{"id":8638,"date":"2026-08-19T05:05:47","date_gmt":"2026-08-19T05:05:47","guid":{"rendered":"https:\/\/www.coffee.ai\/articles\/top-salesforce-replacement-options"},"modified":"2026-08-19T05:05:47","modified_gmt":"2026-08-19T05:05:47","slug":"top-salesforce-replacement-options","status":"publish","type":"post","link":"https:\/\/www.coffee.ai\/articles\/top-salesforce-replacement-options","title":{"rendered":"Top Salesforce Replacement Options 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 Replacing Salesforce in 2026<\/h2>\n<ul>\n<li>Salesforce replacements fall into three categories: cost-driven (Zoho, Pipedrive), complexity-driven (HubSpot, Dynamics 365), and AI-driven (Coffee), which removes manual data entry at the architectural level.<\/li>\n<li>CRM data quality is weak for most teams, and three-quarters of organizations struggle to trust their records while reps lose more than a full workday each week to manual entry, leaving only 28\u201333% of time for actual selling.<\/li>\n<li>Passive CRMs store data only as reliably as humans enter it, while AI agents like Coffee auto-create contacts, log activity, and enrich records from email and calendar.<\/li>\n<li>Coffee\u2019s Standalone CRM compresses implementation to days for small teams, and the Companion App layers onto existing Salesforce or HubSpot without migration risk.<\/li>\n<li><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>See Coffee pricing<\/strong><\/a> and remove the data entry burden that is degrading your pipeline intelligence today.<\/li>\n<\/ul>\n<h2>Why Salesforce Is Losing Ground With Sales Teams<\/h2>\n<p>The case for replacing Salesforce is practical and grounded in daily sales work. Many sales professionals do not completely trust the accuracy of their CRM data, and <a href=\"https:\/\/wavecnct.com\/blogs\/crm-statistics\" target=\"_blank\" rel=\"noindex nofollow\">76% of CRM users report that less than half of their organization&#039;s CRM data is accurate and complete<\/a>. This data quality problem stems from a structural flaw: <a href=\"https:\/\/apollo.io\/insights\/how-can-integration-reduce-time-spent-on-manual-data-entry\" target=\"_blank\" rel=\"noindex nofollow\">sales reps spend an average of 5.5 hours per week on manual data entry<\/a>, which both encourages rushed, incomplete logging and leaves reps with only <a href=\"https:\/\/getgangly.com\/blog\/sales-admin-time-study\" target=\"_blank\" rel=\"noindex nofollow\">28\u201333% of their time for actual selling<\/a>. Pipedrive&#039;s CRM Trends Report 2026 found that nearly four times as many sales professionals spend most of their time logging calls, emails, and meetings as those who count closing deals among their most frequent weekly activities.<\/p>\n<p>This article evaluates eight alternatives across eight criteria: data quality and entry effort, automation depth, implementation effort, user adoption, integration complexity, reporting visibility, scalability, and three-year total cost of ownership (TCO). The platforms evaluated are HubSpot, Zoho CRM, Pipedrive, Microsoft Dynamics 365, Attio, Nutshell, Coffee (Standalone CRM), and Coffee (Companion App). The table below highlights the core architectural split: every platform except Coffee relies on passive data entry, so data quality remains human-dependent regardless of price point.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Explore Coffee&#039;s AI-first approach<\/strong><\/a> to see how agent architecture addresses the data quality problem at its root.<\/p>\n<h2>Side-by-Side Comparison of Eight Salesforce Alternatives<\/h2>\n<table>\n<thead>\n<tr>\n<th>Platform<\/th>\n<th>Agent vs. Passive<\/th>\n<th>Est. 3-Year TCO (25 seats)<\/th>\n<th>Data Quality Reality Check<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>HubSpot Sales Hub Pro<\/td>\n<td>Passive<\/td>\n<td>Licenses alone at $90\/seat\/mo (3-year costs for 25 seats vary significantly with configuration)<\/td>\n<td>Data completeness depends entirely on rep entry, and the 76% accuracy gap mentioned earlier persists across price tiers<\/td>\n<\/tr>\n<tr>\n<td>Zoho CRM<\/td>\n<td>Passive<\/td>\n<td><a href=\"https:\/\/www.zoho.com\/crm\/compare\/total-cost-of-ownership-comparison.html\" target=\"_blank\" rel=\"noindex nofollow\">Zoho CRM Est. 3-Year licensing cost (25 seats) $12,600\u2013$46,800 (Standard $14\/seat\/mo to Ultimate $52\/seat\/mo, billed annually)<\/a><\/td>\n<td>Lower cost does not change passive architecture, so the manual entry burden remains<\/td>\n<\/tr>\n<tr>\n<td>Pipedrive<\/td>\n<td>Passive<\/td>\n<td><a href=\"https:\/\/softwaresift.com\/pipedrive-cost-worksheet\/\" target=\"_blank\" rel=\"noindex nofollow\">Pipedrive base 3-year TCO (25 seats, annual billing) is $12,600\u2013$71,100 (Lite $14\/seat\/mo to Ultimate $79\/seat\/mo)<\/a><\/td>\n<td>Fast adoption with strong usability, yet data quality still depends on human consistency<\/td>\n<\/tr>\n<tr>\n<td>Microsoft Dynamics 365<\/td>\n<td>Passive (Copilot add-on available)<\/td>\n<td>Comparable to Salesforce Enterprise, and implementation adds significant overhead per <a href=\"https:\/\/resources.rework.com\/tools\/crm\/best-crm-software-2026\" target=\"_blank\" rel=\"noindex nofollow\">2026 comparison data<\/a><\/td>\n<td>45% of organizations report their CRM data is not prepared for AI use, and Copilot features sit on top of the same passive record layer<\/td>\n<\/tr>\n<tr>\n<td>Attio<\/td>\n<td>Passive (modern UI)<\/td>\n<td>Seat-based pricing (Plus $29\/seat\/mo to Pro $69\/seat\/mo)<\/td>\n<td>Flexible data model, yet still reliant on human entry for unstructured data like call transcripts<\/td>\n<\/tr>\n<tr>\n<td>Nutshell<\/td>\n<td>Passive<\/td>\n<td>Competitive SMB pricing with quick onboarding for small teams<\/td>\n<td>Strong usability, but data quality remains contingent on rep discipline<\/td>\n<\/tr>\n<tr>\n<td>Coffee (Standalone CRM)<\/td>\n<td><strong>Agent<\/strong><\/td>\n<td>Seat-based pricing with agent labor included at no additional metering cost, as detailed on <a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\">Coffee pricing<\/a><\/td>\n<td>Agent auto-creates contacts, logs activity, and enriches records from email and calendar, so AI capture can significantly improve data completeness<\/td>\n<\/tr>\n<tr>\n<td>Coffee (Companion App)<\/td>\n<td><strong>Agent layer on Salesforce or HubSpot<\/strong><\/td>\n<td>Additive seat cost on top of existing CRM license, while eliminating the need for separate enrichment, recording, and sequencing tools<\/td>\n<td>Agent writes clean, structured data back to the existing system of record and addresses the root cause without platform migration<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Category-by-Category Analysis of Salesforce Alternatives<\/h2>\n<p><strong>Setup and onboarding.<\/strong> A simple HubSpot rollout for a small team can be functional in 2\u20138 weeks, while an equivalent Salesforce build typically requires 3\u20138 weeks. Automation rebuild often accounts for a substantial portion of total CRM implementation effort. Coffee&#039;s Standalone CRM connects to Google Workspace or Microsoft 365 and begins populating records immediately, with implementation measured in days rather than weeks for teams under 20.<\/p>\n<p><strong>Data capture and maintenance.<\/strong> Every passive CRM in this comparison shares the same architectural flaw: they store data only as reliably as humans enter it. This forces reps to manually log emails, calls, and meetings, which consumes more than a full workday each week and leaves data incomplete when entries are skipped under time pressure. AI-powered automatic capture removes this manual logging burden entirely. Coffee&#039;s agent ingests emails, calendar events, and call transcripts to handle capture automatically, while passive CRMs leave this work to humans.<\/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><strong>Frontline usability.<\/strong> Salesforce implementation and adoption timelines vary, yet many teams require several weeks for initial setup and several months to reach full team adoption. Pipedrive and Nutshell often reach adoption in two to four weeks for small teams. Coffee&#039;s adoption curve compresses further because reps are not asked to enter data, and the agent handles routine logging for them.<\/p>\n<p><strong>Manager visibility and reporting.<\/strong> Reporting quality flows directly from data quality. <a href=\"https:\/\/vonlabs.ai\/blog\/crm-data-entry-killing-productivity\" target=\"_blank\" rel=\"noindex nofollow\">Gartner estimates that poor data quality costs the average organization $12.9 million per year<\/a>, including forecast inaccuracy and missed follow-ups. Coffee&#039;s Pipeline Compare feature visualizes week-over-week changes automatically and replaces manual CSV exports.<\/p>\n<p><strong>Integration complexity.<\/strong> <a href=\"https:\/\/apollo.io\/insights\/how-can-integration-reduce-time-spent-on-manual-data-entry\" target=\"_blank\" rel=\"noindex nofollow\">51% of sales leaders with AI say tech silos delay or limit their AI initiatives<\/a>. Coffee consolidates CRM, enrichment, meeting intelligence, prospecting, and sequencing into one agent, while passive CRMs require separate subscriptions for each capability. Coffee&#039;s current third-party integrations run via Zapier, and deeper native integrations are on the roadmap.<\/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><strong>Customization and long-term flexibility.<\/strong> Salesforce offers the deepest customization but at the cost of <a href=\"https:\/\/resources.rework.com\/tools\/crm\/best-crm-software-2026\" target=\"_blank\" rel=\"noindex nofollow\">dedicated admin headcount and TCO of $150,000\u2013$300,000 per year at 100 seats<\/a>. Zoho and Pipedrive provide lighter customization with lower overhead. Coffee&#039;s agent architecture serves teams that prioritize automation over configuration.<\/p>\n<h2>The 2026 AI Shift From Passive Databases to Active Agents<\/h2>\n<p>The product-level differences above reflect a broader industry inflection point. <a href=\"https:\/\/technologyreview.com\/2026\/08\/12\/1141032\/scaling-ai-agents-with-trustworthy-data\" target=\"_blank\" rel=\"noindex nofollow\">A 2026 MIT Technology Review survey of 300 data and technology executives found that AI agents have access to an average of only 45% of company data overall<\/a>, and <a href=\"https:\/\/technologyreview.com\/2026\/08\/12\/1141032\/scaling-ai-agents-with-trustworthy-data\" target=\"_blank\" rel=\"noindex nofollow\">66% of data laggards say legacy data systems limit AI agent scaling<\/a>. The root cause is architectural, because passive CRMs were built for human-readable dashboards rather than the millisecond decision loops that agents require.<\/p>\n<p><a href=\"https:\/\/elementum.ai\/blog\/crm-automation\" target=\"_blank\" rel=\"noindex nofollow\">By the end of 2026, 40% of enterprise applications will include task-specific AI agents, up from less than 5% in 2025, according to Gartner<\/a>. Yet <a href=\"https:\/\/forbes.com\/councils\/forbestechcouncil\/2026\/06\/02\/agentic-ai-readiness-is-a-data-problem-not-an-ai-problem\" target=\"_blank\" rel=\"noindex nofollow\">Harvard Business Review has reported that only about 3% of companies&#039; data meets basic quality standards<\/a>, which becomes critical when an agent acts autonomously instead of a human reviewing output. Coffee&#039;s architecture addresses this directly, because the agent ingests emails, calendar events, and call transcripts to build a structured, ground-truth data layer before any intelligence is generated.<\/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<p><a href=\"https:\/\/www.nannyml.com\/blog\/91-of-ml-perfomance-degrade-in-time\" target=\"_blank\" rel=\"noindex nofollow\">In a 2022 study of four ML models across healthcare, transportation, finance, and weather datasets, 91% experienced quality degradation over time since their last training cycle.<\/a> Adding an AI feature to a passive CRM does not fix the underlying data problem, and it scales the problem instead.<\/p>\n<h2>Best-Fit Scenarios by Company Size and Primary Pain Point<\/h2>\n<p><strong>10\u201320 employees.<\/strong> Teams at this stage have outgrown spreadsheets but experience HubSpot and Pipedrive as expensive manual chores. SMB companies with 10\u2013100 employees often achieve basic CRM adoption, yet implementation and daily use remain challenging. Coffee&#039;s Standalone CRM fits these teams well, because the agent manages the system of record from day one and removes configuration overhead.<\/p>\n<p><strong>21\u201350 employees.<\/strong> Teams in this range often run an existing HubSpot or Pipedrive instance with adoption problems. A full platform migration introduces risks of sales productivity impacts for several weeks after cutover. Coffee&#039;s Companion App offers a lower-risk path, since the agent layers onto the existing system, writes clean data back, and removes migration risk entirely.<\/p>\n<p><strong>51\u2013200 employees.<\/strong> At this scale, Salesforce or HubSpot usually sits at the center of the stack. The primary issue is not the platform but the data quality feeding it. <a href=\"https:\/\/laxis.com\/blog\/state-of-ai-sales-agent-2026\" target=\"_blank\" rel=\"noindex nofollow\">Broken CRM write-back is the single most-cited failure mode for AI sales agents<\/a>. Coffee&#039;s Companion App resolves this by acting as the data-in layer, preserving existing workflows, quotas, forecasting logic, and required fields while keeping the system of record accurate without human effort.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Choose your Coffee deployment model<\/strong><\/a>, either as a standalone AI-first CRM or as a companion agent on top of Salesforce or HubSpot.<\/p>\n<h2>Operational and Long-Term Considerations for CRM Success<\/h2>\n<p>Cross-functional ownership often determines whether a CRM succeeds. <a href=\"https:\/\/centricconsulting.com\/blog\/why-did-your-crm-project-fail-change-management_eas\" target=\"_blank\" rel=\"noindex nofollow\">Most organizations spend 80% of their CRM implementation effort on technology configuration and only 20% on adoption and process optimization<\/a>. <a href=\"https:\/\/huble.com\/blog\/what-goes-wrong-in-crm-migrations\" target=\"_blank\" rel=\"noindex nofollow\">A named executive sponsor from the commercial side, typically a CRO, CMO, or COO, should own CRM migrations internally<\/a>, because IT-owned migrations tend to succeed technically but fail commercially.<\/p>\n<p>Data hygiene operates as an ongoing operational cost rather than a one-time migration task. B2B contact data decays at about 22.5% per year on average, with rates reaching up to 70% in high-turnover sectors, so a six-month migration timeline can degrade a substantial portion of records before cutover. An agent that continuously ingests live signals from email and calendar reduces this decay structurally by refreshing records in real time.<\/p>\n<h2>Risks, Limitations, and Common Misconceptions<\/h2>\n<p>Software alone does not fix process problems. Estimates of CRM failure rates have varied widely (often 30\u201370%), with user adoption frequently cited as a primary non-technical cause. Switching platforms without addressing the underlying data entry burden produces the same outcome on a new license.<\/p>\n<p>AI features in passive CRMs differ from agent architecture. <a href=\"https:\/\/elementum.ai\/blog\/crm-automation\" target=\"_blank\" rel=\"noindex nofollow\">AI-powered CRM automation does not fix bad data, and it scales it instead<\/a>. A Salesforce Einstein or HubSpot AI feature operating on incomplete records generates confident but wrong outputs. <a href=\"https:\/\/venturebeat.com\/resources\/agent-context-layers-enterprises-governing-their-ai-data-are-catching-twice-as-many-bad-answers-as-the-ones-who-arent\" target=\"_blank\" rel=\"noindex nofollow\">68% of enterprises have traced a confident but wrong AI agent answer to missing or inconsistent business context in the past six months<\/a>.<\/p>\n<p>Coffee&#039;s Companion App requires authentication to the existing CRM and currently integrates with third-party tools via Zapier. Teams with highly regulated environments or enterprise-scale custom objects should evaluate fit carefully. Coffee is not designed for organizations with 200+ seat deployments that require multi-year security reviews.<\/p>\n<h2>Decision Framework: Matching Options to Your Constraints<\/h2>\n<table>\n<thead>\n<tr>\n<th>Primary Constraint<\/th>\n<th>Best-Fit Option<\/th>\n<th>Key Trade-Off<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>License cost is the primary driver<\/td>\n<td>Zoho CRM or Pipedrive<\/td>\n<td>Lower cost with passive architecture unchanged, so data quality remains human-dependent<\/td>\n<\/tr>\n<tr>\n<td>Salesforce complexity is the primary driver<\/td>\n<td>HubSpot or Nutshell<\/td>\n<td>Faster adoption than Salesforce and simpler configuration, yet still requires manual data entry<\/td>\n<\/tr>\n<tr>\n<td>Data quality and adoption are the primary drivers; no existing CRM<\/td>\n<td>Coffee Standalone CRM<\/td>\n<td>Agent handles data in, provides the fastest path to accurate pipeline visibility, and works best for teams under 50<\/td>\n<\/tr>\n<tr>\n<td>Data quality and adoption are the primary drivers; Salesforce or HubSpot is entrenched<\/td>\n<td>Coffee Companion App<\/td>\n<td>No migration risk, with the agent writing clean data to the existing system at an additive seat cost<\/td>\n<\/tr>\n<tr>\n<td>Microsoft ecosystem dependency<\/td>\n<td>Dynamics 365<\/td>\n<td>Deep Microsoft integration, 45% of organizations find CRM data unprepared for AI use, and high implementation overhead<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Frequently Asked Questions About Salesforce Alternatives<\/h2>\n<h3>How long does implementation typically take?<\/h3>\n<p>Implementation timelines vary significantly by platform and team size. For teams under 25 users, HubSpot can be functional in 2\u20138 weeks, while Salesforce typically requires 3\u20138 weeks for an equivalent build. Mid-market organizations with 25\u2013150 users should plan 8\u201316 weeks for either platform when real automation is involved. Enterprise deployments with 150+ users and custom objects can run 4\u20139 months. Coffee&#039;s Standalone CRM connects to Google Workspace or Microsoft 365 and begins populating records immediately, which compresses implementation to days for small teams. The Companion App deploys via authentication to an existing Salesforce or HubSpot instance and removes the migration timeline entirely.<\/p>\n<h3>What is the migration effort from Salesforce?<\/h3>\n<p>Migrating from Salesforce is consistently more complex than vendors quote. CRM migrations routinely take 6\u201318 months, cost 2\u20133x the original budget estimate, and almost always lose more data than anticipated. The most common failure points include dirty source data, incomplete field mapping, broken automation logic that cannot transfer between platforms, and lost activity history. No migration tool can transfer Salesforce Process Builder flows or Apex triggers, so every automation must be manually audited and rebuilt in the target system. Sales productivity often drops for several weeks after cutover as reps learn the new system. Coffee&#039;s Companion App sidesteps this entirely, because the agent layers onto the existing Salesforce instance, so there is no migration, no cutover risk, and no productivity dip.<\/p>\n<h3>How do integrations and data quality compare across options?<\/h3>\n<p>All passive CRMs in this comparison, including HubSpot, Zoho, Pipedrive, Dynamics 365, Attio, and Nutshell, require separate subscriptions for enrichment, meeting intelligence, and sales engagement. This fragmentation forces reps to toggle between multiple tools to assemble a complete customer view, and data quality depends entirely on how consistently they enter information across those tools. Coffee consolidates CRM, enrichment, meeting recording and transcription, prospecting via Lead Finder, and email sequencing via Campaigns into one agent. The agent writes structured data back to the system of record automatically. For teams using Coffee as a Companion App on Salesforce or HubSpot, third-party integrations currently run via Zapier, and deeper native integrations are on the product roadmap. Coffee is SOC 2 Type 2 and GDPR compliant, and data is not used to train public models.<\/p>\n<h3>How do reporting, scalability, and security differ in 2026?<\/h3>\n<p>Reporting quality reflects the underlying data quality. Passive CRMs generate reports from whatever reps enter, which means pipeline reviews are only as accurate as the least disciplined rep on the team. Coffee&#039;s Pipeline Compare feature generates week-over-week pipeline changes automatically from agent-captured data, replaces manual CSV exports, and removes the interrogation dynamic from pipeline reviews. On scalability, Coffee&#039;s Standalone CRM is designed for teams up to roughly 200 seats, while larger enterprises with complex custom workflows are better served by Salesforce or Dynamics 365 with Coffee&#039;s Companion App handling the data-in layer. On security, Coffee is SOC 2 Type 2 and GDPR compliant. Salesforce and HubSpot carry enterprise-grade security certifications appropriate for regulated industries, and heavily regulated sectors like healthcare and finance that require multi-year security reviews remain outside Coffee&#039;s current target profile.<\/p>\n<h2>Conclusion: Choosing the Right Path Forward<\/h2>\n<p>The core problem with every passive CRM, including Salesforce, is that data quality depends on human discipline, and human discipline under sales pressure is unreliable. Switching from Salesforce to HubSpot, Zoho, or Pipedrive reduces cost or complexity but does not change this dynamic. The only architectural path to &quot;good data in, good data out&quot; is an agent that handles data entry autonomously and ingests emails, calendar events, and call transcripts without waiting for a rep to log them.<\/p>\n<p>For teams starting fresh or replacing a spreadsheet, Coffee&#039;s Standalone CRM deploys the agent as the system of record. For teams with Salesforce or HubSpot already entrenched, Coffee&#039;s Companion App deploys the agent as the data-in layer without requiring a migration. Both paths remove the manual entry burden that is degrading pipeline intelligence across the market.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Deploy Coffee&#039;s AI agent<\/strong><\/a> and put it to work on your CRM data today.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Explore the best Salesforce replacements for 2026. Coffee auto-logs activity, enriches records, and cuts manual entry. See pricing and switch today.<\/p>\n","protected":false},"author":11,"featured_media":8637,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-8638","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\/8638","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=8638"}],"version-history":[{"count":0,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/8638\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media\/8637"}],"wp:attachment":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media?parent=8638"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/categories?post=8638"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/tags?post=8638"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}