{"id":3608,"date":"2026-03-24T23:29:20","date_gmt":"2026-03-24T23:29:20","guid":{"rendered":"https:\/\/aidevlab.com\/?page_id=3608"},"modified":"2026-03-29T18:54:00","modified_gmt":"2026-03-29T18:54:00","slug":"accounting-ai-assistant","status":"publish","type":"page","link":"https:\/\/aidevlab.com\/case-studies\/accounting-ai-assistant\/","title":{"rendered":"Accounting AI Assistant"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"3608\" class=\"elementor elementor-3608\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3c25f7d ct-section-stretched elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"3c25f7d\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-abe6bf5\" data-id=\"abe6bf5\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-548c96a elementor-widget elementor-widget-html\" data-id=\"548c96a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<!-- \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\r\n     CASE STUDY: FINANCIAL SERVICES AI PLATFORM\r\n     Page slug: \/case-studies\/accounting-ai-assistant\/\r\n     Three sections \u2014 paste each as its own widget\r\n\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550 -->\r\n\r\n\r\n<!-- \u2550\u2550 SECTION A: HERO \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550 -->\r\n<style>\r\n@keyframes acc-fadeUp { from{opacity:0;transform:translateY(18px)} to{opacity:1;transform:translateY(0)} }\r\n\r\n.acc-hero {\r\n  background: #0A1628;\r\n  padding: 140px var(--gutter,clamp(1.5rem,5vw,4.5rem)) 80px;\r\n  position: relative; overflow: hidden;\r\n}\r\n.acc-hero-glow {\r\n  position: absolute; top: 10%; left: 40%;\r\n  width: 600px; height: 400px;\r\n  background: radial-gradient(ellipse, rgba(20,58,162,0.25) 0%, transparent 68%);\r\n  pointer-events: none;\r\n}\r\n.acc-hero-inner { max-width: 1160px; margin: 0 auto; position: relative; z-index: 1; }\r\n.acc-hero-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 5rem; align-items: center; }\r\n\r\n.acc-back {\r\n  display: inline-flex; align-items: center; gap: 0.5rem;\r\n  font-size: 0.78rem; color: rgba(220,230,245,0.42);\r\n  text-decoration: none; font-family: 'DM Sans', system-ui, sans-serif;\r\n  margin-bottom: 2rem; transition: color 0.2s;\r\n  opacity: 0; animation: acc-fadeUp 0.6s 0.1s forwards;\r\n}\r\n.acc-back:hover { color: rgba(220,230,245,0.78); }\r\n\r\n.acc-industry {\r\n  font-size: 0.67rem; font-weight: 700; letter-spacing: 0.15em;\r\n  text-transform: uppercase; color: #3E8DE3;\r\n  font-family: 'DM Sans', system-ui, sans-serif; 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justify-content: space-between; align-items: center;\r\n  padding: 1.25rem 1.625rem; border-bottom: 1px solid rgba(255,255,255,0.06); gap: 1rem;\r\n}\r\n.acc-meta-row:last-child { border-bottom: none; }\r\n.acc-meta-lbl { font-size: 0.65rem; font-weight: 700; letter-spacing: 0.1em; text-transform: uppercase; color: rgba(220,230,245,0.28); font-family: 'DM Sans', system-ui, sans-serif; flex-shrink: 0; }\r\n.acc-meta-val { font-size: 0.875rem; color: rgba(220,230,245,0.75); font-weight: 400; font-family: 'DM Sans', system-ui, sans-serif; text-align: right; }\r\n.acc-meta-val.gold { color: #E8A820; font-weight: 600; }\r\n\r\n@media (max-width: 900px) { .acc-hero-grid { grid-template-columns: 1fr; gap: 3rem; } }\r\n<\/style>\r\n\r\n<section class=\"acc-hero adl-section\">\r\n  <div class=\"acc-hero-glow\" aria-hidden=\"true\"><\/div>\r\n  <div class=\"acc-hero-inner\">\r\n    <a href=\"\/case-studies\/\" class=\"acc-back\">\r\n      <svg width=\"14\" height=\"14\" viewBox=\"0 0 14 14\" fill=\"none\"><path d=\"M11.5 7h-9M5.5 3.5L2 7l3.5 3.5\" stroke=\"currentColor\" stroke-width=\"1.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg>\r\n      All Case Studies\r\n    <\/a>\r\n    <div class=\"acc-hero-grid\">\r\n      <div>\r\n        <div class=\"acc-industry\">Financial Services<\/div>\r\n        <h1>From Financial Data to<br><em>Decisions That Actually Get Made.<\/em><\/h1>\r\n        <p class=\"acc-hero-desc\">\r\n          A financial services firm needed more than reports. They needed AI that could read their numbers, surface what mattered, flag what was wrong, forecast what was coming, and tell their team what to do next. We built that. The work ran deep enough that the products we designed became the foundation of a standalone company.\r\n        <\/p>\r\n      <\/div>\r\n      <div class=\"acc-meta\">\r\n        <div class=\"acc-meta-row\"><span class=\"acc-meta-lbl\">Industry<\/span><span class=\"acc-meta-val\">Financial Services<\/span><\/div>\r\n        <div class=\"acc-meta-row\"><span class=\"acc-meta-lbl\">Engagement Type<\/span><span class=\"acc-meta-val\">Full product design and build<\/span><\/div>\r\n        <div class=\"acc-meta-row\"><span class=\"acc-meta-lbl\">AI Capability<\/span><span class=\"acc-meta-val\">Analysis \u00b7 Compliance \u00b7 Forecasting \u00b7 Benchmarking<\/span><\/div>\r\n        <div class=\"acc-meta-row\"><span class=\"acc-meta-lbl\">Integrations<\/span><span class=\"acc-meta-val\">QuickBooks \u00b7 NetSuite \u00b7 Xero<\/span><\/div>\r\n        <div class=\"acc-meta-row\"><span class=\"acc-meta-lbl\">Outcome<\/span><span class=\"acc-meta-val gold\">Products spun off as standalone company<\/span><\/div>\r\n      <\/div>\r\n    <\/div>\r\n  <\/div>\r\n<\/section>\r\n\r\n\r\n<!-- \u2550\u2550 SECTION B: BODY \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550 -->\r\n<style>\r\n.acc-body { background: #F5F2EB; 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font-weight: 300; font-family: 'DM Sans', system-ui, sans-serif; margin-bottom: 1.25rem; }\r\n.acc-spinoff-right p:last-child { margin-bottom: 0; }\r\n.acc-spinoff-right strong { color: rgba(220,230,245,0.85); font-weight: 500; }\r\n\r\n@media (max-width: 960px) {\r\n  .acc-two-col { grid-template-columns: 1fr; gap: 3rem; }\r\n  .acc-caps { grid-template-columns: 1fr; }\r\n  .acc-result-strip { grid-template-columns: 1fr; gap: 1.5rem; }\r\n  .acc-result-divider { display: none; }\r\n  .acc-spinoff { grid-template-columns: 1fr; gap: 2rem; }\r\n}\r\n<\/style>\r\n\r\n<section class=\"acc-body adl-section\">\r\n  <div class=\"acc-body-inner\">\r\n\r\n    <!-- Problem -->\r\n    <div class=\"acc-two-col\">\r\n      <div>\r\n        <span class=\"acc-lbl\">The Problem<\/span>\r\n        <h2>Spreadsheets full of numbers.<br><em>No one quite sure what to do next.<\/em><\/h2>\r\n        <p>The firm had data. What they did not have was intelligence. Financial teams were spending 4 to 6 weeks just to compile and review reports \u2014 trapped in tactical work that left no bandwidth for the strategic thinking the business actually needed.<\/p>\r\n        <p>Spreadsheets had stopped linking to live accounting data. Reports were static snapshots, disconnected from reality by the time anyone acted on them. Questions that should take minutes \u2014 where is money leaking, how do we compare to peers, will we have enough cash in 13 weeks \u2014 required either expensive analysts or guesswork.<\/p>\r\n        <p><strong>The deeper problem<\/strong> was structural. The gap between raw financial data and a clear action was wide enough that decisions were routinely made on instinct. Not because the team lacked capability \u2014 but because the tools they had were not built to answer the questions a finance leader actually needs answered.<\/p>\r\n        <div class=\"acc-callout\">\r\n          <p>\"We were spending weeks producing reports that were outdated by the time anyone read them. The intelligence we needed was already in the data \u2014 <em>we just could not get to it fast enough to matter.<\/em>\"<\/p>\r\n        <\/div>\r\n      <\/div>\r\n      <div>\r\n        <span class=\"acc-lbl\">The Scope<\/span>\r\n        <h2>Not one tool.<br><em>A full intelligence layer.<\/em><\/h2>\r\n        <p>This engagement was not a single AI feature bolted onto an existing workflow. We designed and built a suite of interconnected AI capabilities that addressed four distinct financial intelligence needs \u2014 each solving a different question the firm had been unable to answer reliably.<\/p>\r\n        <p>The work integrated with their existing accounting platforms \u2014 QuickBooks, NetSuite, and Xero \u2014 so the intelligence layer sat on top of systems they already used, not parallel to them.<\/p>\r\n        <p>Every output was designed to produce a decision, not a dashboard. Executive summaries with clear next steps. Compliance reports with specific fixes. Forecasts with confidence intervals. Benchmarks with prioritized recommendations. The work was done. The team just had to act on it.<\/p>\r\n      <\/div>\r\n    <\/div>\r\n\r\n    <!-- What was built \u2014 4 capabilities -->\r\n    <span class=\"acc-lbl\">What Was Built<\/span>\r\n    <h2 style=\"font-family:'Playfair Display',Georgia,serif;font-size:clamp(1.75rem,2.75vw,2.5rem);font-weight:500;line-height:1.15;letter-spacing:-0.015em;color:#140F1E;margin-bottom:0.5rem;\">Four AI capabilities.<br><em style=\"font-style:italic;color:#143AA2;\">One intelligence layer.<\/em><\/h2>\r\n    <p style=\"font-size:.95rem;color:#4A4E5A;line-height:1.82;font-weight:300;font-family:'DM Sans',system-ui,sans-serif;max-width:560px;margin-bottom:0;\">Each capability addressed a different dimension of financial intelligence \u2014 together they gave the firm a complete picture of where they stood, where they were heading, and what to do about it.<\/p>\r\n\r\n    <div class=\"acc-caps\">\r\n\r\n      <div class=\"acc-cap\">\r\n        <div class=\"acc-cap-icon\" aria-hidden=\"true\">\ud83d\udcca<\/div>\r\n        <div class=\"acc-cap-name\">Deep Financial Analysis<\/div>\r\n        <p class=\"acc-cap-desc\">Broad AI-driven analysis of financial data across 21 essential metrics \u2014 uncovering hidden patterns, exposing inefficiencies, and surfacing the risks and opportunities buried inside P&L statements that standard review misses entirely. Three views of performance delivered as executive-ready summaries with specific next steps.<\/p>\r\n        <div class=\"acc-cap-metrics\">\r\n          <span class=\"acc-cap-metric\">21 metrics<\/span>\r\n          <span class=\"acc-cap-metric\">3 P&L views<\/span>\r\n          <span class=\"acc-cap-metric\">Executive summaries<\/span>\r\n          <span class=\"acc-cap-metric\">Pattern detection<\/span>\r\n        <\/div>\r\n      <\/div>\r\n\r\n      <div class=\"acc-cap\">\r\n        <div class=\"acc-cap-icon\" aria-hidden=\"true\">\u2696\ufe0f<\/div>\r\n        <div class=\"acc-cap-name\">GAAP Compliance Analysis<\/div>\r\n        <p class=\"acc-cap-desc\">Automated scanning of financial statements against GAAP standards \u2014 identifying misreporting, flagging compliance gaps, and delivering a prioritized list of specific fixes before they become audit findings or regulatory exposure. Eliminates the expensive manual compliance review cycle entirely.<\/p>\r\n        <div class=\"acc-cap-metrics\">\r\n          <span class=\"acc-cap-metric\">Comprehensive scan<\/span>\r\n          <span class=\"acc-cap-metric\">Specific fixes<\/span>\r\n          <span class=\"acc-cap-metric\">Risk reduction<\/span>\r\n          <span class=\"acc-cap-metric\">Audit ready<\/span>\r\n        <\/div>\r\n      <\/div>\r\n\r\n      <div class=\"acc-cap\">\r\n        <div class=\"acc-cap-icon\" aria-hidden=\"true\">\ud83c\udfc6<\/div>\r\n        <div class=\"acc-cap-name\">Industry Benchmarking<\/div>\r\n        <p class=\"acc-cap-desc\">Real-world peer comparison using industry data to show exactly where the firm stands relative to competitors across 14 critical metrics. Validates performance claims, identifies the highest-priority improvement opportunities, and delivers ranked recommendations based on potential impact and achievability.<\/p>\r\n        <div class=\"acc-cap-metrics\">\r\n          <span class=\"acc-cap-metric\">14 metrics<\/span>\r\n          <span class=\"acc-cap-metric\">Peer comparison<\/span>\r\n          <span class=\"acc-cap-metric\">Ranked actions<\/span>\r\n          <span class=\"acc-cap-metric\">Real industry data<\/span>\r\n        <\/div>\r\n      <\/div>\r\n\r\n      <div class=\"acc-cap\">\r\n        <div class=\"acc-cap-icon\" aria-hidden=\"true\">\ud83d\udcc8<\/div>\r\n        <div class=\"acc-cap-name\">ML Cashflow Forecasting<\/div>\r\n        <p class=\"acc-cap-desc\">A 13-week rolling cashflow forecast built on a machine learning model that refines itself every cycle. Syncs AP, AR, and GL data in real time, flags anomalies, and merges human judgment with data science to produce reliable, actionable projections \u2014 not generic assumptions. Accuracy improves with every run.<\/p>\r\n        <div class=\"acc-cap-metrics\">\r\n          <span class=\"acc-cap-metric\">13-week forecast<\/span>\r\n          <span class=\"acc-cap-metric\">Self-improving model<\/span>\r\n          <span class=\"acc-cap-metric\">Anomaly detection<\/span>\r\n          <span class=\"acc-cap-metric\">AP\/AR\/GL sync<\/span>\r\n        <\/div>\r\n      <\/div>\r\n\r\n    <\/div>\r\n\r\n    <!-- Results -->\r\n    <div class=\"acc-result-strip adl-reveal\">\r\n      <div class=\"acc-result-item\">\r\n        <strong>$7K+<\/strong>\r\n        <span>Monthly overhead reduction identified in first analysis report<\/span>\r\n      <\/div>\r\n      <div class=\"acc-result-divider\"><\/div>\r\n      <div class=\"acc-result-item\">\r\n        <strong>$23K<\/strong>\r\n        <span>Saved in auditor fees through early GAAP misreporting detection<\/span>\r\n      <\/div>\r\n      <div class=\"acc-result-divider\"><\/div>\r\n      <div class=\"acc-result-item\">\r\n        <strong>20+ hrs<\/strong>\r\n        <span>Freed from month-end close process every single month<\/span>\r\n      <\/div>\r\n    <\/div>\r\n\r\n    <!-- Spinoff callout -->\r\n    <div class=\"acc-spinoff adl-reveal\">\r\n      <div>\r\n        <span class=\"acc-spinoff-label\">What Happened Next<\/span>\r\n        <h3>The work became<br><em>a company.<\/em><\/h3>\r\n      <\/div>\r\n      <div class=\"acc-spinoff-right\">\r\n        <p>The AI capabilities AI Dev Lab designed and built ran deep enough \u2014 and proved valuable enough \u2014 that they formed the foundation of a standalone company. The platform expanded beyond financial analysis into a full AI-powered CFO intelligence layer, serving CFO and finance leaders, accounting and private equity advisors, and business owners who needed strategic financial clarity without the cost of a full finance department.<\/p>\r\n        <p>Due to a non-compete agreement, the products were spun off independently and continue to serve hundreds of finance professionals today.<\/p>\r\n        <p><strong>This is what it looks like when an AI engagement produces something genuinely valuable.<\/strong> Not a prototype. Not a pilot. A commercially viable AI product, built from scratch, that stands on its own.<\/p>\r\n      <\/div>\r\n    <\/div>\r\n\r\n  <\/div>\r\n<\/section>\r\n\r\n\r\n<!-- \u2550\u2550 SECTION C: CTA \u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550 -->\r\n<style>\r\n.acc-cta { background: #0A1628; padding: clamp(80px,10vw,100px) var(--gutter,clamp(1.5rem,5vw,4.5rem)); position: relative; overflow: hidden; }\r\n.acc-cta::before { content: ''; position: absolute; top: 50%; left: 50%; transform: translate(-50%,-50%); width: 800px; height: 400px; background: radial-gradient(ellipse, rgba(20,58,162,0.22) 0%, transparent 68%); pointer-events: none; }\r\n.acc-cta-inner { max-width: 780px; margin: 0 auto; display: grid; grid-template-columns: 1fr 1fr; gap: 5rem; align-items: center; position: relative; z-index: 1; }\r\n.acc-cta h2 { font-family: 'Playfair Display', Georgia, serif !important; font-size: clamp(2rem,3.5vw,3rem) !important; font-weight: 500 !important; line-height: 1.12 !important; color: rgba(220,230,245,0.95); margin-bottom: 1.25rem !important; }\r\n.acc-cta h2 em { font-style: italic; color: #E8A820; font-weight: 400; }\r\n.acc-cta p { font-size: 0.95rem; color: rgba(220,230,245,0.58); line-height: 1.82; font-weight: 300; font-family: 'DM Sans', system-ui, sans-serif; margin-bottom: 2rem; }\r\n.acc-cta-btn { display: block; text-align: center; background: #259F6C; color: #fff; padding: 0.95rem 2.25rem; border-radius: 5px; text-decoration: none; font-weight: 600; font-size: 0.9rem; font-family: 'DM Sans', system-ui, sans-serif; border: 2px solid #259F6C; transition: background 0.22s, color 0.22s, transform 0.15s; }\r\n.acc-cta-btn:hover { background: #fff; color: #259F6C; transform: translateY(-1px); }\r\n.acc-cta-link { display: block; margin-top: 1rem; text-align: center; font-size: 0.82rem; color: rgba(220,230,245,0.35); text-decoration: none; font-family: 'DM Sans', system-ui, sans-serif; transition: color 0.2s; }\r\n.acc-cta-link:hover { color: rgba(220,230,245,0.65); }\r\n.acc-cta-right { background: rgba(255,255,255,0.04); border: 1px solid rgba(255,255,255,0.08); border-radius: 12px; padding: 2.25rem; }\r\n.acc-cta-right-lbl { font-size: 0.63rem; font-weight: 700; letter-spacing: 0.13em; text-transform: uppercase; color: rgba(232,168,32,0.6); font-family: 'DM Sans', system-ui, sans-serif; margin-bottom: 1.25rem; display: block; }\r\n.acc-cta-right h3 { font-family: 'Playfair Display', Georgia, serif; font-size: 1.15rem; font-weight: 500; color: rgba(220,230,245,0.9); margin-bottom: 0.875rem; line-height: 1.35; }\r\n.acc-cta-right p { font-size: 0.84rem; color: rgba(220,230,245,0.45); line-height: 1.72; font-weight: 300; font-family: 'DM Sans', system-ui, sans-serif; margin: 0; }\r\n@media (max-width: 860px) { .acc-cta-inner { grid-template-columns: 1fr; gap: 3rem; max-width: 560px; } }\r\n<\/style>\r\n\r\n<section class=\"acc-cta adl-section\">\r\n  <div class=\"acc-cta-inner\">\r\n    <div>\r\n      <h2>Your financial data already<br>holds the answers.<br><em>We build the system that reads them.<\/em><\/h2>\r\n      <p>If your team is making decisions without a clear picture of what the numbers are actually saying, that gap is worth closing. Tell us what intelligence your organization needs and we will tell you what is possible.<\/p>\r\n      <a href=\"https:\/\/tinyurl.com\/ADL-Main-Meeting\" class=\"acc-cta-btn\" target=\"_blank\" rel=\"noopener\">Start a Conversation<\/a>\r\n      <a href=\"\/case-studies\/\" class=\"acc-cta-link\">\u2190 Back to all case studies<\/a>\r\n    <\/div>\r\n    <div class=\"acc-cta-right\">\r\n      <span class=\"acc-cta-right-lbl\">What this engagement proved<\/span>\r\n      <h3>Deep AI work creates assets, not just solutions<\/h3>\r\n      <p>The most valuable AI engagements produce systems that generate compounding returns \u2014 tools your team relies on daily, insights that improve decision quality over time, and in some cases, products substantial enough to stand on their own. That is the standard we build toward on every engagement.<\/p>\r\n    <\/div>\r\n  <\/div>\r\n<\/section>\r\n\r\n<script>\r\n(function() {\r\n  const io = new IntersectionObserver(entries => {\r\n    entries.forEach(e => { if(e.isIntersecting){e.target.classList.add('visible');io.unobserve(e.target);} });\r\n  }, {threshold:0.1});\r\n  document.querySelectorAll('.acc-cap').forEach(c => io.observe(c));\r\n})();\r\n<\/script>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>All Case Studies Financial Services From Financial Data toDecisions That Actually Get Made. A financial services firm needed more than reports. They needed AI that could read their numbers, surface what mattered, flag what was wrong, forecast what was coming, and tell their team what to do next. We built that. The work ran deep [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":0,"parent":3585,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"nf_dc_page":"","footnotes":""},"class_list":["post-3608","page","type-page","status-publish","hentry"],"blocksy_meta":{"has_hero_section":"disabled","styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":6}},"featured_image_src":null,"featured_image_src_square":null,"_links":{"self":[{"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/pages\/3608","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/comments?post=3608"}],"version-history":[{"count":19,"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/pages\/3608\/revisions"}],"predecessor-version":[{"id":4233,"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/pages\/3608\/revisions\/4233"}],"up":[{"embeddable":true,"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/pages\/3585"}],"wp:attachment":[{"href":"https:\/\/aidevlab.com\/wp-json\/wp\/v2\/media?parent=3608"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}