Top 10 AI Feedback Analytics Tools for Actionable Customer Insights in 2025

Over 80% of customer feedback never sees the light of day. That means eight out of every ten comments, complaints, or feature requests are silently piling up while competitors move faster. Picture your CX dashboard on a Monday morning: 2,347 open‑text responses waiting for someone—probably you—to decode them. If you’re leading customer experience, steering a product roadmap, or firefighting support tickets, you know the gut‑punch of “too much feedback, too little insight.”

That paralysis ends with AI feedback analytics tools. These platforms don’t merely tally scores; they comb through verbatims, surface hidden themes, predict churn signals, and hand you a ranked to‑do list before your coffee gets cold, turning feedback into revenue‑saving actions.

In this blog, we’ll explore the top AI feedback analytics tools to watch in 2025—what makes them powerful, who they’re best for, and how they stack up in terms of features, pricing, and business impact. Plus, you’ll get a practical decision-making framework to help you find the right tool for your team—whether you’re scaling CX insights, improving product experience, or closing the loop faster than ever. So, let's get started!

TL;DR

• AI feedback analytics tools helps teams make sense of unstructured feedback at scale—automatically surfacing themes, sentiment, intent, and trends that drive action.
• We’ve evaluated top AI feedback analytics tools based on advanced AI capabilities, data ingestion breadth, automation, role-based usability, and feedback loop closure.
• Some of the best AI analytics tools in 2025 include Zonka Feedback, Chattermill, Enterpret, and more, each offering unique strengths across analysis depth, speed, and team alignment.
• Zonka Feedback’s new AI Feedback Intelligence platform brings together thematic analysis, sentiment detection, role-based dashboards, verbatim traceability, and AI-powered insights to turn feedback into clear, prioritized actions. You can get early access or schedule a demo to explore how it helps you improve your customer experience. 

Get a Better Understanding of Customer Feedback with AI Analytics Tools

With AI Feedback Analytics Tool, create surveys in seconds and use artificial intelligence to decode insights from the data collected.

If you want to jump straight to the list of the best AI Feedback Analytics tools, click here. Prefer to understand how AI feedback analytics works and what to look for? Keep reading below.

What is AI Feedback Analytics Tools?

AI feedback analytics tools are platforms that help you analyze customer feedback at scale, without the manual grunt work. They use natural language processing (NLP), machine learning, and large language models (LLMs) to read through open-text responses, tag sentiment, detect recurring themes, and surface insights that would otherwise go unnoticed.

Think of them as the evolution of traditional survey tools. Legacy dashboards show you response rates, NPS scores, and a wall of raw comments. But they leave it up to you to figure out what those comments actually mean and what to do about them. AI flips that. It does the heavy lifting, so you can focus on acting instead of analyzing.

For example, instead of sifting through 500 “other” responses in your post-purchase survey, an AI survey tool can group them into themes like “slow checkout,” “confusing product descriptions,” or “missing size filters.” You instantly know where the friction is and what to fix. These tools don’t just summarize feedback. They translate voice of customer into clear next steps fast.

Why AI Feedback Analytics Software Matter in 2025?

Feedback today doesn’t trickle in—it floods your systems from every direction: surveys, chats, social media, review sites, support logs. It’s real-time, multilingual, and messy. And if you're still relying on spreadsheets or traditional dashboards, you're not analyzing feedback, you're surviving it.

That’s exactly why AI feedback analytics tools have gone from a future bet to a current necessity. Our AI in Feedback Analytics Research Report 2025 flags a reality gap—only 17% use LLMs or custom AI for feedback analytics today—so early adopters gain a speed and insight edge. However, those early adopters of AI-powered feedback platforms are already seeing serious returns:

• 80% faster insight-to-action cycle — so teams act in hours, not days
• 5% drop in churn — because at-risk customers get flagged (and heard) in time
• 10% boost in CSAT — as recurring pain points don’t just get noticed, they get fixed
  Source: Product at Work

Multiply those gains across hundreds of touchpoints and thousands of customers, and you’re looking at major revenue impact, not to mention team sanity.

Analysts are catching on too. In TechRadar’s 2025 list of top AI use cases in CRM, sentiment analysis ranked in the top seven, alongside predictive lead scoring and generative sales automation. Giants like Salesforce and HubSpot are already building AI-native feedback capabilities and your customers are expecting you to keep up.

That being said, speed, retention, and customer loyalty are the currencies that matter in 2025. AI feedback analytics puts all three on the same dashboard—minus the manual grind—so your team can spend its energy acting on insights instead of looking for them.

Features to Look for in AI Feedback Analytics Tools in 2025

Not all AI feedback tools are created equal. The best ones go beyond dashboards and charts, they dig into the mess, make sense of it fast, and serve up insights tailored to each team’s priorities.
Here’s your non-negotiable feature checklist for 2025:

• Multichannel & Multimodal Ingestion: Collect feedback from everywhere your customers speak—surveys, chat, social, app reviews, even voice and video. The more signals you capture, the sharper your insights. No more juggling five platforms to understand one journey.
• NLP-Powered Theme & Sentiment Detection: Go beyond surface-level keywords. Let AI unpack what customers are saying and how they feel—automatically grouping feedback into themes like “pricing confusion” or “shipping delays,” complete with emotional context.
• Emotion & Intent Analysis: Frustrated rants, urgent escalation cues, subtle buying signals—this is the layer that catches what scores alone can’t. Perfect for flagging silent churn risks or hot leads before anyone else notices.
• Generative AI Summaries & Auto-Reply Drafts: Whether it’s summarizing 1,000 survey comments or suggesting a thoughtful response to a low NPS, generative AI saves your team from manual analysis—and bad replies.
• Role-Based Dashboards & Self-Serve Analytics: Your CX head shouldn’t have to dig through product feedback. And your PMs shouldn’t filter out loyalty data. Great tools tailor insights to what each team actually cares about—no analyst required.
• Predictive Churn & NPS Forecasting: Don’t just react—anticipate. AI models can project loyalty dips and identify at-risk segments based on past behavior and sentiment trends, giving you time to intervene.
• Closed-Loop Workflow Automation: Insights are useless unless acted on. These tools assign feedback to the right owner, trigger workflows, and track resolution—so nothing slips through the cracks.
• Verbatim Traceability & Explainable AI: Want to understand why a score dropped? You should be able to click through to the exact comment or customer thread. This builds trust—internally and with stakeholders who demand context.
• Multilingual & Cross-Cultural Sentiment: For global brands, tone and meaning can vary wildly across languages. Tools with strong multilingual NLP make sure nothing gets lost—or misread—in translation.

Advanced AI Capabilities that Some AI Analytics Tools for Feedback Analysis Offer

If basic tagging and sentiment scoring were version 1.0, the new wave of AI feedback tools is all about action. These advanced capabilities are where real impact (and differentiation) happens:

• AI Copilots for Next-Best Actions: It’s not enough to spot a problem—modern tools recommend what to do next. Whether that’s assigning a follow-up, triggering a workflow, or escalating an issue, copilots reduce decision fatigue and help teams take action faster.
• Business Entity Recognition: Advanced AI tools can automatically detect and tag business-specific elements—like product features, agent names, or store locations—within open-ended feedback. That means teams don’t waste time manually sorting what belongs where.
• Customer Attribute-Level Insights: Go beyond surface stats. These tools link feedback to meaningful traits—like account value, lifecycle stage, or plan tier—so you can answer questions like “What are our most valuable customers unhappy about this month?” in one click.
• Multi-Dimensional Filtering & Exploration: Feedback gets powerful when you can slice it by what matters—sentiment, theme, persona, location, and more. Top tools let teams explore intersecting trends and drill down into what’s driving sentiment shifts within key segments.
• AI-Powered Insight Validation: Not every trend is worth chasing. Some tools now validate emerging themes by showing volume, impact, and supporting verbatims—so your team knows if a spike in “billing issues” is a blip or a red flag worth prioritizing.

Best AI Feedback Analytics Software at a Glance

Here’s a quick side-by-side comparison of the top AI Feedback Analytics tools highlighting their standout strengths, pricing models, and rating to help you make an informed choice.

Top AI Analytics Tools for Feedback for Customer Insights 

Let’s get into the AI powered feedback analytics tools that are redefining how teams listen, learn, and act on customer feedback.

1. Zonka Feedback

Zonka Feedback is more than just a survey platform—it’s a complete AI-powered customer insight engine designed to help CX, Product, and Support teams scale how they listen, understand, and act on feedback. While this customer experience software offers robust capabilities for collecting feedback across surveys, SMS, in-app, email, and offline channels, its standout is the AI Feedback Intelligence module—built to transform raw, unstructured feedback into prioritized, real-time insights.

Using NLP and GenAI, Zonka Feedback detects emotion, urgency, and recurring themes across open-ended responses. But it doesn’t stop at analysis. It automatically routes insights to the right owners, suggests next-best actions, and closes the feedback loop with collaborative tools—all from a single dashboard. From support tickets and NPS surveys to app reviews and call transcripts, Zonka Feedback centralizes feedback operations and empowers every team to act fast, reduce churn, and improve customer experience continuously.

Whether you need to analyze sentiment trends for a product launch, monitor service issues by location, or respond instantly to unhappy customers—Zonka Feedback makes feedback operational, not just informational.

Key Features

• Emotion, Sentiment & Theme Detection: AI identifies patterns, urgency, emotion, and intent across feedback—so you see what customers are really feeling and where they’re struggling.
• Entity Mapping for Contextual Insights: Responses are tagged to products, agents, locations, or departments for pinpointed accountability and faster resolution.
• Role-Based Dashboards & Data Views: Tailored dashboards for CX leaders, product managers, support heads, and execs—each team sees what matters to them.
• Agentic AI Recommendations: Zonka’s AI doesn’t just report—it recommends. Get prioritized next steps based on urgency, sentiment, and business goals.
• AI Workflow Automation: Feedback is auto-tagged, categorized, and routed to the right team instantly—no bottlenecks, no manual triage.
• AI-Powered Smart Summaries & Reports: Turn thousands of responses into digestible summaries and dynamic reports—no analyst required.
• Flexible Taxonomy & Custom Mapping: Define themes and KPIs based on your business logic and org structure—perfect for enterprise setups.
• Multilingual AI Translations & Analysis: Analyze global feedback in local languages with AI-powered translation and sentiment detection.
• Real-Time Alerts & Feedback Loop Closure: Set up triggers for urgent feedback, monitor resolution, and ensure nothing gets dropped.

2. Chattermill

Chattermill is built for enterprises that live in data chaos—think millions of survey responses, support tickets, reviews, and social media mentions flowing in every week. What sets it apart is its ability to bring all that feedback into a single AI-powered view, making sense of it instantly and at scale. Powered by proprietary NLP and machine learning, Chattermill detects sentiment, uncovers recurring topics, and flags emerging issues across channels and languages. Whether you’re a global CX leader trying to reduce churn or a product manager spotting feature friction, Chattermill pulls signal from noise so your team can act quickly—with full context.

Used by brands like Uber, HelloFresh, and Amazon, it’s designed for teams that need precision and performance at volume. With role-specific dashboards, real-time alerts, and drillable verbatims, it doesn't just show you what’s trending—it shows you why, with the customer’s words right behind every insight.

Key Features

• Multi-Channel Feedback Integration: Connects surveys, NPS programs, reviews, support platforms, chat logs, and social media into one unified Voice of Customer (VoC) dataset.
• AI-Powered Theme & Sentiment Clustering: Automatically groups responses by theme, emotion, and sentiment—even with industry-specific language—so you can spot trends fast.
• Custom Dashboards & Role-Based Reporting: Create filtered views by product, region, emotion, or touchpoint. Product teams see friction themes, CX sees satisfaction drivers, Ops sees escalations.
• Real-Time Alerts & Trend Detection: Get notified when sentiment dips, complaints spike, or new issues emerge—before they hit your CSAT or social feeds.
• Verbatim Drill-Down & Traceability: Click from a theme directly to the raw customer comments behind it. Great for stakeholder buy-in and deeper qualitative insights.
• Scalable Across Languages & Data Volumes: Built for enterprise speed, Chattermill supports multilingual feedback analysis and scales easily with growing data pipelines.

3. Thematic

What sets Thematic apart isn’t just its AI—it’s how that AI collaborates with your team. Designed for mid-to-large organizations, Thematic offers advanced thematic analysis driven by machine learning, but with a twist: you stay in the loop. Its standout feature is an intuitive theme editor that allows analysts to refine AI-generated categories, ensuring your feedback taxonomy actually matches how your business thinks and operates.

That means no rigid code frames or misread intent—just intelligent clustering of feedback with domain-aware flexibility. Whether you’re tracking why NPS dropped last quarter or surfacing insights from open-text CSAT responses, Thematic breaks down customer feedback into meaningful themes, sentiment trends, and impact drivers. With brands like Atlassian, DoorDash, and Jetstar on board, it’s a go-to tool for teams that want fast, explainable insights—with the option to fine-tune every step.

Key Features

• Human-in-the-Loop Theme Detection: AI identifies themes and sub-themes automatically, while users can merge, edit, or rename them using a visual interface
• Sentiment Analysis at Theme Level: Every theme is mapped with sentiment direction—positive, negative, neutral—so teams can see not just what’s being said, but how customers feel about it.
• Explainable Insights with Verbatim Drilldown: Click on any theme to instantly view the raw comments that formed it. Great for building stakeholder trust.
• Role-Based Dashboards & Thematic Answers: Custom views tailored to CX, Product, and Ops. Plus, a GPT-powered search bar lets you ask questions like “What changed in our NPS last month?” and get instant insights.
• Trend Detection & Emerging Issues Alerts: Automatically flags spikes in topics or sentiment shifts so you can catch bugs, frustration, or praise as it’s happening.
• Integrations & Flexible Imports: Connects with systems like Qualtrics, Zendesk, and survey tools, or allows CSV/API imports from any source—ensuring a unified feedback ecosystem.

4. Enterpret

Enterpret is an AI insights tools that stands out is its tailored intelligence. Unlike generic AI tools, Enterpret custom-trains its NLP models to understand your product’s unique language—feature names, support jargon, even internal acronyms—so it doesn’t just analyze feedback, it gets it.

Built for product and CX teams dealing with feedback across multiple touchpoints, Enterpret consolidates everything—support tickets, chats, CRM notes, app reviews, social media, surveys—into one unified, searchable platform. But more than aggregation, it categorizes feedback into themes and sub-themes, detects sentiment and intent, and shows you which issues matter most based on volume and emotional weight. Whether you're a PM prioritizing your roadmap or a CX lead tracing sentiment trends across user segments, Enterpret helps you move fast and with context—no tagging marathons, no spreadsheet exports.

Key Features

• Custom-Trained Topic Categorization: AI automatically groups feedback into themes tailored to your company’s domain—learns from your product structure, use cases, and customer terminology.
• Unified Feedback Repository: Connects with tools like Zendesk, Intercom, Salesforce, Slack, app stores, and surveys to centralize all qualitative data in one place.
• Sentiment & Intent Detection: Differentiates between complaints, praise, bug reports, and feature requests—so you can focus on what’s urgent, not just what’s frequent.
• Smart Query & Search: Use filters or natural language prompts like “Show me all negative feedback about checkout from the past 30 days” and get instant results.
• Explainable, Verbatim-Linked Insights: Every insight links back to the original comment or source (e.g., a Zendesk ticket), letting you explore real user voices behind each theme.
• Trend Prioritization: Ranks issues not just by mention volume, but also by sentiment impact—helping teams prioritize fixes that actually move the needle.

5. Kapiche

Kapiche is built for speed and clarity—making it ideal for teams that want to go from feedback dump to prioritized action without needing data scientists or complex setup. Its standout feature is a Dynamic Discovery engine that automatically uncovers new, unexpected themes in customer feedback, even if they don’t fit into existing taxonomies.

But what really makes Kapiche shine is how it connects those themes to metrics like NPS, CSAT, and churn. In one click, you can see which topics are dragging down customer satisfaction—or boosting it. Combined with an intuitive, no-code dashboard and quadrant-style impact visualizations, Kapiche helps product, CX, and insight teams not only know what’s being said but what to fix first.

Key Features

• Dynamic Theme Discovery: Automatically detects recurring themes from feedback without predefined tags or coding. Also flags “unmapped” comments so nothing important slips through.
• Theme-to-Metric Impact Analysis: Measures how each theme influences key metrics like NPS or CSAT—so you know what’s actually moving the numbers.
• Unified Data Ingestion Across Channels: Consolidates surveys, reviews, support tickets, CRM notes, and more into one feedback hub—no more separate analysis silos.
• Interactive Dashboards with Visual Prioritization: Filter by segment, timeframe, or channel and explore data via word clouds, trend graphs, and quadrant charts that show frequency vs. impact.
• Collaborative Reporting & Sharing: Generate stakeholder-specific reports, export visual insights, and comment directly in the platform to keep teams aligned on customer priorities.

6. SentiSum

SentiSum is purpose-built for support and CX teams who live in the trenches of daily customer conversations. Its standout capability? Real-time, automated tagging and sentiment detection for every chat, ticket, email, or survey response without manual labeling required. Whether your inbox is flooded with login complaints or feature requests, SentiSum immediately categorizes incoming feedback (e.g., “billing error,” “delivery delay”) and assesses the tone, so teams can spot rising issues, route them to the right department, and take action before they escalate. It’s not just about watching support volumes; it’s about understanding the why behind them.

With its Ask-AI feature, you can even type in plain questions like “Why are refunds up this week?” and get data-backed answers, complete with visualizations and verbatim quotes. Add customizable dashboards and multilingual capabilities, and SentiSum becomes a feedback operations command center tailored to the needs of high-velocity support environments.

Key Features

• Automated Tagging & Sentiment Detection: Instantly tags each customer interaction with relevant topics and sentiment, helping teams see what’s trending and how users feel.
• Multichannel Feedback Aggregation: Pulls in data from Zendesk, Intercom, email, live chat, survey tools, and more—giving you a complete view of customer pain points across support channels.
• Real-Time Alerts & Trend Spotting: Detects sudden spikes in complaints or sentiment changes—great for catching bugs, broken flows, or delivery issues before they go viral.
• Support Team Dashboards & Feedback Routing: Auto-routes feedback to the right teams (e.g., billing complaints to finance) and delivers insights in tailored dashboards for Product, Ops, and Support.
• Ask-AI & Conversational Querying: Use plain English to ask questions like “What’s driving negative CSAT this week?”—and get instant summaries with supporting verbatims.
• Multilingual Analysis & Translation: Handles over 100 languages, either analyzing native text or translating into English for unified insight across global operations.

7. Birdie

Birdie is built for product teams who want more than just dashboards—they want a direct line between customer feedback and product decisions. Its standout strength is a built-in prioritization engine that not only surfaces insights from unstructured feedback but also connects them to business impact and tracks what happens after you take action.

Birdie pulls in data from surveys, support tickets, social comments, app reviews, and more—then uses AI to categorize feedback by feature, theme, or issue. But where it really shines is its ability to quantify opportunities (e.g., “X% of detractors mention checkout issues”) and help teams decide which problems to fix first. After implementation, it tracks whether those fixes reduced complaints or improved sentiment closing the loop and proving ROI.

Key Features

• AI-Powered Categorization & Sentiment Analysis: Automatically classifies feedback by product area or theme and tags sentiment, making it easy to detect high-friction points.
• Custom Areas of Interest Tracking: Set topics like “checkout experience” or “onboarding friction,” and Birdie will track all relevant feedback across sources in real time.
• Opportunity Scoring & Prioritization Engine: Quantifies how each issue impacts metrics like NPS, CSAT, or retention—so teams can focus on high-impact improvements.
• Feedback-to-Feature Workflow: Manage opportunities within Birdie using statuses like “Planned” or “In Progress,” and sync with Jira or product tools to bridge insight and execution.
• Closed-Loop ROI Tracking: After shipping a feature, Birdie tracks if related complaints dropped or sentiment improved—tying product work to measurable outcomes.
• Feedback Centralization: Integrates with CRMs, helpdesks, review sites, and community tools to create a 360° feedback stream—no more siloed feedback sources.

8. Lumoa

Lumoa is designed for teams that want clear, real-time answers from customer feedback without needing analysts to interpret charts. Its standout feature is an AI-powered insights engine that answers questions like, “What’s making customers unhappy this week?” in natural language, backed by live data. The platform aggregates feedback from surveys, reviews, support logs, and more, then categorizes it by topic and sentiment across 60+ languages.

You don’t just see a wall of responses. You get themes that matter, how they’re trending, and their impact on metrics like NPS or CSAT—all presented in clean, intuitive dashboards. It even lets you assign feedback for follow-up and track case resolution. With near real-time updates, GPT-style querying, and red/green CX indicators, Lumoa turns feedback chaos into actionable insights that anyone on your team can understand and act on.

Key Features

• Multi-Source Feedback Aggregation: Pulls in data from surveys, reviews, support tickets, and more—consolidating feedback from all sources and languages into a single view.
• AI Categorization & Sentiment Detection: Automatically tags comments by topic and sentiment (positive/negative) so you can instantly see which areas are performing well—and which aren’t.
• Driver Impact Analysis: Links feedback topics to performance metrics like NPS, CSAT, or star ratings, and shows how they’ve shifted over time.
• Plain-Language AI Summaries: Answers open-ended questions like “What changed in Europe this month?” with digestible, GPT-powered summaries and supporting verbatims.
• Feedback Assignment & Alerts: Assigns comments to owners for follow-up and notifies teams if negative sentiment spikes in a specific area—ideal for fast CX issue resolution.

9. Dovetail

Dovetail isn’t just another customer feedback tool—it’s a researcher’s command center. Its standout strength lies in helping teams synthesize qualitative data at scale, from interviews, usability tests, and transcripts to survey responses and open-text feedback.

What sets Dovetail apart is how it blends a powerful, searchable insights repository with AI-driven tagging and highlight generation. Imagine uploading a batch of interviews and instantly getting suggested themes, visualizations, and quote highlights—ready for cross-functional teams to explore, share, and act on. From UX researchers to product managers and marketers, Dovetail makes past research easy to find, understand, and use.

Key Features

• Centralized Research Repository: Store, organize, and search everything—from interview recordings and notes to survey feedback and screenshots—in one searchable hub.
• AI Transcription & “Magic” Highlight Suggestions: Upload audio or video files, and Dovetail auto-transcribes and suggests the most relevant insights. 
• Tagging & Theming for Pattern Recognition: Tag excerpts with custom labels like “UX friction” or “feature request,” and Dovetail groups, counts, and visualizes these across projects and time.
• Collaborative Insight Building: Teams can co-annotate transcripts, comment, and create reports together—great for keeping stakeholders in the loop.
• Searchable Insights Across Projects: Ask, “What do customers say about onboarding?” and instantly pull up every relevant note, quote, and video clip—no need to dig manually.
• AI Summaries for Fast Exploration: Ask questions in plain English and get AI-generated summaries across datasets—helping teams quickly understand key takeaways.

10. Zefi

Zefi stands out by doing what most feedback platforms don’t, automatically telling you which issues and requests deserve your attention right now. Built for product and CX teams that don’t have time (or data analysts) to comb through every comment, Zefi’s strength lies in its real-time prioritization engine. It gathers feedback from every corner—support tickets, app reviews, surveys, emails, social media—and uses AI to categorize, score, and highlight urgent patterns that correlate with satisfaction drops or recurring friction.

The setup is quick: connect your data sources, and Zefi gets to work—no manual training, no complex dashboards. It’s the kind of tool that says, “Here’s what’s trending negative this week,” so teams can respond fast, iterate faster, and keep the user experience moving forward.

Key Features

• Feedback Aggregation Across Channels: Pulls in user feedback from email, chat, reviews, surveys, and CRMs into a single dashboard for unified analysis.
• AI-Powered Theme & Sentiment Analysis: Auto-categorizes feedback into clear topics (e.g., “Payment Issues,” “Feature Request – Filters”) and detects tone and urgency—no setup needed.
• Insight Prioritization by Impact: Highlights the most pressing feedback based on volume, sentiment, and correlation with satisfaction metrics—so teams can act on what matters most.
• Plug-and-Play Integrations: Works with Slack, Intercom, Zendesk, Gmail, Salesforce, and more. Alerts, summaries, and tickets can be routed directly into existing workflows.
• Fast Time-to-Value & Scalability: Designed for speed—teams can be up and running in a day. Plus, Zefi scales with growing feedback volume, offering enterprise-grade security and flexibility.

Conclusion

In 2025, AI feedback analytics is how modern teams keep pace with what customers are really saying, feeling, and expecting. The right tool doesn’t just reduce manual effort; it turns every survey, support ticket, and review into fuel for smarter decisions, faster fixes, and more loyal customers. From predictive churn signals to sentiment-rich product insights, the benefits are too tangible and too timely to ignore.

At Zonka Feedback, we’re building exactly that future. Our new AI Feedback Intelligence platform is powered with features like thematic analysis, sentiment analysis, role based dashboard, verbatim traceability, AI-generated insights and actions—all designed to help CX, Product, and Support teams turn raw feedback into prioritized, real-time actions without the manual grind.

Get early access and be among the first to automate feedback analysis, surface critical insights instantly, and close the loop at scale. Or schedule a demo to explore more about our platform and turn every response into a growth opportunity.