=\"(max-width: 704px) 100vw, 704px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/a><\/figure>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"ZoomInfo_%E2%80%94_Contact_Database_with_Intent_Signals\"><\/span>ZoomInfo \u2014 Contact Database with Intent Signals<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"293\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28-1024x293.png\" alt=\"\" class=\"wp-image-1078 lazyload\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28-1024x293.png 1024w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28-300x86.png 300w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28-768x220.png 768w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28-1536x440.png 1536w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-28.png 1600w\" data-sizes=\"(max-width: 1024px) 100vw, 1024px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1024px; --smush-placeholder-aspect-ratio: 1024\/293;\" \/><\/figure>\n\n\n\n<p>ZoomInfo is a large B2B contact database with intent and technographic data. It&#8217;s commonly used by teams that prioritize database size and intent signals for targeting.<\/p>\n\n\n\n<p>Classification consistency varies. Seniority labels and function mapping can differ across industries and enrichment cycles, which requires ongoing RevOps oversight. Workflow automation features exist but are less developed than AI-native platforms\u2014ZoomInfo&#8217;s architecture reflects its database origins rather than workflow-first design.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Core_Capabilities-4\"><\/span>Core Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Large contact and account database (US market focus)<\/li>\n\n\n\n<li>Intent and technographic signals<\/li>\n\n\n\n<li>CRM and sales tool integrations<\/li>\n\n\n\n<li>Broad industry coverage<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"When_ZoomInfo_Fits\"><\/span>When ZoomInfo Fits<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>ZoomInfo makes sense for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Teams using intent signals for targeting<\/li>\n\n\n\n<li>Use cases requiring broad database coverage<\/li>\n\n\n\n<li>Organizations prioritizing data volume over workflow sophistication<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Cognism_%E2%80%94_EMEA-Focused_Contact_Enrichment\"><\/span>Cognism \u2014 EMEA-Focused Contact Enrichment<br><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1024\" height=\"584\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29-1024x584.png\" alt=\"\" class=\"wp-image-1079 lazyload\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29-1024x584.png 1024w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29-300x171.png 300w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29-768x438.png 768w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29-1536x876.png 1536w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/image-29.png 1600w\" data-sizes=\"(max-width: 1024px) 100vw, 1024px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 1024px; --smush-placeholder-aspect-ratio: 1024\/584;\" \/><\/figure>\n\n\n\n<p>Cognism is a contact enrichment platform focused on EMEA markets. It&#8217;s designed for teams that need regional data coverage with GDPR compliance built in.<\/p>\n\n\n\n<p>Workflow depth is limited compared to platforms designed for complex enrichment tasks. Cognism handles contact enrichment and prospecting but doesn&#8217;t support multi-step workflows or custom research operations.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Core_Capabilities-5\"><\/span>Core Capabilities<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>EMEA contact data coverage<\/li>\n\n\n\n<li>GDPR-compliant data handling<\/li>\n\n\n\n<li>Contact enrichment and prospecting<\/li>\n\n\n\n<li>Regional accuracy for European markets<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"When_Cognism_Fits\"><\/span>When Cognism Fits<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Cognism makes sense for:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Sales teams focused on EMEA markets<\/li>\n\n\n\n<li>Organizations requiring GDPR compliance<\/li>\n\n\n\n<li>Use cases centered on regional contact enrichment<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Data_Provider_Ecosystem_Marketplace_vs_Single-Vendor_Approach\"><\/span>Data Provider Ecosystem: Marketplace vs. Single-Vendor Approach<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>When evaluating Clay alternatives, one consideration is how the platform accesses data providers. Platforms like Pintel and Clay use a marketplace model that connects to multiple data providers. Single-vendor tools like Apollo, ZoomInfo, and Cognism rely on their own databases.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Single-Vendor_Limitations\"><\/span>Single-Vendor Limitations<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>When using single-vendor tools, coverage gaps require multiple contracts:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>2-3 contact enrichment tools for different regions<\/li>\n\n\n\n<li>Separate account research tools<\/li>\n\n\n\n<li>Minimum spend commitments per vendor<\/li>\n\n\n\n<li>Manual integration and vendor management<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Marketplace_Approach\"><\/span>Marketplace Approach<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Marketplace platforms\u2014tools like Clay and Pintel that aggregate multiple data sources\u2014offer:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Waterfall enrichment across multiple regional providers (US, Europe, EMEA, APAC)<\/li>\n\n\n\n<li>Usage-based pricing without minimum commitments<\/li>\n\n\n\n<li>Automatic integration of new data providers<\/li>\n\n\n\n<li>One contract instead of multiple vendor relationships<\/li>\n<\/ul>\n\n\n\n<p>This reduces vendor management overhead and provides access to regional data sources without maintaining separate tools.<\/p>\n\n\n\n<p>The operational difference: Pintel offers marketplace access through a business-user interface, while Clay requires technical resources to manage provider integration and workflow design.<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Factors_to_Consider_When_Choosing_the_Right_Solution\"><\/span>Factors to Consider When Choosing the Right Solution<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Choosing among Clay alternatives depends on how enrichment data will behave once it becomes part of day-to-day GTM operations. The factors below reflect the real constraints teams run into after enrichment moves upstream and starts influencing outbound execution directly.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Data_Accuracy_Over_Time\"><\/span>Data Accuracy Over Time<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Initial accuracy is easy. Consistency is not.<\/p>\n\n\n\n<p>When evaluating a solution, look beyond first-run enrichment results and ask how data behaves across multiple refresh cycles. If the same account or persona is classified differently over time without any real-world change, segmentation and scoring logic will eventually break. The right solution should prioritize repeatable accuracy, not just one-time correctness.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Schema_Alignment_and_Field_Discipline\"><\/span>Schema Alignment and Field Discipline<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Enrichment should strengthen your CRM, not reshape it.<\/p>\n\n\n\n<p>Many tools append data without respecting existing field definitions, overwrite logic that RevOps teams rely on, or introduce new attributes without governance\u2014issues that become especially risky in regulated environments where data accuracy, traceability, and control are expected, as outlined in <a href=\"https:\/\/gdpr.eu\/checklist\/\" target=\"_blank\" rel=\"noopener\">GDPR data governance<\/a> requirements.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Persona_and_Seniority_Reliability\"><\/span>Persona and Seniority Reliability<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Outbound relevance depends on persona trust.<\/p>\n\n\n\n<p>If SDRs feel the need to double-check job titles, seniority, or responsibilities before outreach, enrichment isn&#8217;t doing its job. Reliable solutions produce persona data that reps can act on confidently, without manual validation or workaround research.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"User_Accessibility_vs_Technical_Dependency\"><\/span>User Accessibility vs. Technical Dependency<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Business users should be able to operate enrichment tools independently.<\/p>\n\n\n\n<p>If your platform requires dedicated specialists, extensive training programs, or technical resources to design workflows, you&#8217;ve created an organizational bottleneck. The right solution empowers SDRs, sales ops, and RevOps teams to solve prospecting problems themselves\u2014without waiting for technical support.<\/p>\n\n\n\n<p><strong>Red flag:<\/strong> If adopting a tool means hiring a specialist or sending team members through multi-week training programs, consider whether that complexity is truly necessary for your use case.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Built-In_Quality_Assurance\"><\/span>Built-In Quality Assurance<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Manual validation defeats the purpose of automation.<\/p>\n\n\n\n<p>Tools that require you to manually review every enriched cell before trusting the data haven&#8217;t solved the quality problem\u2014they&#8217;ve just shifted the work. Look for platforms with built-in confidence scoring, automatic quality flagging, and guided optimization suggestions.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Segmentation_and_Routing_Stability\"><\/span>Segmentation and Routing Stability<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Automation only works when inputs are predictable.<\/p>\n\n\n\n<p>If enriched fields cause leads to shift segments unexpectedly or trigger inconsistent routing behavior, operational overhead increases quickly. The right solution supports stable segmentation and deterministic routing, allowing GTM teams to scale outbound without adding exceptions or manual fixes.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Operational_Overhead_and_Maintenance\"><\/span>Operational Overhead and Maintenance<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Every tool creates maintenance work\u2014the question is how much.<\/p>\n\n\n\n<p>Some solutions require constant monitoring, tuning, and cleanup as data volumes grow. Others are designed to behave predictably with minimal intervention. When evaluating options, consider the long-term RevOps cost, not just setup effort or subscription price.<\/p>\n\n\n\n<p><strong>Hidden cost example:<\/strong> Platforms requiring manual prompt writing, workflow mapping, and cell-by-cell validation add ongoing operational burden that compounds over time.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"Fit_for_Your_GTM_Maturity\"><\/span>Fit for Your GTM Maturity<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>There is no universally &#8220;best&#8221; solution.<\/p>\n\n\n\n<p>Teams experimenting with ICPs and workflows benefit from flexibility and customization. Teams running production outbound motions benefit from accuracy, consistency, and control. The right solution is the one that aligns with where your GTM system is today, not where it was six months ago.<\/p>\n\n\n\n<p><strong>Maturity checkpoint:<\/strong> If your outbound motion is already defined and you&#8217;re optimizing for execution speed and data trust, technical flexibility becomes less valuable than operational simplicity. This is often where teams discover that GTM system architecture matters more than individual tool features.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><a href=\"https:\/\/calendly.com\/aman-garg91\/30min\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"704\" height=\"244\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives-1.png\" alt=\"\" class=\"wp-image-1083 lazyload\" style=\"--smush-placeholder-width: 704px; --smush-placeholder-aspect-ratio: 704\/244;width:986px;height:auto\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives-1.png 704w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives-1-300x104.png 300w\" data-sizes=\"(max-width: 704px) 100vw, 704px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/a><\/figure>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"The_Common_Mistakes_Teams_Make_When_Choosing_a_Clay_Alternative\"><\/span>The Common Mistakes Teams Make When Choosing a Clay Alternative<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Even the best Clay alternatives can fall short if they&#8217;re chosen or implemented without understanding how enrichment data behaves inside real GTM systems. Most problems don&#8217;t surface during evaluation or demos\u2014they appear weeks later, once enriched data starts powering segmentation, routing logic, scoring models, and outbound execution.<\/p>\n\n\n\n<p>Here are the most common mistakes GTM teams make when evaluating tools like Clay.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"1_Optimizing_for_Flexibility_Instead_of_Usability\"><\/span>1. Optimizing for Flexibility Instead of Usability<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>We experienced this directly. We could technically build anything in Clay, but each new workflow meant hours of mapping, prompt writing, and testing. The question shifted from &#8220;Can we build this?&#8221; to &#8220;Do we have time to build and maintain this?&#8221; The answer was increasingly no.<\/p>\n\n\n\n<p><strong>The mistake:<\/strong> Choosing a tool based on what it <em>can<\/em> do rather than what your team <em>can realistically operate<\/em> without technical support.<\/p>\n\n\n\n<p><strong>The fix:<\/strong> Evaluate whether your team actually needs unlimited flexibility or whether they need to solve 5-10 specific enrichment problems reliably. If it&#8217;s the latter, business-user platforms like Pintel will deliver faster results with less overhead.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"2_Underestimating_the_Cost_of_Manual_Quality_Control\"><\/span>2. Underestimating the Cost of Manual Quality Control<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Many teams evaluate Clay alternatives based on how many data sources a tool connects to or how much information it can append to each record. They don&#8217;t evaluate how much manual review will be required to trust that data.<\/p>\n\n\n\n<p>Here&#8217;s what we learned using Clay: even when enrichment runs successfully, you still need to open every cell, review the AI&#8217;s output, and decide whether to trust it. One bad job title classification means an entire segment gets routed incorrectly. Without built-in confidence scoring, you&#8217;re forced to choose between manual review (slow) or automation with unknown error rates (risky).<\/p>\n\n\n\n<p><strong>The mistake:<\/strong> Assuming more data automatically means better data, without accounting for quality assurance workflows.<\/p>\n\n\n\n<p><strong>The fix:<\/strong> Ask vendors how their platform handles quality control. Look for built-in confidence scoring, automatic error flagging, and guided optimization\u2014not just broad data coverage.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"3_Treating_Enrichment_as_a_One-Time_Append\"><\/span>3. Treating Enrichment as a One-Time Append<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>A common assumption is that enrichment happens once, at the top of the funnel. In reality, data is refreshed, re-enriched, and reused continuously across CRM workflows, scoring systems, and outbound campaigns.<\/p>\n\n\n\n<p>When teams choose tools that don&#8217;t behave consistently across enrichment cycles, the same account can look different week to week\u2014even without any real-world change. This breaks segmentation stability, skews reporting, and makes GTM performance harder to predict.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"4_Ignoring_CRM_Schema_and_Routing_Dependencies\"><\/span>4. Ignoring CRM Schema and Routing Dependencies<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Many enrichment tools append data without respecting existing CRM schemas. Fields get overwritten, new attributes are created without governance, and conflicting values creep into critical workflows.<\/p>\n\n\n\n<p>Initially, these issues go unnoticed. Over time, they cause routing rules to misfire, leads to land in the wrong queues, and RevOps teams to spend cycles debugging data instead of improving systems.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"5_Assuming_SDRs_Will_Compensate_for_Inaccurate_Data\"><\/span>5. Assuming SDRs Will Compensate for Inaccurate Data<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>When enrichment data isn&#8217;t trustworthy, the burden shifts to SDRs. Reps start checking LinkedIn profiles, validating job titles, and rewriting messaging to compensate for uncertainty.<\/p>\n\n\n\n<p>We saw this pattern repeat: SDRs would pull enriched leads, glance at the persona data, then open LinkedIn anyway &#8220;just to be sure.&#8221; That&#8217;s the moment you realize enrichment isn&#8217;t actually saving time\u2014it&#8217;s just adding steps.<\/p>\n\n\n\n<p>This manual validation slows execution, introduces inconsistency, and defeats the purpose of automation. If SDRs don&#8217;t trust the data by default, the enrichment tool has already failed.<\/p>\n\n\n\n<h3 class=\"wp-block-heading has-large-font-size\"><span class=\"ez-toc-section\" id=\"6_Overlooking_the_Hidden_Cost_of_Technical_Dependencies\"><\/span>6. Overlooking the Hidden Cost of Technical Dependencies<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Some Clay alternatives seem flexible and powerful during demos but require dedicated specialists, ongoing training, and constant workflow maintenance as outbound scales. These hidden costs don&#8217;t show up on pricing pages\u2014they show up as headcount, time-to-value delays, and RevOps bottlenecks.<\/p>\n\n\n\n<p>When we used Clay, we initially justified the learning curve: &#8220;Once we&#8217;re trained, it&#8217;ll pay off.&#8221; What we didn&#8217;t account for was that every new use case meant re-learning, re-training, and re-optimizing. The maintenance cost never went away\u2014it compounded.<\/p>\n\n\n\n<p>When evaluating tools like Clay, it&#8217;s critical to factor in long-term operational costs, not just initial capabilities.<\/p>\n\n\n\n<p><strong>The mistake:<\/strong> Evaluating tools based on feature lists without considering the organizational cost of operating them long-term.<\/p>\n\n\n\n<p><strong>The fix:<\/strong> Ask yourself: &#8220;Can our business users operate this independently, or will we need to hire someone?&#8221; If the answer is the latter, factor that cost into your decision.<\/p>\n\n\n\n<p><strong>Why this matters once outbound scales:<\/strong> The mistakes above seem small during evaluation but create compounding costs at scale. Teams that choose tools based on coverage or flexibility often spend the next 12 months compensating for quality gaps, schema conflicts, and operational overhead. The right time to evaluate these factors is before enrichment becomes a critical dependency.<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-larger-font-size\"><span class=\"ez-toc-section\" id=\"Final_Thoughts\"><\/span>Final Thoughts<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Evaluating Clay alternatives depends on understanding how enrichment data behaves once it becomes part of core GTM systems\u2014and whether your team can operate the tool without creating new technical dependencies.<\/p>\n\n\n\n<p>We used Clay extensively. Its flexibility is genuinely useful for teams with specific needs. That flexibility comes with operational costs: learning curves, manual workflow design, quality control gaps, and the need for dedicated specialists. For teams with technical resources and complex customization requirements, those tradeoffs can make sense.<\/p>\n\n\n\n<p>For teams that need reliable enrichment without the operational overhead\u2014teams that want to solve prospecting problems without becoming workflow engineers\u2014platforms designed for business users offer a different tradeoff.<\/p>\n\n\n\n<p>As outbound scales, enrichment stops being a background task and starts influencing segmentation, routing, scoring, and SDR execution directly. At that point, accuracy, schema alignment, and usability matter more than unlimited flexibility. The lesson we learned: <strong>data that looks correct but requires constant validation isn&#8217;t automating anything.<\/strong><\/p>\n\n\n\n<p><strong>When choosing among tools like Clay, consider these two questions:<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>How mature is your outbound system?<\/strong> Teams still experimenting will value flexibility. Teams running production motions will value reliability and ease of use.<\/li>\n\n\n\n<li><strong>Who needs to operate the tool?<\/strong> If your answer is &#8220;business users without technical training,&#8221; that immediately narrows your options.<\/li>\n<\/ol>\n\n\n\n<p>The takeaway is simple: choose the solution that matches how mature your outbound system is, how much stability it requires, and who needs to use it day-to-day. Among Clay alternatives, the most powerful tool isn&#8217;t always the most effective one.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><a href=\"https:\/\/calendly.com\/aman-garg91\/30min\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" width=\"704\" height=\"244\" data-src=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives.png\" alt=\"\" class=\"wp-image-1081 lazyload\" style=\"--smush-placeholder-width: 704px; --smush-placeholder-aspect-ratio: 704\/244;width:986px;height:auto\" data-srcset=\"https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives.png 704w, https:\/\/pintel.ai\/blogs\/wp-content\/uploads\/2025\/12\/Clay-alternatives-300x104.png 300w\" data-sizes=\"(max-width: 704px) 100vw, 704px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" \/><\/a><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>If you\u2019re running outbound or managing GTM data, enrichment plays a critical role in how effectively&#8230;<\/p>\n","protected":false},"author":3,"featured_media":1143,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kadence_starter_templates_imported_post":false,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"categories":[1],"tags":[39,38,40],"class_list":["post-1071","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-b2b-data-quality","tag-clay-alternatives","tag-lead-enrichment-2"],"_links":{"self":[{"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/posts\/1071","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/comments?post=1071"}],"version-history":[{"count":13,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/posts\/1071\/revisions"}],"predecessor-version":[{"id":2027,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/posts\/1071\/revisions\/2027"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/media\/1143"}],"wp:attachment":[{"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/media?parent=1071"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/categories?post=1071"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pintel.ai\/blogs\/wp-json\/wp\/v2\/tags?post=1071"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}