{"id":7606,"date":"2026-06-13T05:07:36","date_gmt":"2026-06-13T05:07:36","guid":{"rendered":"https:\/\/www.coffee.ai\/articles\/gong-alternatives-crm-integration"},"modified":"2026-06-13T05:07:36","modified_gmt":"2026-06-13T05:07:36","slug":"gong-alternatives-crm-integration","status":"publish","type":"post","link":"https:\/\/www.coffee.ai\/articles\/gong-alternatives-crm-integration","title":{"rendered":"Best Gong Alternatives with CRM Integration (2026)"},"content":{"rendered":"<p><em>Written by: Doug Camplejohn, CEO &amp; Co-Founder, Coffee<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>Most Gong alternatives act as passive recording layers and still force reps to update Salesforce or HubSpot by hand, which keeps data hygiene problems alive.<\/li>\n<li>Genuine CRM integration means the system automatically writes back contacts, activities, deal stages, and enrichment fields without any rep intervention.<\/li>\n<li>Coffee stands out by offering both a standalone CRM and a companion app, with deeper field-level write-back than Sybill, Avoma, or Clari.<\/li>\n<li>Hidden TCO costs from separate enrichment tools, manual logging time, and CRM admin hours often exceed license fees, while Coffee\u2019s bundled agent model reduces these expenses.<\/li>\n<li>Eliminate manual CRM updates and see agent-led write-back in action with Coffee, <a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\">get started today<\/a>.<\/li>\n<\/ul>\n<h2>What Makes a Strong Gong Alternative with CRM Integration<\/h2>\n<p>A strong alternative automatically creates activities, updates deal stages, and enriches records without rep input. This automation matters because <a href=\"https:\/\/futurumgroup.com\/insights\/ai-agents-take-center-stage-will-sales-teams-that-automate-win-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">sales professionals now prioritize data hygiene and integration<\/a>, and they need tools that maintain CRM accuracy without adding to their workload. A tool that records calls but leaves logging to humans does not solve that problem.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678549697-4e8d65abe17d.gif\" alt=\"GIF of Coffee platform where user is using AI to prep for a meeting with Coffee AI\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Automated meeting prep with Coffee AI CRM Agent<\/em><\/figcaption><\/figure>\n<p>Five criteria separate genuine integrations from bolted-on layers:<\/p>\n<ol>\n<li><strong>Depth and reliability of Salesforce\/HubSpot write-back<\/strong>, meaning the tool writes field-level data to contacts, opportunities, and activities automatically.<\/li>\n<li><strong>Total cost of ownership<\/strong>, which includes license fee plus integration, maintenance, and rep-hour savings across the full stack.<\/li>\n<li><strong>Setup friction and required permissions<\/strong>, including OAuth scopes, admin access, and time-to-value.<\/li>\n<li><strong>Quality of pipeline intelligence output<\/strong>, such as forecast accuracy, deal-stage tracking, and week-over-week visibility.<\/li>\n<li><strong>Standalone vs. companion deployment<\/strong>, so the tool can replace or augment an existing CRM without a rip-and-replace.<\/li>\n<\/ol>\n<p>The table below applies these five criteria across Coffee and three leading alternatives, so you can see how each platform handles write-back depth, TCO structure, setup requirements, pipeline intelligence, and deployment options.<\/p>\n<h2>Side-by-Side Comparison of Gong Alternatives with CRM Integration<\/h2>\n<table>\n<thead>\n<tr>\n<th>Criterion<\/th>\n<th>Coffee<\/th>\n<th>Sybill<\/th>\n<th>Avoma<\/th>\n<th>Clari<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>CRM Write-Back Depth<\/strong><\/td>\n<td>Agent writes contacts, companies, activities, deal stages, and enrichment fields to Salesforce or HubSpot automatically, and <a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">summary templates are customizable and writable back to Coffee, HubSpot, or Salesforce<\/a>.<\/td>\n<td>Writes AI-generated call summaries and CRM fields post-call, and in most configurations relies on rep review before sync.<\/td>\n<td>Syncs meeting notes, action items, and transcripts to CRM, while deal-stage updates require a manual trigger or workflow rule.<\/td>\n<td>Focuses on pipeline forecasting and deal inspection, and activity write-back to Salesforce Opportunities requires companion tools for field-level logging.<\/td>\n<\/tr>\n<tr>\n<td><strong>TCO Signal<\/strong><\/td>\n<td>Seat-based pricing with agent labor for enrichment, logging, and forecasting included, which consolidates enrichment, recording, and forecasting point tools.<\/td>\n<td>Per-seat subscription with enrichment and forecasting sold separately.<\/td>\n<td>Per-seat subscription where CRM admin effort adds hidden maintenance cost.<\/td>\n<td>Enterprise pricing, and <a href=\"https:\/\/emvigotech.com\/blog\/AI-business-automation-tools\" target=\"_blank\" rel=\"noindex nofollow\">license fees often represent under 30% of total platform spend once integration and maintenance are included<\/a>.<\/td>\n<\/tr>\n<tr>\n<td><strong>Setup Friction<\/strong><\/td>\n<td>OAuth connection to Google Workspace or Microsoft 365, so the agent begins logging immediately, with no custom field mapping required for standard objects.<\/td>\n<td>OAuth to CRM, with some custom field mapping needed for non-standard objects.<\/td>\n<td>OAuth to CRM and calendar, and template configuration adds setup time.<\/td>\n<td>Enterprise implementation, and non-native systems require MuleSoft, integration partners, or AgentExchange apps.<\/td>\n<\/tr>\n<tr>\n<td><strong>Pipeline Intelligence<\/strong><\/td>\n<td>Agent-driven Pipeline Compare shows week-over-week deal changes, stalled opportunities, and new additions without CSV exports.<\/td>\n<td>Provides deal summaries and next-step tracking, with limited week-over-week visualization.<\/td>\n<td>Offers meeting-centric insights, and pipeline views require CRM data to be current.<\/td>\n<td>Delivers strong forecast modeling, and <a href=\"https:\/\/revenue.io\/faqs\" target=\"_blank\" rel=\"noindex nofollow\">real-time deal health scoring using engagement data<\/a> is a comparable capability in Revenue.io\u2019s Salesforce-native model.<\/td>\n<\/tr>\n<tr>\n<td><strong>Deployment Model<\/strong><\/td>\n<td>Standalone CRM or Companion App on top of Salesforce or HubSpot.<\/td>\n<td>Companion only.<\/td>\n<td>Companion only.<\/td>\n<td>Companion only and Salesforce-dependent.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>CRM Write-Back Proof with Field-Level Examples<\/h2>\n<p>Field-level write-back is the operative test. <a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">Coffee&#8217;s Stripe integration, launched in January 2026, automatically imports customers and companies, enriches them, and marks paid invoices as Closed Won deals<\/a>, which means a deal-stage update triggered by a financial event instead of a rep action. <a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">The QuickBooks integration, released in February 2026, syncs invoices and payment statuses in real time within the CRM<\/a>, so write-back extends beyond sales activity into revenue data.<\/p>\n<p>On the competitive side, Cirrus Insight automatically syncs emails, calendar events, tasks and activity data to Salesforce, reducing manual data entry. <a href=\"https:\/\/revenue.io\/faqs\" target=\"_blank\" rel=\"noindex nofollow\">Revenue.io writes AI-generated call and deal summaries directly to Salesforce records after calls and meetings<\/a>, but <a href=\"https:\/\/revenue.io\/faqs\" target=\"_blank\" rel=\"noindex nofollow\">is built exclusively for Salesforce and does not support HubSpot<\/a>. Salesforce&#8217;s own Conversation Insights add-on does not describe automatic opportunity stage updates or autonomous pipeline management without additional configuration.<\/p>\n<p>While write-back depth determines what a tool can do, total cost of ownership determines whether you can afford to do it at scale, and the gap between license fees and true TCO is wider in this category than most buyers expect.<\/p>\n<h2>Hidden TCO Considerations for Gong Alternatives on Salesforce and HubSpot<\/h2>\n<p><a href=\"https:\/\/emvigotech.com\/blog\/AI-business-automation-tools\" target=\"_blank\" rel=\"noindex nofollow\">Total cost of ownership for AI automation tools should be evaluated as license fee plus integration, maintenance, and training rather than subscription price alone, and license fees often represent under 30% of total platform spend.<\/a> For Gong alternatives, the hidden costs cluster in three areas: enrichment tools that must be purchased separately such as Apollo or ZoomInfo, CRM admin hours spent mapping fields and fixing sync errors, and rep time lost to manual logging.<\/p>\n<p><a href=\"https:\/\/futurumgroup.com\/insights\/ai-agents-take-center-stage-will-sales-teams-that-automate-win-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">AI agents can deliver time savings in research and content creation for sales teams.<\/a> Coffee&#8217;s seat-based model bundles enrichment, recording, and pipeline intelligence into a single agent, which removes the per-tool licensing that inflates TCO on fragmented stacks. Salesforce&#8217;s Conversation Insights add-on alone costs $50 per user per month on top of existing Sales Cloud licenses, and that price comes before any pipeline management tooling is added.<\/p>\n<h2>Real-World Setup Time and Permission Requirements<\/h2>\n<p>Coffee&#8217;s Companion App connects via OAuth to Google Workspace or Microsoft 365 and begins logging activities immediately against existing Salesforce or HubSpot records. Standard object mapping for contacts, companies, opportunities, and activities requires no custom field configuration for most teams. Salesforce-native tools that rely on MuleSoft or AgentExchange for non-native system connections introduce additional permission layers and implementation timelines. <a href=\"https:\/\/pipeline.zoominfo.com\/sales\/sales-engagement-automation-platforms\" target=\"_blank\" rel=\"noindex nofollow\">HubSpot Sales Hub updates contact data, activities, and deal stages in real time because its engagement features are native to the CRM<\/a>, which makes HubSpot-native tools faster to configure than external sync solutions, but that advantage disappears when the tool is not HubSpot-native.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678412915-a11943d2b0b8.gif\" alt=\"Join a meeting from the Coffee AI platform\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Join a meeting from the Coffee AI platform<\/em><\/figcaption><\/figure>\n<h2>Pipeline Intelligence Differences Across Tools<\/h2>\n<p><a href=\"https:\/\/futurumgroup.com\/insights\/ai-agents-take-center-stage-will-sales-teams-that-automate-win-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">Top-performing sales teams are 1.7x more likely than underperformers to use AI agents.<\/a> The underlying reason is data quality, because agent-based tools write structured, timestamped activity data into the CRM continuously and give forecasting models accurate inputs. Passive recording layers produce transcripts but leave deal-stage data stale until a rep updates it manually.<\/p>\n<p>Coffee&#8217;s Pipeline Compare feature visualizes week-over-week changes such as progressed deals, stalled opportunities, and new additions directly from agent-captured data, without CSV exports or manual pipeline reviews. An agent&#8217;s success depends more on data completeness and governance than on the underlying model, because a well-governed agent with complete customer context outperforms a more capable model operating on stale CRM data.<\/p>\n<p>For teams evaluating these tools on limited budgets, free tiers appear attractive, but they typically sacrifice the very capabilities that drive pipeline intelligence quality.<\/p>\n<h2>Free Gong Alternatives with CRM Integration and Paid Tier Limitations<\/h2>\n<p>Several tools offer free tiers, with Avoma and Fireflies among them, but free plans typically cap recording minutes, restrict CRM sync to one-way note pushes, and exclude deal-stage write-back entirely. Sybill&#8217;s free tier limits the number of calls analyzed per month and does not include Salesforce field mapping. These constraints make free tiers viable for individual contributors evaluating fit, but they remain insufficient for RevOps teams that need reliable, field-level write-back at scale. <a href=\"https:\/\/emvigotech.com\/blog\/AI-business-automation-tools\" target=\"_blank\" rel=\"noindex nofollow\">Tools with lower integration and maintenance burden deliver materially better TCO than platforms requiring extensive manual administration<\/a>, a calculus that applies equally to free tiers that generate manual cleanup work downstream, where the 30% license-to-total-cost ratio discussed earlier becomes even more skewed.<\/p>\n<h2>Why Most Gong Alternatives Still Require Manual CRM Updates<\/h2>\n<p>Most conversation intelligence tools were built as recording layers first and CRM connectors second. Their architecture captures audio and generates transcripts, then attempts to push structured data into a CRM via API. That push is typically triggered by a rep action such as reviewing a summary, approving a sync, or clicking a button, rather than by the agent itself. <a href=\"https:\/\/svitla.com\/blog\/agentic-ai-market-trends-2026\" target=\"_blank\" rel=\"noindex nofollow\">Data movement and workflow execution are moving closer to the system of record rather than remaining trapped in a conversation layer<\/a>, but most incumbent tools have not rebuilt their core architecture to reflect that shift.<\/p>\n<p>Returning to the data entry burden mentioned earlier, Coffee&#8217;s agent closes this gap by treating every email, calendar event, call transcript, and financial signal as a write-back trigger, with no rep action required.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678321672-5c8717cf0024.gif\" alt=\"Create instant meeting follow-up emails with the Coffee AI CRM agent\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Create instant meeting follow-up emails with the Coffee AI CRM agent<\/em><\/figcaption><\/figure>\n<h2>Best-Fit Use Cases for Early-Stage Teams and Established Salesforce or HubSpot Shops<\/h2>\n<p>Early-stage teams with roughly 1 to 20 employees that have outgrown spreadsheets but find Salesforce or HubSpot too maintenance-heavy are best served by Coffee&#8217;s Standalone CRM, where the agent manages the system of record from day one. There is no legacy data model to reconcile and no admin overhead to sustain.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1763678186019-5cc1a76ac78e.gif\" alt=\"Build people lists automatically with Coffee AI CRM Agent\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Build people lists automatically with Coffee AI CRM Agent<\/em><\/figcaption><\/figure>\n<p>Established Salesforce or HubSpot shops, which form the primary audience for this guide, are best served by Coffee&#8217;s Companion App. The agent writes back to existing records and preserves pipeline history, custom fields, quotas, and forecasting configurations that took years to build. Avoma and Sybill are reasonable companions for teams whose primary need is meeting notes and lightweight CRM sync, but neither offers the autonomous deal-stage and enrichment write-back that Coffee&#8217;s agent provides. Clari is appropriate for enterprise forecast modeling but adds cost and complexity that small-to-mid-market teams rarely need.<\/p>\n<h2>Risks and Limitations to Consider<\/h2>\n<p>No tool eliminates all integration risk. Coffee&#8217;s deeper third-party integrations beyond Google Workspace, Microsoft 365, Salesforce, and HubSpot currently route through Zapier, with native connections on the product roadmap. Teams with highly customized Salesforce orgs that include complex validation rules, required fields, or multi-currency setups should validate field mapping during a trial before committing. Enterprise AI agent reliability depends on deterministic guardrails, context engineering, and open standards rather than simple prompt-based layers, which is a standard Coffee applies to its write-back logic but one that any buyer should verify against their specific org configuration.<\/p>\n<p>Data quality parity with dedicated enrichment providers like ZoomInfo is close but not identical for all firmographic fields, though for most small-to-mid-market use cases Coffee&#8217;s built-in enrichment is sufficient and eliminates a separate license. Beyond data quality, change management remains a factor, because reps accustomed to reviewing and approving CRM updates before sync may require a brief adjustment period when the agent begins writing autonomously.<\/p>\n<h2>Decision-Framework Checklist for Selecting a Gong Alternative<\/h2>\n<p>Use this checklist to map your specific CRM environment and requirements to the platforms discussed above. Each question ties back to a key differentiator covered in the comparison, so you can move from theory to a concrete short list.<\/p>\n<ul>\n<li>\u2610 Does your team use Salesforce or HubSpot as the system of record? \u2192 Coffee Companion App or a Salesforce-native tool like Revenue.io.<\/li>\n<li>\u2610 Are you starting fresh without a CRM? \u2192 Coffee Standalone CRM.<\/li>\n<li>\u2610 Is deal-stage write-back, not just note sync, a hard requirement? \u2192 Coffee, and verify Avoma and Sybill against your specific deal-stage field configuration.<\/li>\n<li>\u2610 Do you need HubSpot support? \u2192 Eliminate Revenue.io and evaluate Coffee and Avoma.<\/li>\n<li>\u2610 Is TCO a primary constraint? \u2192 Calculate license plus enrichment tool plus CRM admin hours, and note that Coffee&#8217;s bundled model typically wins at under 50 seats.<\/li>\n<li>\u2610 Do you need enterprise forecast modeling at scale? \u2192 Evaluate Clari alongside Coffee&#8217;s Pipeline Compare feature.<\/li>\n<li>\u2610 Is a free tier required for initial evaluation? \u2192 Avoma and Fireflies offer free tiers, with the expectation of limited write-back depth.<\/li>\n<\/ul>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How long does Coffee take to implement compared with other Gong alternatives with CRM integration?<\/h3>\n<p>Coffee&#8217;s Companion App connects to Salesforce or HubSpot via OAuth and begins logging activities against existing records immediately after authentication. For teams using Google Workspace or Microsoft 365, the agent starts scanning emails and calendars for contact and activity data within minutes of connection. There is no custom field mapping required for standard CRM objects. Most teams reach full operational write-back for contacts, activities, meeting summaries, and deal enrichment within a single business day. By contrast, tools that rely on external sync layers or require MuleSoft-style middleware typically involve multi-week implementation timelines and dedicated admin resources. Enterprise forecasting platforms like Clari often require formal implementation engagements measured in weeks or months.<\/p>\n<h3>What migration effort is required when moving from Gong to an agent-based companion app?<\/h3>\n<p>Moving from Gong to Coffee as a Companion App does not require migrating your CRM. Coffee writes to your existing Salesforce or HubSpot instance, so historical pipeline data, custom fields, quotas, and forecasting configurations remain intact. The migration effort is limited to three steps: deprovisioning Gong licenses and any associated recording bot permissions, authenticating Coffee to your CRM and communication tools, and configuring summary templates to match your sales methodology such as BANT, MEDDIC, or SPICED. Coffee&#8217;s changelog documents that summary templates are customizable and writable back to HubSpot or Salesforce, so methodology alignment becomes a configuration step rather than a development task. Teams that used Gong primarily for call recording and coaching will find the functional overlap high, while teams that relied on Gong&#8217;s enterprise revenue forecasting should evaluate Coffee&#8217;s Pipeline Compare feature against their specific forecasting workflow before decommissioning.<\/p>\n<h3>How do security and compliance compare across these platforms?<\/h3>\n<p>Coffee is SOC 2 Type 2 certified and GDPR compliant. Customer data is not used to train public AI models, which addresses the most common security objection from RevOps teams handling sensitive deal and contact data. Gong and Sybill publish SOC 2 Type 2 certifications as well, which makes compliance posture broadly comparable across the category for standard commercial use cases. The meaningful differentiator is data residency and model training policy, so buyers in regulated-adjacent industries should confirm with any vendor whether conversation transcripts or CRM field data are used for model improvement. Coffee&#8217;s policy explicitly prohibits this. Teams in healthcare or financial services with formal multi-year security review requirements fall outside Coffee&#8217;s current ideal customer profile regardless of compliance certification.<\/p>\n<h3>How can I evaluate true CRM sync depth before committing?<\/h3>\n<p>The most reliable evaluation method is a structured trial with a live Salesforce or HubSpot sandbox connected to real call and email data. During that trial, test whether the tool creates a new contact record automatically from a calendar invite without rep action, logs a call activity to the associated opportunity record post-meeting without a rep clicking &#8220;sync,&#8221; updates a deal stage field based on a defined trigger such as a signed contract or a payment event, and writes a structured meeting summary that includes next steps and methodology fields to the opportunity record. Tools that require rep approval before any of these writes occur act as passive layers rather than agents. Coffee&#8217;s trial environment supports all four tests against a live CRM connection. Ask any vendor on your shortlist to demonstrate the same four scenarios in a sandbox before signing a contract.<\/p>\n<h2>Conclusion: Choosing the Right Gong Alternative with CRM Integration<\/h2>\n<p>The five criteria in this guide, which include write-back depth, TCO, setup friction, pipeline intelligence quality, and deployment flexibility, consistently separate genuine agent-led integrations from passive recording layers. Earlier research such as <a href=\"https:\/\/ivristech.com\/salesforce-state-of-sales-2026-ai-agents\/\" target=\"_blank\" rel=\"noindex nofollow\">Salesforce\u2019s 2026 State of Sales report<\/a> shows that AI agents are already common, yet most conversation intelligence tools still leave the last mile of CRM data entry to humans.<\/p>\n<p>For RevOps and sales leaders at small-to-mid-market companies already running Salesforce or HubSpot, Coffee&#8217;s Companion App delivers the write-back depth, stack consolidation, and pipeline intelligence that the category has promised but rarely delivered. The agent handles data in so the CRM produces accurate data out, without replacing the system of record teams have already built.<\/p>\n<p> <a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Get started with Coffee and let the agent handle your CRM data entry.<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tired of manual CRM updates? Coffee auto-writes contacts, deals &amp; activities \u2014 deeper than Sybill, Avoma, or Clari. See it in action today.<\/p>\n","protected":false},"author":11,"featured_media":7605,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-7606","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/7606","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/comments?post=7606"}],"version-history":[{"count":0,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/7606\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media\/7605"}],"wp:attachment":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media?parent=7606"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/categories?post=7606"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/tags?post=7606"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}