{"id":7420,"date":"2026-06-08T05:02:18","date_gmt":"2026-06-08T05:02:18","guid":{"rendered":"https:\/\/www.coffee.ai\/articles\/best-crm-companion-app-2026\/"},"modified":"2026-06-08T05:02:18","modified_gmt":"2026-06-08T05:02:18","slug":"best-crm-companion-app-2026","status":"publish","type":"post","link":"https:\/\/www.coffee.ai\/articles\/best-crm-companion-app-2026","title":{"rendered":"Best CRM Companion App for Salesforce or HubSpot in 2026"},"content":{"rendered":"<p><em>Written by: Doug Camplejohn, CEO &amp; Co-Founder, Coffee<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Choosing a CRM Companion<\/h2>\n<ul>\n<li>A CRM companion app layers automation on top of Salesforce or HubSpot to capture data, manage meetings, and update pipelines without replacing the core system.<\/li>\n<li>Four evaluation criteria \u2013 data-entry automation depth, structured and unstructured data unification, integration effort, and measurable time savings \u2013 help leaders separate real automation from surface-level tools.<\/li>\n<li>Native CRM apps and sales-engagement platforms like Salesloft or Outreach leave reps maintaining shadow CRMs because they fail to unify all interaction data back into the record.<\/li>\n<li>AI-agent companions like Coffee deliver 8\u201312 hours of weekly time savings per rep by auto-creating contacts, ingesting call transcripts, and writing summaries directly to Salesforce or HubSpot.<\/li>\n<li>Eliminate manual data entry from your Salesforce or HubSpot instance today \u2013 <a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>start with Coffee&#8217;s pricing page<\/strong><\/a>.<\/li>\n<\/ul>\n<h2>Four Evaluation Criteria for CRM Companion Apps<\/h2>\n<p>Mid-market Heads of Sales and RevOps leaders should align on four criteria that separate genuine automation from surface-level tooling before evaluating any vendor.<\/p>\n<p><strong>1. Depth of data-entry automation.<\/strong> Sales reps spend about 70% of their time on non-selling tasks, including manually entering customer notes. A companion app must capture contacts, activities, and interaction history autonomously, not just prompt reps to fill fields faster.<\/p>\n<p><strong>2. Ability to unify structured and unstructured data.<\/strong> Even when a companion automates data entry, it must handle both structured data such as contact fields and deal stages and unstructured data such as call transcripts, email threads, and meeting notes. A companion that cannot ingest both leaves critical context out of the CRM and undermines the time savings from criterion 1.<\/p>\n<p><strong>3. Integration effort and ongoing maintenance.<\/strong> <a href=\"https:\/\/integrateiq.com\/integrations\/hubspot-salesforce\" target=\"_blank\" rel=\"noindex nofollow\">The native HubSpot-Salesforce connector has sync limitations and risks of duplicates from mismatched Leads vs. Contacts handling<\/a>. A companion app should reduce this maintenance burden instead of multiplying it.<\/p>\n<p><strong>4. Measurable time savings and pipeline accuracy.<\/strong> <a href=\"https:\/\/klu.so\/blog\/manual-crm-updates-sales-productivity\" target=\"_blank\" rel=\"noindex nofollow\">Automating several hours per week of manual CRM data entry can yield significant additional selling time per year<\/a>. Evaluate vendors against a concrete hours-saved benchmark, not feature lists.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>See how Coffee&#8217;s automation delivers measurable time savings<\/strong><\/a> for your Salesforce or HubSpot instance.<\/p>\n<h2>Side-by-Side Comparison: Native Apps vs Platforms vs Coffee<\/h2>\n<p>The table below applies these four criteria to native CRM apps, sales-engagement platforms, and AI-agent companions like Coffee.<\/p>\n<table>\n<thead>\n<tr>\n<th>Criterion<\/th>\n<th>Native Salesforce \/ HubSpot Apps<\/th>\n<th>Sales-Engagement Platforms (Salesloft, Outreach)<\/th>\n<th>AI-Agent Companions (Coffee)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Data-entry automation depth<\/strong><\/td>\n<td>Surfaces existing records but offers limited data-entry automation<\/td>\n<td>Logs cadence touches but offers limited automation for contact creation and record enrichment<\/td>\n<td><a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">Auto-creates contacts, companies, and activities, and writes summaries back to Salesforce or HubSpot<\/a><\/td>\n<\/tr>\n<tr>\n<td><strong>Structured + unstructured data unification<\/strong><\/td>\n<td><a href=\"https:\/\/vantagepoint.io\/blog\/sf\/einstein-conversation-insights-complete-guide-ai-sales-call-intelligence\" target=\"_blank\" rel=\"noindex nofollow\">Native Salesforce Einstein Conversation Insights ingests and analyzes call transcripts, and HubSpot supports syncing third-party transcripts via its Conversation Intelligence API<\/a><\/td>\n<td>Cadence data only, with call recordings siloed in separate tools<\/td>\n<td>Ingests emails, calendar, and call transcripts and unifies them into one CRM record<\/td>\n<\/tr>\n<tr>\n<td><strong>Integration effort<\/strong><\/td>\n<td>Built-in but limited, which can lead to sync issues<\/td>\n<td>Requires configuration and ongoing field mapping<\/td>\n<td>Single authentication to Google Workspace or Microsoft 365, and the agent handles sync automatically<\/td>\n<\/tr>\n<tr>\n<td><strong>Measurable time savings<\/strong><\/td>\n<td>Minimal, because reps still enter data manually<\/td>\n<td><a href=\"https:\/\/sybill.ai\/blogs\/salesforce-vs-hubspot-vs-dynamics-365\" target=\"_blank\" rel=\"noindex nofollow\">4\u20136 hours per week saved on CRM updates when AI call-capture is added<\/a><\/td>\n<td>8\u201312 hours per week saved per rep through full-cycle automation<\/td>\n<\/tr>\n<tr>\n<td><strong>2026 readiness signals<\/strong><\/td>\n<td>SOC 2 varies by tier, with no agent-first architecture<\/td>\n<td>SOC 2 Type 2 common, but architecture remains cadence-centric, not agent-first<\/td>\n<td>SOC 2 Type 2 compliant, seat-based pricing with no LLM metering, and proactive agent architecture<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Setup and Onboarding: From Zero to Live<\/h2>\n<p>Native Salesforce and HubSpot apps require no additional setup but deliver almost no additional automation. Sales-engagement platforms demand dedicated Salesforce integration users, inclusion-segment configuration, and ongoing field-mapping reviews to prevent duplicate records. <a href=\"https:\/\/integrateiq.com\/integrations\/hubspot-salesforce\" target=\"_blank\" rel=\"noindex nofollow\">A common data quality failure occurs when the integration creates Salesforce Leads while HubSpot&#8217;s auto-create companies setting is enabled, producing duplicate Company records upon lead conversion.<\/a> Coffee&#8217;s Companion App connects through a single authentication to Google Workspace or Microsoft 365, then the agent begins populating contacts, companies, and activities immediately, with no dedicated integration user required.<\/p>\n<h2>Data Capture and Enrichment: Getting Every Interaction<\/h2>\n<p>Salesforce, HubSpot, and Dynamics 365 all function as recording systems that depend on manual rep data entry. Because reps must log calls manually, these systems <a href=\"https:\/\/aloware.com\/blog\/crm-conversation-intelligence\" target=\"_blank\" rel=\"noindex nofollow\">capture only about 25% of actual calls (logging 20 out of 80 daily calls)<\/a>, which leaves budget signals, stakeholder mentions, competitor references, and timeline objections out of the CRM entirely. Sales-engagement platforms capture cadence-touch data but keep call recordings in a separate silo. Coffee&#8217;s agent ingests emails, calendar events, and call transcripts simultaneously, enriches records with job titles, funding data, and LinkedIn profiles via licensed data partners, and writes structured summaries back to the CRM. AI automation can cut manual data work such as data entry, duplicate detection, and record enrichment.<\/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<h2>Meeting and Follow-Up Automation: Before, During, and After Calls<\/h2>\n<p>Native CRM apps provide no pre-meeting briefing and require reps to log post-meeting notes manually. Sales-engagement platforms generate call recordings but route summaries to a separate dashboard, not back to the CRM record. Coffee&#8217;s agent solves this siloing problem by writing all meeting data directly to the CRM. It delivers a pre-meeting &#8220;Today&#8221; page briefing attendees, roles, and past context, joins calls through an AI meeting bot on Zoom, Teams, or Meet, and after the call generates summaries, next steps, and follow-up email drafts in Gmail, all written back to the Salesforce or HubSpot record automatically. <a href=\"https:\/\/creatio.com\/glossary\/ai-crm\" target=\"_blank\" rel=\"noindex nofollow\">AI agents can autonomously trigger actions, update data, and move processes forward without waiting for human input, cutting operational time by hours or even days.<\/a> Coffee supports BANT, MEDDIC, and SPICED frameworks to ensure consistent qualification data enters the system on every call.<\/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<h2>Pipeline Visibility and Accuracy: Trusting the Forecast<\/h2>\n<p>Pipeline reviews in native CRM environments rely on manual CSV exports or expensive add-ons because the underlying data is incomplete. <a href=\"https:\/\/www.askelephant.ai\/blog\/why-reps-spend-25-percent-of-time-on-crm\" target=\"_blank\" rel=\"noindex nofollow\">Sales reps typically spend 10 to 11 hours per week on manual CRM data entry<\/a>. Sales-engagement platforms surface engagement metrics but do not update opportunity stages or close dates autonomously. Coffee&#8217;s Pipeline Compare feature visualizes week-over-week changes such as progressed deals, stalled opportunities, and new additions directly from the data the agent has already captured. This approach eliminates spreadsheet-based pipeline reviews and reduces shadow CRM reliance.<\/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>Long-Term Scalability and 2026 AI-Agent Trends<\/h2>\n<p><a href=\"https:\/\/fptsoftware.com\/resource-center\/blogs\/top-ai-trends-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">In 2026, organizations are shifting from reactive AI tools to AI agents and agentic workflows that execute defined goals with less human intervention, and IDC forecasts that by 2030, 45% of organizations will orchestrate AI agents at scale.<\/a> The global AI companion market is projected to grow substantially in the coming years, with the business segment expanding rapidly. Coffee is built for this trajectory: SOC 2 Type 2 certified, GDPR compliant, and priced on a seat-based model with no LLM metering, so the agent&#8217;s labor scales without unpredictable cost spikes as usage grows.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Explore Coffee&#8217;s seat-based pricing<\/strong><\/a>, where costs scale with your team, not your token count.<\/p>\n<h2>Best-Fit Use Cases for 20\u2013100 Person Sales Teams<\/h2>\n<p>Coffee&#8217;s Companion App is purpose-built for mid-market teams already committed to Salesforce or HubSpot. It delivers immediate value in three common scenarios. First, a 30-person sales team where reps toggle between HubSpot, ZoomInfo, and Gong daily gains a single agent that consolidates enrichment, recording, and CRM updates. Second, a RevOps leader whose pipeline reviews are unreliable because reps log fewer than half their activities regains forecast accuracy through Coffee&#8217;s autonomous activity logging without a heavy change-management campaign. Third, a Head of Sales whose new hires take weeks to learn the CRM shortens ramp time because Coffee&#8217;s pre-meeting briefings and automated follow-ups handle the administrative layer from day one.<\/p>\n<h2>Risks and Limitations to Weigh Before Adopting Coffee<\/h2>\n<p>Every companion app introduces trade-offs that teams should understand. Teams relying on Zapier for integrations beyond Google Workspace and Microsoft 365 should account for Zapier task costs, which compound as automation volume grows. Companion apps that rely on field mapping must be audited regularly, and <a href=\"https:\/\/integrateiq.com\/integrations\/hubspot-salesforce\" target=\"_blank\" rel=\"noindex nofollow\">incomplete field coverage is a known failure mode in HubSpot-Salesforce setups where data ownership rules are not clearly defined between marketing and sales systems.<\/a> Over-reliance on automated summaries without a human review step can also allow AI-generated errors to propagate into the CRM. Coffee mitigates this risk by routing follow-up email drafts to the rep for review before sending, which preserves human judgment at the final output stage.<\/p>\n<h2>Decision Checklist: Matching Companion Types to Your Team<\/h2>\n<p><strong>Choose native CRM apps if:<\/strong> your team&#8217;s primary need is mobile record access and you have no data-quality complaints.<\/p>\n<p><strong>Choose a sales-engagement platform if:<\/strong> outbound cadence consistency is the sole bottleneck and your CRM data quality is already strong.<\/p>\n<p><strong>Choose an AI-agent companion (Coffee) if:<\/strong> your team has 20\u2013100 reps on Salesforce or HubSpot, data quality is poor, reps spend more time on admin than selling, pipeline reviews require manual prep, and you want a single agent to replace fragmented point solutions for enrichment, recording, and forecasting without migrating your system of record.<\/p>\n<h2>Which CRM Is Better for Mid-Market Teams: Salesforce or HubSpot?<\/h2>\n<p>Neither platform is categorically superior because the right choice depends on team size, technical resources, and go-to-market motion. Salesforce offers deeper customization, advanced forecasting, and enterprise-grade territory management, which makes it the default for larger or more complex sales organizations. HubSpot provides faster onboarding, and <a href=\"https:\/\/sybill.ai\/blogs\/salesforce-vs-hubspot-vs-dynamics-365\" target=\"_blank\" rel=\"noindex nofollow\">most users become productive within one or two days without dedicated training<\/a>, while tighter native alignment between marketing and sales data makes it the preferred choice for growth-stage teams. For mid-market companies, the more relevant question is whether the chosen CRM has an agent layer that ensures data quality. Both platforms share the same structural flaw: they depend on manual rep entry, which leaves the majority of interaction content, including the 75% of calls not logged plus email threads and meeting notes, out of the CRM without an AI companion.<\/p>\n<h2>What CRMs Compete with Salesforce for Mid-Market Teams?<\/h2>\n<p>For mid-market teams, no single CRM is universally better than Salesforce because the evaluation depends on use case. HubSpot outperforms Salesforce on ease of adoption and marketing-sales alignment. Newer AI-native CRMs like Clarify and Day.ai offer modern interfaces but lack the integration depth required for established sales operations with quotas, forecasting, and required fields. The more productive framing for a team already on Salesforce is to add an AI-agent companion that resolves Salesforce&#8217;s core weakness, which is manual data dependency, instead of undertaking a costly CRM migration. Coffee&#8217;s Companion App preserves the Salesforce investment while eliminating the manual entry burden that makes reps resent the platform.<\/p>\n<h2>Do Companion Apps Work Inside Existing Salesforce Instances?<\/h2>\n<p>Companion apps such as Coffee work inside existing Salesforce instances without replacing them. Coffee&#8217;s Companion App connects to an existing Salesforce instance through a single authentication step. Once connected, the agent reads from and writes back to Salesforce records, auto-creating contacts and companies, logging activities, and <a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">writing customizable meeting summaries directly to Salesforce fields<\/a>. No data migration occurs, and there is no new system of record or disruption to existing Salesforce configurations including custom objects, required fields, or territory assignments. The agent operates as an autonomous worker inside the existing instance, not as a replacement for it.<\/p>\n<h2>How Much Time Do Sales Reps Spend on CRM Data Entry?<\/h2>\n<p><a href=\"https:\/\/optif.ai\/learn\/questions\/crm-input-time-average\/\" target=\"_blank\" rel=\"noindex nofollow\">On average, a B2B salesperson spends roughly 9\u201312 hours every week on manual CRM data entry<\/a>, including typing notes, creating contacts, logging activities, and searching for information. <a href=\"https:\/\/aeolusgtm.com\/insights\/sellers-only-sell-30\/\" target=\"_blank\" rel=\"noindex nofollow\">Sales reps spend 70% of their time on non-selling tasks, leaving only 28% to 30% of the week for actual selling<\/a>. As noted in the evaluation criteria, this 70% non-selling burden compounds across the entire sales team and limits total selling capacity. Sales teams using organized CRM data can close deals faster because representatives spend more time selling rather than searching for information. For a sales team, reducing administrative work can lead to significant efficiency gains.<\/p>\n<h2>Conclusion: A Practical Framework for Your Final Decision<\/h2>\n<p>The four criteria \u2013 data-entry automation depth, structured and unstructured data unification, integration effort, and measurable time savings \u2013 consistently point to the same conclusion for mid-market teams on Salesforce or HubSpot. Native apps and sales-engagement platforms address symptoms, not the root cause. The root cause is that legacy CRMs are passive databases that require humans to act as data entry clerks. An autonomous AI-agent companion resolves this at the architectural level, which ensures good data enters the system so accurate insights come out. <a href=\"https:\/\/www.creatio.com\/glossary\/ai-for-sales\" target=\"_blank\" rel=\"noindex nofollow\">According to McKinsey research, AI sales tools have the potential to increase leads by more than 50%, reduce costs by up to 60%, and cut call time by up to 70%.<\/a> Coffee is built specifically for this outcome, with SOC 2 Type 2 certification, seat-based pricing with no LLM metering, and deep Salesforce and HubSpot integration that newer AI CRMs cannot match.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Deploy an autonomous agent on your CRM today<\/strong><\/a> and eliminate manual data entry from day one.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>What makes Coffee different from a sales-engagement platform like Salesloft or Outreach?<\/h3>\n<p>Sales-engagement platforms are built to automate outbound cadences, which are sequences of emails, calls, and tasks designed to move a prospect through a defined outreach flow. They log cadence touches back to the CRM but do not auto-create contacts, enrich records, or ingest unstructured data such as call transcripts or email body content. Coffee&#8217;s Companion App is an autonomous AI agent focused on the data quality problem. It captures every interaction across email, calendar, and calls, enriches records with firmographic and contact data, writes structured meeting summaries back to Salesforce or HubSpot, and tracks pipeline changes week over week without rep involvement. The two tools solve different problems. If your pipeline stalls because reps are not following up consistently, a sales-engagement platform helps. If your CRM data is incomplete, your forecasts are unreliable, and your reps spend hours on admin, Coffee addresses the root cause.<\/p>\n<h3>How long does it take to set up Coffee&#8217;s Companion App on an existing Salesforce or HubSpot instance?<\/h3>\n<p>Setup typically finishes within a single day for most teams. It requires one authentication step that connects Coffee to your existing Salesforce or HubSpot instance and to your email and calendar provider, either Google Workspace or Microsoft 365. Once authenticated, the Coffee agent begins scanning emails and calendar events to auto-populate contacts, companies, and activities immediately. There is no data migration, no dedicated integration user requirement, and no disruption to existing CRM configurations such as custom objects, required fields, forecasting hierarchies, or territory assignments. Coffee supports BANT, MEDDIC, and SPICED qualification frameworks out of the box, so meeting summaries match existing sales processes from the first call.<\/p>\n<h3>Is Coffee secure enough for mid-market sales data?<\/h3>\n<p>Coffee is SOC 2 Type 2 certified and GDPR compliant. Customer data is not used to train public AI models. The agent processes emails, calendar events, and call transcripts to populate CRM records, but this data remains within Coffee&#8217;s secure infrastructure and is not shared with third parties beyond the licensed enrichment data partners used to augment contact and company records. For mid-market teams in non-regulated industries, Coffee&#8217;s security posture meets standard enterprise requirements. Teams in heavily regulated industries such as healthcare or finance with multi-year security review requirements fall outside Coffee&#8217;s current ideal customer profile.<\/p>\n<h3>How does Coffee&#8217;s pricing work, and what is included in a seat?<\/h3>\n<p>Coffee uses seat-based pricing, so you pay for the number of human users and the agent&#8217;s labor is included. Data capture, enrichment, meeting management, pipeline tracking, and all AI processing run without additional metering on LLM usage or automated processes. This model remains predictable as usage scales. There are no per-task fees, no token charges, and no separate licensing tiers for AI features. The full Coffee agent capability, including automatic contact creation, meeting briefings, AI meeting bot, post-call summaries, Pipeline Compare, and visitor identification, is available within the seat license.<\/p>\n<h3>What happens to data that was already in Salesforce or HubSpot before Coffee was connected?<\/h3>\n<p>Coffee&#8217;s agent works forward from the point of connection and focuses on live activity. It processes new emails, calendar events, and calls to enrich and update existing records. For contacts and companies already in the CRM, the agent augments records with enrichment data such as job titles, funding information, and LinkedIn profiles through licensed data partners as those records appear in active workflows. Historical call recordings or email threads that predate the connection are not processed retroactively. The practical implication is that data quality improves immediately for active deals and new contacts, while older dormant records are enriched progressively as they re-enter the sales cycle.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Save 8\u201312 hrs\/week per rep with Coffee, the AI companion that auto-updates Salesforce or HubSpot. Eliminate manual data entry today.<\/p>\n","protected":false},"author":11,"featured_media":7419,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-7420","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\/7420","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=7420"}],"version-history":[{"count":0,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/7420\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media\/7419"}],"wp:attachment":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media?parent=7420"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/categories?post=7420"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/tags?post=7420"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}