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Solutions
PRODUCT HUB
Turn consumer feedback into product intelligence. Sharpen innovation, identify and resolve QA issues, and de-risk product launches.Competitor 360°Product return analysisPurchase motivationProduct 360°Improvement areasProduct innovationCompetitor 360°Product return analysisPurchase motivationProduct 360°Improvement areasProduct innovation
SOCIAL HUB
Move beyond tracking conversations to social intelligence that delivers accurate, credible, and actionable insights from the brand to SKU-level.Trend analysisBrand trackerSocial analysisVideo analysisInfluencer discovery & KitPDP enrichmentCampaign monitoringContent performanceCompetitor analysisTrend analysisBrand trackerSocial analysisVideo analysisInfluencer discovery & KitPDP enrichmentCampaign monitoringContent performanceCompetitor analysis
CI HUB
A unified market research platform that aggregates the total voice of the customer. Consolidate feedback across channels, from online reviews, social media, CSAT, surveys, and forums, into a single actionable view.New product monitoringStar ratings driversCompetitive analysisSWOT analysisMarket trend analysisInnovationNew product monitoringStar ratings driversCompetitive analysisSWOT analysisMarket trend analysisInnovation
ECOMM HUB
Equip your eCommerce teams with a powerful set of tools to maximize conversions at scale across both D2C and channel platforms.Tiktok shopRetailer analysisProduct sentiment analysisPDP enrichmentShopper experienceMAP monitoringStar rating optimizationTiktok shopRetailer analysisProduct sentiment analysisPDP enrichmentShopper experienceMAP monitoringStar rating optimization
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Industries
Food & BeverageThe Food & Beverage industry is a highly competitive one with new products and brands emerging all the time. Is it a new energy capitalizing on organic ingredients or a food fad that has taken the world by storm? Arm yourself with Revuze's online review analytics to maintain your edge.
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Revuze AI
Revuze AITurn fragmented consumer signals into trusted, AI-ready intelligence your teams can use across every workflow.RatingsCustomer ReviewsSocial ConversationsSurveysPOS DataProduct DataProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysisProduct 360°RatingsCustomer ReviewsSocial ConversationsSurveysPOS DataProduct DataProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysisProduct 360°
MCP CONNECTIONBring validated consumer intelligence directly into ChatGPT, Claude, Copilot, Gemini, and your internal AI workflows.More Accurate AnswersTrusted ContextConsistent OutputsDeeper IntelligenceHype or trendSWOT analysisProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysisProduct 360°More Accurate AnswersTrusted ContextConsistent OutputsDeeper IntelligenceHype or trendSWOT analysisProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysisProduct 360°
VEE Chat
Ask complex consumer and market questions and get immediate answers grounded in validated category, brand, and SKU-level data.Why are ratings dropping?What is driving competitor growth?Which trends are gaining momentum?Product 360°Hype or trendSWOT analysisProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysisWhy are ratings dropping?What is driving competitor growth?Which trends are gaining momentum?Product 360°Hype or trendSWOT analysisProduct innovationImprovement areasPurchase motivationProduct wishlistsProduct return analysis
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Platform
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Company
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Company
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Case Studies
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Discover What Really Drives Laundry Product Choice in the US and UKGet My Copy
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Industries
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Post-Olympic Sports Trends ReportGet My Copy
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Resources
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Resources
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Past Events
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Featured Trend Reports
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Discover What Drives Consumer Satisfaction in OTC Cough, Cold, and Flu RemediesGet My Copy
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PRODUCT HUB
SOCIAL HUB
CI HUB
ECOMM HUB
Cosmetics & Fragrance
Home Appliances
Revuze AI
VEE Chat
Germany (DE) 
Spain (ES) 
Italy (IT) 
France (FR) 
Would you bet $5M on a
hallucinating LLM?
If your copilots run only on public data, you’re making high‑stakes decisions on incomplete,
hallucinated, and non‑traceable answers. The brands that win will hook their agents into real
consumer signal, not vibes.
LLMs need better signals
What generic LLMs miss
Strong at generating language. Weak on fragmented, fast-moving market reality.
- Creative text, shallow business understanding
- Trained on unfiltered internet; prone to hallucinations
- Can’t trace sources or category‑specific clues
- Produces noise, not category benchmarks
- Misses fast, SKU‑level market changes
What Revuze sees
The signal layer that gives AI real market context to work from.
- Market analyst for brands and retailers
- Purpose‑taught VoC models, >90% precision
- Every insight traceable to real signals
- Full‑category, brand, and SKU benchmarking
- Connects reviews, social, PDPs, care, returns
Agents that watch what teams miss
Revuze Agents handle the tracking work teams already do manually across
launches, issues, competitors, trends, returns, and PDP performance.
Launch Monitoring
Issue Detection
Trend Discovery
Competitive Monitoring
One intelligence foundation.
Two ways to access it
Ask Revuze intelligence directly through Vee, or bring the same governed signal
layer into the AI systems your organization already uses.
Conversational research, grounded in real consumer signals
Ask questions about launches, claims, product issues, trends, competitors, and shopper behavior in natural language. Vee turns Revuze’s validated VoC and category intelligence into clear, traceable answers—with the evidence behind them.
The missing layer under your AI stack
If your team is building copilots or agentic workflows, Revuze supplies the context public LLMs do not have: what buyers are saying, what changed in the category, where friction sits, and which brand, SKU, retailer, or claim is affected.
How Revuze turns raw signals
into business decisions
Three layers connect what customers say to what your teams do
Collect
The Revuze Signal Layer unifies reviews, social, surveys, CSAT, customer care, product catalogs, sales, and more into one market model, mapped to every category, brand, product, SKU, retailer, and market.
Stop stitching sources together. Start from the full picture.
Understand
The Revuze Intelligence Layer’s purpose-built models turn consumer signals into reusable intelligence, revealing return drivers, defect clusters, unmet needs, trend momentum, and competitive benchmarks.
Know what changed, why it changed, and what it means.
Decide
The Revuze Action Layer brings market intelligence into AI Agents, Vee, MCP connections, and role-based Action Hubs, so teams and AI assistants make decisions from the same evidence.
One source of truth. Every team ready to act.
From brief to live agent in days
A live agent watching the category, so your team can act while there’s still time.
Step 1: Pick the job
Choose the workflow the agent will run: launch monitoring, issue detection, competitor tracking, trend analysis, sentiment monitoring, or shopper friction.
Step 2: Set the scope
Define the category, brands, SKUs, competitors, retailers, channels, and thresholds the agent should continuously watch.
Step 3: Go live
Start receiving live alerts, benchmarked reports, and recommended actions tied to the exact products and signals that changed.
Step 1: Pick the tools
Choose which Revuze MCP tools you want to expose: launch health checks, PDP diagnostics, sentiment drivers, competitor moves, returns analysis, or shopper friction.
Step 2: Set the endpoint
Define the Revuze MCP endpoint in your orchestrator, authenticate with your keys, and configure scopes by category, brand, SKU, retailer, channel, and environment (dev, staging, prod).
Step 3: Go live
Start letting your assistants call Revuze tools directly from prompts and workflows, and receive structured responses, benchmarks, and recommendations tied to the exact products and signals that changed.
The scale behind trusted AI
Revuze is the consumer signal foundation behind the agents, copilots,
and decisions leading brands rely on.
