{"id":430,"date":"2025-11-17T05:00:29","date_gmt":"2025-11-17T05:00:29","guid":{"rendered":"https:\/\/blog.coffee.ai\/feature-set-relevant-to-sales-processes-find-top-sales-apps-integrating-with-salesforce\/"},"modified":"2026-07-20T05:06:05","modified_gmt":"2026-07-20T05:06:05","slug":"feature-set-relevant-to-sales-processes-find-top-sales-apps-integrating-with-salesforce","status":"publish","type":"post","link":"https:\/\/www.coffee.ai\/articles\/feature-set-relevant-to-sales-processes-find-top-sales-apps-integrating-with-salesforce","title":{"rendered":"Best Salesforce Sales Apps to Automate Data Entry in 2026"},"content":{"rendered":"<p><em>Written by: Doug Camplejohn, CEO &amp; Co-Founder, Coffee | Last updated: July 19, 2026<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways for Salesforce Automation in 2026<\/h2>\n<ul>\n<li>Sales reps spend 65\u201371% of their time on non-selling tasks, so automation depth is the primary evaluation criterion for Salesforce tools in 2026.<\/li>\n<li>Most point solutions cover only fragments of the data-entry burden, which forces teams to maintain separate tools for capture, enrichment, and pipeline intelligence.<\/li>\n<li>Agent-based solutions that write structured data directly to Salesforce objects outperform layered apps by removing manual input and shrinking stack complexity.<\/li>\n<li>Full data-entry automation becomes realistic when tools unify structured and unstructured data sources without adding admin overhead or creating proprietary silos.<\/li>\n<li><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>See Coffee\u2019s pricing and start your trial<\/strong><\/a> to eliminate manual data entry and consolidate your Salesforce automation stack.<\/li>\n<\/ul>\n<h2>How This Comparison Scores Salesforce Automation Tools<\/h2>\n<p>Every tool in this comparison is scored against six criteria:<\/p>\n<ol>\n<li><strong>Depth of data-entry elimination:<\/strong> Does the tool remove human input entirely, or does it only reduce it?<\/li>\n<li><strong>Unification of structured and unstructured data:<\/strong> Can it process both CRM fields and raw inputs like call transcripts or emails?<\/li>\n<li><strong>Integration effort with existing Salesforce instances:<\/strong> How much admin work is required to connect and maintain the tool?<\/li>\n<li><strong>Ongoing administrative burden:<\/strong> Does the tool create its own maintenance overhead?<\/li>\n<li><strong>Pipeline visibility without spreadsheets:<\/strong> Does it surface deal intelligence automatically?<\/li>\n<li><strong>Total cost of ownership:<\/strong> What is the all-in cost including licenses, admin time, and adjacent tools required to fill gaps?<\/li>\n<\/ol>\n<h2>Comparison Table: Top Five Salesforce Automation Options<\/h2>\n<table>\n<thead>\n<tr>\n<th>Tool<\/th>\n<th>Stack Consolidation<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Salesforce Flow<\/td>\n<td>Native, no additional license, but <a href=\"https:\/\/digitalmass.com\/insights\/salesforce-flow-technical-debt-automation-sprawl-2026\" target=\"_blank\" rel=\"noindex nofollow\">creates automation debt at scale<\/a><\/td>\n<\/tr>\n<tr>\n<td>Gong<\/td>\n<td>Requires CRM, enrichment, and sequencing tools alongside it<\/td>\n<\/tr>\n<tr>\n<td>DocuSign<\/td>\n<td>Standalone contract layer, does not replace CRM data entry<\/td>\n<\/tr>\n<tr>\n<td>Celigo<\/td>\n<td>Requires all source tools to remain active, adds integration admin<\/td>\n<\/tr>\n<tr>\n<td>Coffee<\/td>\n<td>Replaces enrichment, note-taking, and pipeline reporting tools as a Salesforce Companion App<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>The table above provides a high-level view of how these tools affect stack consolidation. The following sections examine each tool in detail, ranked by their ability to eliminate manual data entry and reduce Salesforce admin work.<\/p>\n<h2>Ranked Comparison of Salesforce Automation Tools<\/h2>\n<h3>1. Coffee (Agent Layer for Capture, Enrichment, and Intelligence)<\/h3>\n<p>Coffee deploys as a Companion App on top of existing Salesforce instances. After connecting Google Workspace or Microsoft 365, the agent auto-creates contacts and companies, logs activities, enriches records with job titles, funding data, and LinkedIn profiles, and writes summaries back to Salesforce automatically. <a href=\"https:\/\/www.coffee.ai\/changelog\" target=\"_blank\">Improved summary templates released in November 2025 are customizable and writable back to Salesforce<\/a>. The agent joins calls via Zoom, Teams, or Meet, generates post-call summaries structured to BANT, MEDDIC, or SPICED, and tracks pipeline changes week-over-week without spreadsheets. No other tool in this list performs all of these functions without additional point solutions.<\/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<h3>2. Salesforce Flow (Native Process Automation)<\/h3>\n<p>Flow is the native process automation layer inside Salesforce and the logical starting point for any automation strategy. <a href=\"https:\/\/revenuegrid.com\/blog\/what-does-salesforce-automation-look-like-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">Salesforce ended support for Workflow Rules and Process Builder on December 31, 2025<\/a>, which makes Flow the only supported declarative option. It handles record-triggered updates, approval routing, and field population well at small scale. However, <a href=\"https:\/\/linkedin.com\/pulse\/why-salesforce-automations-fail-scale-perigeon-xbudf\" target=\"_blank\" rel=\"noindex nofollow\">Flows break silently when records are modified by integrations, scheduled jobs, or data loads<\/a>, which creates a critical failure mode for teams relying on third-party enrichment or integration platforms. <a href=\"https:\/\/www.pagelines.com\/blog\/salesforce-flow-10-second-limit\" target=\"_blank\" rel=\"noindex nofollow\">Flows approaching 10 seconds of CPU time hit Salesforce&#8217;s practical ceiling (the former 2000-element limit having been removed)<\/a>, and there is no requirement for test coverage before production deployment. Flow automates processes, but it does not capture or enrich data.<\/p>\n<h3>3. Gong (Conversation Intelligence for Call Data)<\/h3>\n<p>Gong records, transcribes, and analyzes sales calls, <a href=\"https:\/\/nimitai.com\/blog\/automated-call-scoring\" target=\"_blank\" rel=\"noindex nofollow\">lifting call coverage from the typical manual baseline of ~3% to 100%<\/a>. It surfaces deal risk signals and coaching insights from conversation data. The limitation is scope, because Gong captures what is said on calls but does not create or enrich contact records, log email activity, or generate pipeline forecasts from structured CRM data. Teams using Gong still require a separate enrichment tool, a CRM admin layer, and a forecasting solution.<\/p>\n<h3>4. ZoomInfo (Firmographic and Contact Enrichment)<\/h3>\n<p>ZoomInfo provides firmographic and contact enrichment at scale, keeping Salesforce records current with job changes, funding rounds, and technographic data. It closes the enrichment gap but does not capture activity data, process call transcripts, or automate workflow logic. <a href=\"https:\/\/stealthagents.com\/research\/ai-sales-tools-adoption-statistics-2026\" target=\"_blank\" rel=\"noindex nofollow\">Mid-market companies report 68% AI sales tool adoption<\/a> while maintaining separate licenses for conversation intelligence (41%), outreach (52%), and forecasting (38%). ZoomInfo usually sits in a stack that still requires manual stitching.<\/p>\n<h3>5. Celigo (Integration Platform for System Sync)<\/h3>\n<p>Celigo automates data synchronization between Salesforce and adjacent systems such as ERP, billing, and marketing automation, which reduces manual re-entry across platforms. It functions as an integration layer, not a full automation layer, because it moves data that humans or other tools have already created. <a href=\"https:\/\/apollo.io\/insights\/why-are-mid-market-revenue-teams-consolidating-their-gtm-stack-into-fewer-platforms\" target=\"_blank\" rel=\"noindex nofollow\">Every added platform compounds sync failures, admin overhead, and vendor management burden<\/a>, and Celigo requires all source tools to remain active and maintained.<\/p>\n<h3>6. DocuSign (Contract Workflow Automation)<\/h3>\n<p><a href=\"https:\/\/www.docusign.com\/deloitte-agreement-study\" target=\"_blank\" rel=\"noindex nofollow\">A Deloitte study found that DocuSign delivers 36% efficiency gains<\/a> measured as reduction in manual effort and cycle time on agreement workflows. DocuSign&#8217;s AI layer reduces manual drafting and approval routing within the contract lifecycle. It does not touch CRM data entry, call capture, or pipeline reporting. <a href=\"https:\/\/docusign.com\/en-gb\/blog\/capitalising-on-AI-deloitte-2026\" target=\"_blank\" rel=\"noindex nofollow\">65% of organizations continue to juggle four or more separate agreement tools<\/a>, and DocuSign typically adds to that count rather than reducing it.<\/p>\n<h3>7. Salesforce Agentforce (Enterprise-Grade AI Agents)<\/h3>\n<p>Agentforce 360 reached general availability on October 14, 2025, with ARR surpassing $500 million by December 2025. It delivers autonomous agents for lead qualification, meeting booking, and pipeline updates using the Atlas Reasoning Engine. <a href=\"https:\/\/digitalapplied.com\/blog\/crm-ai-agent-salesforce-hubspot-zoho-2026-guide\" target=\"_blank\" rel=\"noindex nofollow\">Total cost starts at $300\/user\/month and scales to $550+\/user\/month for full editions<\/a>. Agentforce is purpose-built for large Salesforce-native organizations and carries significant implementation complexity. For mid-market teams, the cost and configuration overhead often exceed the automation benefit.<\/p>\n<h3>8. Zapier (Lightweight Workflow Automation)<\/h3>\n<p>Zapier connects sales tools via trigger-action workflows and added lightweight AI agents in 2025. It reduces manual re-entry between disconnected systems but does not capture unstructured data, enrich records, or provide pipeline intelligence. <a href=\"https:\/\/lagrowthmachine.com\/best-ai-agents-sales-automation\" target=\"_blank\" rel=\"noindex nofollow\">Zapier provides limited autonomy and reasoning capabilities compared to full agent platforms<\/a>. It works best as a bridge between tools that already exist, not as a replacement for any of them.<\/p>\n<h2>Full Data-Entry Automation in 2026<\/h2>\n<p>Field sales reports show that full CRM data entry automation remains rare in 2026. The gap between what is technically possible and what teams have actually deployed stays wide. Agent-based tools that ingest emails, calendars, and call transcripts can eliminate most manual input when they write structured data back to CRM objects directly instead of storing it in proprietary silos. <a href=\"https:\/\/revenuegrid.com\/blog\/einstein-activity-capture-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">Einstein Activity Capture has historically stored data on AWS rather than inside Salesforce objects, with an optional Summer &#8217;25 setting to write emails as native records, and does not natively support custom objects<\/a>, so it cannot serve as a complete data-entry replacement for most Salesforce configurations.<\/p>\n<h2>Why Revenue Teams Are Leaving Salesforce-Centric Stacks<\/h2>\n<p>The core issue rarely comes from Salesforce itself and usually comes from the stack required to make Salesforce useful. The average sales rep now juggles more than ten tools daily while spending only 30% of their time actually selling. Each point solution added to a Salesforce instance creates a new integration dependency, a new admin responsibility, and a new source of conflicting data. <a href=\"https:\/\/thesmarketers.com\/blogs\/revops-b2b-2026\" target=\"_blank\" rel=\"noindex nofollow\">When multiple AI tools surface different next-best-action recommendations to the same rep, trust in AI drops fast and adoption follows<\/a>. <a href=\"https:\/\/apollo.io\/insights\/why-are-mid-market-revenue-teams-consolidating-their-gtm-stack-into-fewer-platforms\" target=\"_blank\" rel=\"noindex nofollow\">94% of sales organizations planned to consolidate their tech stack in 2024\u20132025<\/a>, and the primary driver extends beyond cost to the recognition that fragmented stacks produce fragmented data, and fragmented data produces unreliable AI outputs.<\/p>\n<h2>How Agent Tools Differ from Layered Apps<\/h2>\n<p>Point solutions automate a single job: Gong captures calls, ZoomInfo enriches records, and Celigo syncs systems. Each requires configuration, maintenance, and a human to interpret outputs across tools. An agent layer operates differently, because it ingests multiple data streams, structures them, and writes the result back to the system of record without human intervention at any step. 54% of sellers have already used AI agents. The distinction that matters operationally is whether the agent writes to Salesforce objects, which makes data available via the API, reportable in dashboards, and usable by downstream automations, or stores data in a proprietary layer that requires manual export to be useful. If you want an agent that writes clean data directly to your Salesforce instance without proprietary silos, Coffee provides that capability out of the box.<\/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.coffee.ai\/pricing\" target=\"_blank\"><strong>Deploy Coffee&#8217;s agent in your Salesforce instance<\/strong><\/a> to start writing clean data automatically.<\/p>\n<h2>Best-Fit Automation Guidance by Team Size<\/h2>\n<p><strong>Small growing teams (1\u201320 reps):<\/strong> Native Salesforce Flow covers basic process automation without additional cost, which makes it the right foundation at this stage. Flow does not capture activity data, so the priority investment should be an agent that logs emails, meetings, and calls automatically to fill that gap. At this size, the cost of Agentforce or enterprise conversation intelligence tools is disproportionate to the value. Coffee&#8217;s Companion App provides full activity capture, enrichment, and meeting intelligence at a seat-based price that scales with the team.<\/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>Established mid-market teams (20\u2013100 reps already on Salesforce):<\/strong> These teams typically carry 8\u201312 tools with overlapping functions. <a href=\"https:\/\/leadpipe.com\/blog\/revops-stack-consolidation-2026\" target=\"_blank\" rel=\"noindex nofollow\">AI agents are collapsing enrichment waterfalls, note-takers, lead-scoring engines, and data quality patchers into single prompts<\/a>. As noted earlier, the majority of sales organizations are actively consolidating their stacks. For teams at this stage, the evaluation question shifts from which point solution to add next to which agent layer can replace the most tools while writing the cleanest data back to Salesforce. Teams at this stage gain the most from a solution that handles data in (capture, enrichment, activity logging) and data out (pipeline intelligence, forecasting inputs) without requiring a dedicated admin to maintain it.<\/p>\n<h2>Operational Considerations and Risks of Salesforce Automation<\/h2>\n<p>Change management is the most common failure mode for automation projects. Over 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value or inadequate risk controls. Teams that layer automation on top of dirty data accelerate the production of dirty outputs. The correct sequence, <a href=\"https:\/\/revenuegrid.com\/blog\/what-does-salesforce-automation-look-like-in-2026\" target=\"_blank\" rel=\"noindex nofollow\">recommended by Salesforce MVPs<\/a>, is activity data capture first, process automation second, and AI intelligence third.<\/p>\n<p>Point solutions also carry hidden maintenance costs that extend beyond the license fee. <a href=\"https:\/\/digitalmass.com\/insights\/salesforce-flow-technical-debt-automation-sprawl-2026\" target=\"_blank\" rel=\"noindex nofollow\">Salesforce Flow has no requirement for test coverage before production deployment<\/a>, which allows organizations to accumulate automation debt through redundant flows, conflicting logic, and hard-coded dependencies. Every additional tool added to a Salesforce org compounds this risk by introducing new integration points that can fail silently. The result is predictable, because <a href=\"https:\/\/coommit.com\/blog\/sales-tech-stack-consolidation-2026\" target=\"_blank\" rel=\"noindex nofollow\">most organizations find that 30\u201350% of paid sales seats show zero log-ins in the last 60 days<\/a>, which directly indicates that tools were purchased but never fully adopted as the stack became too complex to use.<\/p>\n<h2>Decision Framework and Automation Checklist<\/h2>\n<p>Use the following checklist to match automation options to your current stack and team size:<\/p>\n<ul>\n<li>If your reps manually log calls and meetings after every interaction, prioritize an agent with automatic activity capture that writes to Salesforce objects.<\/li>\n<li>If your Salesforce records lack job titles, funding data, or LinkedIn profiles, add enrichment as a standalone tool or as part of an agent that includes it.<\/li>\n<li>If you have more than 50 active Flows and no governance documentation, audit for automation debt before adding new automation layers.<\/li>\n<li>If you are paying separately for conversation intelligence, enrichment, and pipeline reporting, evaluate whether a unified agent replaces all three.<\/li>\n<li>If your pipeline reviews still rely on CSV exports or manual slide preparation, the data-out problem remains unsolved regardless of what data-in tools you have.<\/li>\n<li>If more than one tool is surfacing conflicting next-step recommendations to reps, consolidate to a single intelligence layer before expanding automation.<\/li>\n<\/ul>\n<h2>Frequently Asked Questions About Agent-Based Salesforce Automation<\/h2>\n<h3>How long does it take to implement agent-based Salesforce automation?<\/h3>\n<p>Implementation time depends on the scope of the agent and the complexity of the existing Salesforce configuration. A Companion App like Coffee connects to Salesforce through a simple authentication flow and begins capturing activity data immediately, so most teams see the agent logging contacts, activities, and enrichment within the first session. Full configuration of meeting templates, summary formats, and pipeline views typically takes days, not weeks. This timeline contrasts with enterprise platforms like Agentforce, where implementation often extends to months due to custom agent configuration, data model mapping, and governance requirements. For mid-market teams, a practical benchmark states that if the tool requires a dedicated Salesforce admin to go live, the implementation cost should factor into the total cost of ownership evaluation.<\/p>\n<h3>What migration effort is required when adding an agent layer to an existing Salesforce instance?<\/h3>\n<p>Adding an agent layer to Salesforce does not require migrating existing data or reconfiguring the org. The agent reads from and writes to existing Salesforce objects such as contacts, accounts, activities, and opportunities using the standard API. The primary prerequisite is data hygiene, because agents that ingest clean records produce reliable outputs, while agents operating on duplicate-heavy or incomplete data amplify existing quality problems. Teams should audit for duplicate contacts and incomplete required fields before activating enrichment or pipeline intelligence features. Coffee&#8217;s agent handles ongoing enrichment automatically after connection, so the migration effort becomes a one-time data quality review rather than a sustained project.<\/p>\n<h3>How do agent tools handle security and compliance in 2026?<\/h3>\n<p>Security requirements for agent tools in 2026 center on three areas: data residency, model training practices, and compliance certifications. Coffee is SOC 2 Type 2 certified and GDPR compliant. Customer data is not used to train public models, which matters for teams handling sensitive deal information or operating under data processing agreements with enterprise customers. When evaluating any agent tool, key questions include whether the tool stores data inside Salesforce objects, which makes it subject to Salesforce&#8217;s own security model, or in a proprietary data store outside the org, and whether the vendor can provide a Data Processing Agreement that meets your organization&#8217;s legal requirements. Teams in heavily regulated industries such as healthcare and financial services should conduct a full security review before deployment.<\/p>\n<h3>How deeply does Coffee integrate with Salesforce objects and workflows?<\/h3>\n<p>Coffee&#8217;s Companion App writes data back to standard Salesforce objects including contacts, accounts, activities, and opportunities. Summary templates are customizable and sync directly to Salesforce, so post-call notes, action items, and enrichment data appear in the correct record without manual entry. The agent also supports pipeline intelligence features such as week-over-week deal tracking, stall detection, and forecast inputs that draw on the structured data it has written to Salesforce over time. Integrations with tools like QuickBooks and Stripe extend the agent&#8217;s data capture to financial events, automatically syncing invoices and payment statuses into the CRM. For teams with custom objects or complex workflow requirements, Coffee&#8217;s current integration depth covers the majority of mid-market use cases, with deeper roadmap integrations in development.<\/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>Conclusion: Choosing a Salesforce Automation Path That Eliminates Manual Entry<\/h2>\n<p>The tools evaluated in this comparison address real problems. Salesforce Flow automates record-triggered processes. Gong captures conversation data. ZoomInfo enriches contact records. DocuSign accelerates contract cycles. Celigo synchronizes systems. Each solves one part of the manual data entry problem, and each requires the others to cover what it cannot do alone.<\/p>\n<p>\u201cThe secret sauce for sales AI agents is unified data. Stand-alone agents without comprehensive customer context tend to fail.\u201d That statement reflects the operational reality for mid-market teams in 2026, because point solutions produce point results. The teams that eliminate manual data entry entirely are the ones that replace the stack with an agent that handles capture, enrichment, and intelligence in a single layer.<\/p>\n<p>Coffee is the only agent-based solution that deploys as a Salesforce Companion App, writes clean structured data back to Salesforce objects, unifies call transcripts and email activity with firmographic enrichment, and delivers pipeline intelligence without additional tools or ongoing manual effort. For RevOps and sales leaders who have already invested in Salesforce and want to stop paying for the privilege of maintaining it manually, the agent layer becomes the next and final automation investment.<\/p>\n<p><a href=\"https:\/\/www.coffee.ai\/pricing\" target=\"_blank\"><strong>Start eliminating manual data entry with Coffee today<\/strong><\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Stop wasting 70% of your day on manual tasks. Coffee automates Salesforce data entry and workflows so your team can sell more. Start your free trial.<\/p>\n","protected":false},"author":11,"featured_media":8229,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-430","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\/430","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=430"}],"version-history":[{"count":4,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/430\/revisions"}],"predecessor-version":[{"id":8230,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/posts\/430\/revisions\/8230"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media\/8229"}],"wp:attachment":[{"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/media?parent=430"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/categories?post=430"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.coffee.ai\/articles\/wp-json\/wp\/v2\/tags?post=430"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}