{"id":1282,"date":"2026-07-22T05:20:24","date_gmt":"2026-07-22T05:20:24","guid":{"rendered":"https:\/\/listenlabs.ai\/articles\/financial-services-prototype-testing-2026\/"},"modified":"2026-07-22T05:20:24","modified_gmt":"2026-07-22T05:20:24","slug":"financial-services-prototype-testing-2026","status":"publish","type":"post","link":"https:\/\/listenlabs.ai\/articles\/financial-services-prototype-testing-2026\/","title":{"rendered":"Financial Services Prototype Testing: Top Platforms (2026)"},"content":{"rendered":"<p><em>Written by: Anish Rao, Head of Growth, Listen Labs<\/em><\/p>\n<h2 id=\"key-takeaways\">Key Takeaways<\/h2>\n<ul>\n<li>Financial services teams must validate flows quickly, avoid weeks of logistics, and maintain strict regulatory compliance without creating exposure.<\/li>\n<li>Traditional UX tools like UserTesting and Maze deliver moderated depth but struggle with speed, sample size, and compliance gaps for regulated flows such as KYC onboarding.<\/li>\n<li>Functional automation suites like Tricentis and UiPath excel at regression testing but provide zero qualitative or emotional insight into real user reactions.<\/li>\n<li>AI-moderated interview platforms like Listen Labs combine verified recruitment, adaptive AI moderation, Emotional Intelligence, Quality Guard fraud prevention, and enterprise compliance certifications to deliver consultant-quality reports in under 24 hours.<\/li>\n<li>Listen Labs is the only platform that meets all ten evaluation criteria for financial services prototype testing. See how it fits your research stack by <a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\">scheduling a personalized demo<\/a>.<\/li>\n<\/ul>\n<h2>Ten Criteria That Define a Fit-for-Purpose Financial Services Testing Platform<\/h2>\n<p>Ten criteria determine whether a platform is fit for purpose in regulated financial services environments:<\/p>\n<ol>\n<li>Research speed<\/li>\n<li>Depth of insight<\/li>\n<li>Sample quality and sourcing<\/li>\n<li>Methodological flexibility<\/li>\n<li>Global and multilingual reach<\/li>\n<li>Analysis effort<\/li>\n<li>Reporting transparency<\/li>\n<li>Governance and security<\/li>\n<li>Scalability<\/li>\n<li>Total operational burden<\/li>\n<\/ol>\n<p>Research speed measures how quickly a team moves from study brief to actionable findings, which is critical when <a href=\"https:\/\/getperspective.ai\/blog\/the-state-of-ai-customer-interviews-2026-mid-year-update\" target=\"_blank\" rel=\"noindex nofollow\">median time-to-readout for AI interview studies dropped from 11 days to 4 days between January and April 2026<\/a>. Depth of insight distinguishes platforms that capture emotional signals and adaptive follow-up from those that return click-path data or survey ratings.<\/p>\n<p>Sample quality and sourcing address fraud risk and demographic precision, since commodity panels carry documented risks of professional survey-takers and incentive-driven responses. Methodological flexibility covers whether a platform supports moderated depth, unmoderated scale, screen sharing, mobile recording, and mixed-method designs within a single workflow.<\/p>\n<p>Global and multilingual reach matter for teams validating products across multiple markets simultaneously. Analysis effort measures how much manual synthesis a team must perform after data collection ends. Reporting transparency determines whether findings are traceable to specific participant moments or arrive as opaque summaries.<\/p>\n<p>Governance and security are non-negotiable. GLBA&#8217;s Safeguards Rule requires administrative, technical, and physical safeguards for customer information, <a href=\"https:\/\/risktemplate.com\/blog\/2026-04-03-pii-handling-ai-llm-systems-compliance\" target=\"_blank\" rel=\"noindex nofollow\">including when processed by AI systems<\/a>, while GDPR, PCI DSS, and CPRA impose overlapping obligations on data minimization, breach notification, and third-party processor contracts. Scalability addresses whether a platform can run one study or one hundred without proportional cost increases. Total operational burden captures the hidden cost of stitching together recruitment vendors, scheduling tools, transcription services, and analysis platforms.<\/p>\n<h2>Where Traditional UX Testing Tools Fall Short for Regulated Flows<\/h2>\n<p>Platforms such as UserTesting and Maze handle study setup through researcher-configured templates and panel recruitment through their own participant networks. Moderation is either human-led, which introduces scheduling overhead and moderator variability across a multi-week field period, or unmoderated, which <a href=\"https:\/\/cleverx.com\/blog\/fintech-compliance-ux-research-methods-for-regulated-flows\" target=\"_blank\" rel=\"noindex nofollow\">is unsuitable for high-stakes regulated steps such as KYC identity verification<\/a> where a moderator must capture verbal reactions to anxiety-inducing moments. Data quality controls vary, and panel fraud remains a persistent concern in commodity recruitment networks.<\/p>\n<p>Qualitative depth is constrained by sample size economics because scheduling and moderating sessions at scale is expensive and slow. Quantitative support exists through task metrics and rating scales, but the two methodologies rarely integrate within a single study. Analysis workflow remains largely manual, with researchers exporting transcripts, tagging themes, and writing reports independently. Deliverable creation becomes a separate effort.<\/p>\n<p>Cross-study knowledge management is often absent or requires a separate repository tool such as Dovetail. For financial services teams, the compliance gap is significant. <a href=\"https:\/\/deviqa.com\/blog\/ux-testing-for-fintech-apps-what-seamless-actually-means-in-financial-services\" target=\"_blank\" rel=\"noindex nofollow\">Moderated usability testing is required for first-time KYC onboarding, high-stakes financial decisions, and error recovery flows<\/a>, yet traditional tools cannot deliver moderated depth at the sample sizes needed for statistical confidence without multi-week timelines.<\/p>\n<h2>How Functional Automation Platforms Support Testing but Miss Human Insight<\/h2>\n<p>Automation suites such as Tricentis and UiPath excel at regression testing, API contract validation, and CI\/CD integration for core transaction flows. Study setup is script-based and requires QA engineering resources rather than research expertise. Recruitment does not apply because these platforms test against synthetic environments, not real users. Moderation does not exist in the conversational sense, since test execution is deterministic and script-bound.<\/p>\n<p>Data quality controls are strong for functional correctness but irrelevant to participant authenticity. Qualitative depth is zero, and <a href=\"https:\/\/deviqa.com\/blog\/automated-testing-for-fintech-apps-what-to-automate-and-what-to-leave-manual\" target=\"_blank\" rel=\"noindex nofollow\">automated tools check if buttons exist and are clickable but cannot assess whether experiences are trustworthy, clear, or frustration-free for real users<\/a>. Quantitative support covers performance benchmarks and pass\/fail rates for defined test cases. Analysis workflow produces structured logs, not thematic insight, and deliverable creation generates test reports, not research narratives.<\/p>\n<p>Cross-study knowledge management functions as a QA artifact store rather than a consumer insight repository. The fundamental limitation for prototype testing is that automation serves as an enabler but not a substitute for layered human review in fintech UX design processes. Emotional signals such as hesitation, confusion, and delight never enter the data.<\/p>\n<h2>How AI-Moderated Interview Platforms Like Listen Labs Work<\/h2>\n<p>Listen Labs covers the full research lifecycle within a single platform. Study setup uses AI-assisted co-design, where researchers describe goals in natural language and the platform drafts structured objectives, questions, and probing context in seconds, with Auto-QA flagging issues before launch. Recruitment draws from a global panel of 30M verified respondents across 45+ countries through Listen Atlas, an AI orchestration layer that matches participants on behavioral and intent data rather than self-reported demographics alone. A dedicated recruitment ops team handles hard-to-reach segments such as enterprise decision-makers, engineers, healthcare workers, and audiences below 1% incidence rate.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773098461736-796a7724447a.png\" alt=\"Screenshot of researcher creating a study by simply typing &quot;I want to interview Gen Z on how they use ChatGPT&quot;\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Our AI helps you go from idea to implemented discussion guide in seconds.<\/em><\/figcaption><\/figure>\n<p>Moderation is conducted by an AI interviewer that probes deeper on short or interesting answers, the same way a trained human moderator would, while running hundreds of parallel conversations simultaneously. Because these conversations happen at scale, the platform must capture more than text transcripts to preserve the emotional context that human moderators naturally observe. Rich response capture includes video, audio, text, and screen recordings, including mobile screen recording on iOS, which enables prototype testing of banking app flows in realistic conditions.<\/p>\n<p>This multi-modal capture feeds Emotional Intelligence, which analyzes tone of voice, word choice, and subconscious micro-expressions built on Ekman&#8217;s universal emotions framework. The system surfaces hesitation, confusion, and delight at timestamp-level precision that transcripts alone miss. Quality Guard monitors every interview in real time for fraud, low-effort responses, AI-generated scripts, and mismatched profiles, with participants limited to three studies per month to eliminate professional survey-takers.<\/p>\n<p>Analysis workflow is automated, as the Research Agent generates key findings, themes, and personas from all interview data without manual tagging. Deliverable creation produces consultant-quality slide decks, memos, video highlight reels, and statistical charts in under a minute. Cross-study knowledge management is handled by Mission Control, which serves as the organization\u2019s source of truth across all studies and enables cross-study queries and trend tracking.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773098910279-d16bc544a32e.png\" alt=\"Listen Labs auto-generates research reports in under a minute\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Listen Labs auto-generates research reports in under a minute<\/em><\/figcaption><\/figure>\n<p>Enterprise compliance certifications include SOC 2, GDPR, ISO 27001, ISO 27701, and ISO 42001, which directly address the <a href=\"https:\/\/risktemplate.com\/blog\/2026-04-03-pii-handling-ai-llm-systems-compliance\" target=\"_blank\" rel=\"noindex nofollow\">GLBA, GDPR, PCI DSS, and CPRA requirements<\/a> that financial services teams must satisfy when sending participant data to third-party platforms. Customer data is never used for AI model training.<\/p>\n<p>With the platform landscape mapped across all three categories, the next step is to connect those capabilities to concrete research scenarios and highlight where Listen Labs becomes operationally necessary.<\/p>\n<h2>Best-Fit Use Cases for Enterprise Insights and Product Teams<\/h2>\n<p>UX research leads needing moderated depth on regulated flows such as KYC onboarding, payment authorization disclosures, and AML screening prompts require a platform that combines adaptive conversational moderation with emotional signal capture. <a href=\"https:\/\/cleverx.com\/blog\/fintech-compliance-ux-research-methods-for-regulated-flows\" target=\"_blank\" rel=\"noindex nofollow\">Regulated fintech flows impose legal accuracy constraints where disclosure copy in prototypes must accurately reflect production copy<\/a>, and only moderated methods can verify whether participants genuinely comprehend data-use disclosures rather than clicking through them. Listen Labs satisfies this use case through AI moderation with screen sharing, Emotional Intelligence, and compliant data handling.<\/p>\n<p>Product teams without dedicated researchers need self-serve simplicity. They describe research goals in natural language, receive a structured study guide, and get synthesized findings without methodology expertise. Listen Labs\u2019 AI-assisted study design and automated Research Agent deliverables serve this persona directly.<\/p>\n<p>Agencies and consultancies requiring rapid global reach, often measured in days for client engagements, benefit from Listen Labs\u2019 45+ country coverage, 100+ language support, and fast turnaround. Robinhood used Listen Labs to assess whether prediction markets feel on-brand and to identify user segments driving the highest re-engagement. The team received insights 5x faster and revealed integration flows that boosted uptake 30\u201340%.<\/p>\n<h2>Operational and Long-Term Factors for Scaling Research Programs<\/h2>\n<p>Stakeholder alignment becomes simpler when a single platform covers recruitment, moderation, analysis, and reporting. Teams avoid the vendor coordination overhead of stitching together panel providers, scheduling tools, transcription services, and analysis repositories. Change management for teams migrating from legacy UX tools centers on demonstrating output quality, since Listen Labs\u2019 Research Agent generates the same slide decks and highlight reels that researchers previously spent days producing manually.<\/p>\n<p>Compliance needs evolve continuously. <a href=\"https:\/\/deviqa.com\/blog\/automated-testing-for-fintech-apps-what-to-automate-and-what-to-leave-manual\" target=\"_blank\" rel=\"noindex nofollow\">Regulatory requirements such as KYC, AML, PCI DSS, GDPR, and SOC 2 are jurisdiction-specific and constantly updated<\/a>, which makes point-in-time compliance certifications insufficient. Platforms must maintain ongoing certification programs. Listen Labs holds SOC 2, ISO 27001, ISO 27701, and ISO 42001, with GDPR compliance built into data handling architecture.<\/p>\n<p>For ongoing or global programs, <a href=\"https:\/\/getperspective.ai\/blog\/the-state-of-ai-customer-interviews-2026-mid-year-update\" target=\"_blank\" rel=\"noindex nofollow\">68% of mid-market and enterprise teams reported at least one production AI interview study by April 2026<\/a>, with the dominant use case shifting from concept testing to continuous discovery. In that group, 41% of teams now run weekly or biweekly AI interview cadences. Mission Control supports this shift by building institutional knowledge across every study rather than siloing findings in individual reports.<\/p>\n<h2>Risks and Limitations When Testing Financial Services Prototypes<\/h2>\n<p>Shallow data from unmoderated tools is a documented risk for regulated flows. <a href=\"https:\/\/thegood.com\/insights\/ai-research-tools\" target=\"_blank\" rel=\"noindex nofollow\">AI-generated findings from synthetic or automated testing match surface-level issues but fail to capture navigation hesitation, emotional reactions, and unexpected workarounds that reveal broken information architecture<\/a>. Slow turnaround from traditional moderated methods creates a different risk, since individual deep interviews require skilled moderators, recruitment, hours of scheduling and transcription, making sub-24-hour turnaround impossible with traditional methods.<\/p>\n<p>Hidden recruitment complexity affects teams that underestimate panel sourcing for niche financial services audiences. Fraud risk in commodity panels is quantifiable, and <a href=\"https:\/\/seedfa.st\/blog\/test-data-for-fintech\" target=\"_blank\" rel=\"noindex nofollow\">the global average cost of a data breach was $4.44 million according to the IBM Cost of a Data Breach Report 2025<\/a>, rising to $10.22 million in the United States, which contextualizes the cost of inadequate participant verification. Overestimating automation without emotional insight capture is a strategic risk, and <a href=\"https:\/\/deviqa.com\/blog\/ux-testing-for-fintech-apps-what-seamless-actually-means-in-financial-services\" target=\"_blank\" rel=\"noindex nofollow\">a 2025 Fenergo survey of 600 senior executives found 70% of financial institutions lost clients last year due to inefficient onboarding<\/a>, a problem that functional test scripts cannot diagnose because they do not capture why users abandon flows.<\/p>\n<h2>Decision Framework: Comparing the Three Platform Categories<\/h2>\n<p>The ten evaluation criteria map to three platform categories:<\/p>\n<ol>\n<li>Traditional UX testing tools<\/li>\n<li>Functional automation platforms<\/li>\n<li>AI-moderated interview platforms<\/li>\n<\/ol>\n<p>The ten evaluation criteria reveal a clear pattern. Functional automation platforms excel at speed but produce no user insight. Traditional UX tools deliver depth but at timelines incompatible with sprint cycles. Only Listen Labs combines rapid turnaround with adaptive conversational depth and emotional signal capture at scale.<\/p>\n<p>On methodological flexibility, automation platforms are script-bound, traditional tools support moderated and unmoderated formats separately, and Listen Labs combines moderated AI interviews, screen sharing, mobile recording, Likert scales, NPS, MaxDiff, and branching logic within a single study. This flexibility matters because financial services teams often need to validate qualitative reactions and quantitative preference data within the same study to satisfy both UX and product stakeholders.<\/p>\n<p>On global and multilingual reach, automation platforms are environment-agnostic, traditional tools have limited panel geography, and Listen Labs covers 45+ countries and 100+ languages with automatic translation and transcription. On governance and security, only Listen Labs holds the full compliance certification stack simultaneously. On total operational burden, automation platforms require QA engineering, traditional tools require multi-vendor coordination, and Listen Labs consolidates the entire research lifecycle into one platform.<\/p>\n<p>Teams that require all ten criteria to be satisfied, particularly governance, emotional depth, and rapid turnaround, have one platform that meets every requirement. <a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\">Map Listen Labs\u2019 capabilities against your specific compliance requirements<\/a> in a personalized demo.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>How quickly can a financial services prototype testing platform deliver results from hundreds of interviews?<\/h3>\n<p>Listen Labs delivers synthesized findings, slide decks, video highlight reels, and statistical charts from hundreds of AI-moderated interviews in under 24 hours. Traditional moderated research takes 4\u20136 weeks from study design to final report. The speed difference is structural because AI moderation runs hundreds of parallel conversations simultaneously, while human moderation is sequential and constrained by moderator availability, scheduling, and transcription time. For financial services teams validating KYC onboarding flows or payment authorization prototypes within sprint cycles, rapid turnaround is the only operationally viable option.<\/p>\n<h3>How do AI-moderated platforms source participants while maintaining PII compliance and fraud prevention?<\/h3>\n<p>Listen Labs sources participants through Listen Atlas, an AI orchestration layer that matches across behavioral and intent data, not just self-reported demographics, across a global network of 30M verified respondents in 45+ countries. Quality Guard monitors every interview in real time across video, voice, content, and device signals to detect fraud, low-effort responses, AI-generated scripts, and mismatched profiles. Participants are limited to three studies per month, which eliminates professional survey-takers. A dedicated recruitment ops team adds a human review layer for hard-to-reach segments.<\/p>\n<p>On the compliance side, Listen Labs holds the full compliance certification stack, and customer data is never used for AI model training, which directly addresses GLBA Safeguards Rule requirements and GDPR Article 32 security controls.<\/p>\n<h3>What is the difference between AI moderation and human moderation for banking app usability testing?<\/h3>\n<p>Human moderation delivers real-time conversational depth but is constrained by moderator availability, scheduling logistics, fatigue across long field periods, and inconsistent probing depth between participant 1 and participant 200. AI moderation applies the same adaptive follow-up methodology, probing multiple levels deep on every response, to every participant simultaneously and eliminates moderator drift that confounds multi-week human field periods.<\/p>\n<p>For banking app usability testing specifically, AI moderation captures screen interactions, emotional signals through Emotional Intelligence, and verbal responses within a single session. Human moderation typically requires separate screen recording tools and manual emotional coding. AI moderation is not appropriate for regulatory sworn testimony or trauma-sensitive financial distress research, where human judgment and legal accountability are required.<\/p>\n<h3>How much analysis effort is required after running prototype tests with Listen Labs?<\/h3>\n<p>Analysis effort is minimal. The Research Agent automatically generates key findings, thematic analysis, personas, statistical charts, segmentation breakdowns, and one-click deliverables including consultant-quality PowerPoint slide decks, memo-style reports, and video highlight reels. Researchers can also query the data in natural language and receive answers, charts, and supporting verbatim quotes without manual tagging.<\/p>\n<figure style=\"text-align: center\"><a href=\"https:\/\/listenlabs.ai\/\" target=\"_blank\"><img decoding=\"async\" src=\"https:\/\/cdn.aigrowthmarketer.co\/1773099063654-7132de546a42.png\" alt=\"Listen Labs&apos; Research Agent quickly generates consultant-quality PowerPoint slide decks\" style=\"max-height: 500px\" loading=\"lazy\"><\/a><figcaption><em>Listen Labs&#039; Research Agent quickly generates consultant-quality PowerPoint slide decks<\/em><\/figcaption><\/figure>\n<p>Mission Control stores findings across all studies and enables cross-study queries, so teams can answer new questions from past research in seconds rather than re-running studies.<\/p>\n<h3>What security and privacy certifications should financial services teams require from a prototype testing platform?<\/h3>\n<p>Financial services teams should require the full compliance certification stack described earlier as a baseline. Teams operating under GLBA should verify that vendor contracts include clauses prohibiting training on customer data, limiting data retention, requiring subprocessor approval, mandating breach notification within 24\u201372 hours, granting audit rights, and specifying data residency. Teams subject to CPRA should confirm the platform supports data minimization, purpose limitation, and consumer opt-out rights for automated decision-making. Listen Labs holds all five certifications and never uses customer data for AI model training.<\/p>\n<h3>Can these platforms support multilingual research across 45+ countries?<\/h3>\n<p>Listen Labs supports interview moderation in 100+ languages with automatic translation and transcription across all supported languages, covering 45+ countries in the Americas, Europe, APAC, and MEA. Emotional Intelligence is available across 50+ languages. Traditional UX testing tools have limited panel geography and typically require separate localization vendors for non-English studies. Functional automation platforms are environment-agnostic and do not conduct participant research.<\/p>\n<p>For financial services teams validating products across multiple regulatory jurisdictions simultaneously, Listen Labs\u2019 multilingual reach and automatic translation eliminate the need for separate regional research vendors.<\/p>\n<h3>How does Listen Labs scale from one study to ongoing global programs?<\/h3>\n<p>Listen Labs is architected for both one-off studies and continuous research programs. Single studies can be launched, fielded, and synthesized within 24 hours. For ongoing programs, Mission Control builds institutional knowledge across every study, tracking customer sentiment, needs, and pain points over time and enabling cross-study queries without re-running research.<\/p>\n<p>Teams running weekly or biweekly discovery cadences use Listen Labs as always-on research infrastructure rather than a project-based tool. Enterprise SSO, role-based access, and the full compliance certification stack support deployment across large, distributed research and product organizations without creating governance gaps as program scope expands.<\/p>\n<h2>Conclusion: Choosing a Platform That Matches Financial Services Demands<\/h2>\n<p>The evaluation across all ten criteria produces a clear differentiation. Functional automation platforms are essential for regression and API testing but produce no user insight and cannot diagnose why participants abandon KYC flows or distrust payment authorization screens. Traditional UX tools deliver moderated depth but at timelines and sample sizes that cannot support continuous discovery or sprint-cycle validation in regulated environments.<\/p>\n<p>AI-moderated interview platforms close both gaps, and only Listen Labs combines verified participant recruitment, adaptive AI moderation with screen sharing and mobile recording, Emotional Intelligence for emotional signal capture, Quality Guard for fraud prevention, automated analysis and deliverable generation, and the full enterprise compliance certification stack in a single end-to-end platform.<\/p>\n<p>Robinhood used Listen Labs to assess prediction market fit and user segment re-engagement, receiving insights 5x faster than traditional methods and identifying integration flows that boosted uptake 30\u201340%. That result, compliant and emotionally rich insights from hundreds of interviews in hours, is the standard financial services prototype testing now requires.<\/p>\n<p>If your team is comparing platforms and needs to validate prototypes without weeks of logistics or compliance risk, <a href=\"https:\/\/listenlabs.ai\/book-my-demo\" target=\"_blank\">see how Listen Labs delivers end-to-end research at the speed and depth your product decisions demand<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Compare UX tools, automation suites &amp; AI platforms for fintech testing. Listen Labs delivers compliance-ready insights in under 24 hours. Try it free.<\/p>\n","protected":false},"author":52,"featured_media":1281,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1282","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts\/1282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/comments?post=1282"}],"version-history":[{"count":0,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/posts\/1282\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/media\/1281"}],"wp:attachment":[{"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/media?parent=1282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/categories?post=1282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/listenlabs.ai\/articles\/wp-json\/wp\/v2\/tags?post=1282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}