Aurevia
AI-nativeOne AI sales agent. Every channel.
aurevia.io Customer Service & Success / AI Support Agents
- Monthly visits
- <5K
- Oct 2026
- Public revenue
- Undisclosed
- No public revenue evidence yet
- Entry price
- Unknown
- Freemium model, plan pricing not identified yet
- Launched
- 42d ago
- 2026-10-05 · Est.
Traffic
Last 12 months
Marketing moves
Launches, search & content, referrals, promotionsX accounts@crazystupidceo
- What are colagen products even used for? My mum keeps asking me to get her some from the UK. anyone sells colagen based cosmetics here?
@crazystupidceo · 2026-09-15 · 0 likes · 0 reposts · 22 views
- Solo founder from the UK Building Aurevia Would love to connect with founders and builders from the UK - and understand how the market is treating yu
@crazystupidceo · 2026-09-15 · 5 likes · 0 reposts · 89 views
- 🚀 Launch Alert 🚀 We just launched https://aurevia.io/ on Fazier Please support us here 👇 https://www.fazier.com/launches/aurevia-io
@crazystupidceo · 2026-09-05 · 0 likes · 0 reposts · 29 views
Launched on Fazier (#146 · 23 upvotes · 2 comments)Launch
Aurevia.io — 24/7 AI sales concierge for Shopify stores
Oct 5 · 42d agoLaunch page
At the time: <5K visits/moVisits: prior 2 mo +139%, next 1 mo -62%1 concurrent moveLaunched on Fazier (#141 · 26 upvotes · 2 comments)Launch
Aurevia.io — 24/7 AI sales concierge for Shopify stores
Oct 5 · 42d agoLaunch page
At the time: <5K visits/moVisits: prior 2 mo +139%, next 1 mo -62%1 concurrent move
Third-party reviews & case dossiers
Acquisition breakdowns, engineer reviews & open-source metricsFazier
2026-10-05Source
- What engineers like:
- 24/7 AI sales agent - Provides real-time buying assistance to Shopify shoppers at any time, including outside normal customer-service hours. Shopify product catalogue understanding - Uses the store’s products and approved business information to ground shopper conversations in the merchant’s actual catalogue. Conversational product discovery - Lets shoppers explain what they want naturally instead of relying only on menus, filters or exact search terms. Personalised product recommendations - Recommends products based on the shopper’s needs, preferences, budget, use case or stated requirements. Guided buying journeys - Asks relevant questions to help shoppers narrow down choices when they are unsure what to purchase. Product comparison- Helps customers understand meaningful differences between products, variants or options and choose the most suitable one. Product Q&A- Answers detailed questions using available store and product information, including product features, materials, ingredients, specifications, use cases and other relevant details. AI-powered conversational search - Allows customers to search for products using natural-language requests rather than relying purely on keyword matching. Sizing and suitability guidance - Helps shoppers evaluate which product or option is likely to suit their requirements based on available merchant information. Gift recommendations - Helps customers discover gift options based on recipient, occasion, interests, preferences and budget. Alternative product recommendations - Suggests other relevant products when the original option is unsuitable, unavailable or does not fully match the shopper’s needs. Upselling - Can recommend a higher-value product when the alternative is genuinely more appropriate for the shopper. Cross-selling - Suggests complementary products based on what the shopper is already considering or purchasing. Product bundle discovery - Helps customers identify products that work well together. Add-to-cart assistance - Moves conversations beyond information by helping shoppers take direct purchase actions. Checkout nudges - Helps resolve final questions or hesitation when a shopper is close to purchasing. Cart recovery support - Can re-engage shoppers with items in their cart and help address the uncertainty or unanswered questions preventing checkout. Objection handling - Helps address buying concerns using the store’s approved information rather than simply returning generic support responses. Brand-specific knowledge - Learns from approved merchant content so responses are based on the individual store rather than generic internet knowledge. Customisable brand voice and behaviour - Merchants can control how Aurevia communicates, including tone, behaviour and the type of sales experience they want customers to receive. Human handover - Conversations that require human involvement can be handed over rather than forcing customers through an automated interaction. Response corrections and merchant control - Merchants can correct or refine how Aurevia answers specific questions, helping keep the agent aligned with the business. Conversation analytics - Gives merchants visibility into what shoppers are asking and how conversations are developing. Recurring question discovery - Identifies questions and topics that repeatedly appear across shopper conversations. Customer objection insights - Helps merchants understand the concerns or uncertainties shoppers commonly raise before buying. Product-level conversation insights - Highlights products receiving high levels of questions, interest or shopper attention. Product-page content gap detection - Helps reveal information customers repeatedly need but may not be able to find clearly on the product page. Buying-friction insights - Helps identify areas where customers appear confused, hesitant or unable to make a decision. Customer intent insights - Gives merchants a better picture of what shoppers are actively looking for, not just what pages they visit. Persuasion and conversation-quality analysis - Helps evaluate whether conversations are actually progressing towards meaningful buying actions rather than simply generating chat volume. Sales and marketing intelligence - Conversation data can be used to improve product pages, merchandising, messaging, campaigns and conversion optimisation. Sales-first architecture - Aurevia is designed primarily around helping customers buy rather than functioning as a ticketing or help-desk system with AI added on.
- Best suited for:
- Helping shoppers who do not know exactly what to buy - Aurevia can ask questions about needs, preferences, budget or intended use and narrow the catalogue down to suitable products. Reducing choice overload - Useful for stores with large catalogues where shoppers may become overwhelmed by too many similar products or variants. Helping customers compare similar products - Shoppers can ask Aurevia to explain the practical difference between two or more options instead of manually comparing multiple product pages. Supporting high-consideration purchases - Particularly useful for categories where customers typically need more explanation, reassurance or comparison before purchasing. Answering specific pre-purchase questions - Customers can get immediate answers to detailed questions that may otherwise cause them to leave the website or delay buying. Helping fashion shoppers choose products or variants - Can assist with product discovery, style preferences, suitability and available sizing information. Helping beauty and skincare shoppers navigate complex catalogues - Useful when customers need help understanding differences between products, ingredients, routines or intended use based on available brand information. Helping jewellery shoppers choose between products - Supports comparison, gifting, preferences and higher-consideration purchase decisions. Helping customers shop for gifts - A shopper can describe the recipient, occasion, budget and preferences and receive relevant suggestions. Helping electronics customers understand specifications and compatibility - Useful when technical product differences are difficult to interpret from a standard product page. Guiding customers through home, lifestyle or specialist products - Helps shoppers determine which product best fits their particular requirement or use case. Replacing rigid ecommerce filters with conversational discovery - Customers can describe what they want in ordinary language rather than trying to work out which category or filter combination to use. Recovering shoppers who are close to buying but still uncertain - Aurevia can resolve last-minute questions or objections before checkout. Reducing cart abandonment caused by unanswered questions - Useful where shoppers have already demonstrated purchase intent but still need reassurance, clarification or help. Increasing average order value - Relevant upsells and complementary cross-sells can be introduced naturally during the buying conversation. Recommending complete product combinations - Useful when several products are commonly used together or form a logical bundle. Providing an always-available sales associate during evenings, weekends and peak periods - Allows shoppers to get buying assistance when human teams may not be available. Handling spikes in storefront traffic - Helps stores maintain personalised assistance during campaigns, seasonal periods, product launches or other high-traffic events. Reducing repetitive pre-sale enquiries for human teams - Aurevia can deal with routine buying questions while allowing staff to focus on conversations that genuinely require human involvement. Providing consistent product guidance across the storefront - Gives shoppers access to the same approved product and brand knowledge regardless of when they visit. Identifying products that need better PDP content - If customers repeatedly ask the same question about a product, merchants can use that signal to improve the product description, specifications, imagery or FAQs. Finding customer objections that standard analytics cannot show - Traditional analytics can show where someone dropped off; Aurevia conversations can help reveal what they were uncertain about before they left. Understanding why certain products create more buying friction - Merchants can investigate products generating disproportionate questions, comparisons or objections. Discovering unmet customer demand - Repeated requests for particular features, products, variants or use cases can reveal potential merchandising or product opportunities. Improving product merchandising - Conversation data can show which products customers naturally compare, which alternatives they consider and what attributes matter most to them. Improving marketing messaging - Real shopper language and recurring questions can help teams understand which benefits, concerns and use cases matter most to customers. Improving conversion-rate optimisation - Merchants can use conversation patterns to identify friction points that would be difficult to detect through clicks, sessions or funnel analytics alone. Improving ecommerce search and navigation - Customer conversations can reveal terminology shoppers use that may differ from the store’s own categories or product naming. Learning why shoppers hesitate or leave - Aurevia gives merchants qualitative context behind conversion behaviour rather than only reporting numerical drop-off rates. Giving Shopify brands an AI sales layer without turning the experience into a traditional help desk - Particularly relevant for merchants who want AI to participate directly in product discovery, decision-making and conversion rather than mainly handling support tickets.
Fazier
2026-10-05Source
- What engineers like:
- 24/7 AI sales agent - Provides real-time buying assistance to Shopify shoppers at any time, including outside normal customer-service hours. Shopify product catalogue understanding - Uses the store’s products and approved business information to ground shopper conversations in the merchant’s actual catalogue. Conversational product discovery - Lets shoppers explain what they want naturally instead of relying only on menus, filters or exact search terms. Personalised product recommendations - Recommends products based on the shopper’s needs, preferences, budget, use case or stated requirements. Guided buying journeys - Asks relevant questions to help shoppers narrow down choices when they are unsure what to purchase. Product comparison - Helps customers understand meaningful differences between products, variants or options and choose the most suitable one. Product Q&A - Answers detailed questions using available store and product information, including product features, materials, ingredients, specifications, use cases and other relevant details. AI-powered conversational search - Allows customers to search for products using natural-language requests rather than relying purely on keyword matching. Sizing and suitability guidance - Helps shoppers evaluate which product or option is likely to suit their requirements based on available merchant information. Gift recommendations - Helps customers discover gift options based on recipient, occasion, interests, preferences and budget. Alternative product recommendations - Suggests other relevant products when the original option is unsuitable, unavailable or does not fully match the shopper’s needs. Upselling - Can recommend a higher-value product when the alternative is genuinely more appropriate for the shopper. Cross-selling - Suggests complementary products based on what the shopper is already considering or purchasing. Product bundle discovery - Helps customers identify products that work well together. Add-to-cart assistance - Moves conversations beyond information by helping shoppers take direct purchase actions. Checkout nudges - Helps resolve final questions or hesitation when a shopper is close to purchasing. Cart recovery support - Can re-engage shoppers with items in their cart and help address the uncertainty or unanswered questions preventing checkout. Objection handling - Helps address buying concerns using the store’s approved information rather than simply returning generic support responses. Brand-specific knowledge - Learns from approved merchant content so responses are based on the individual store rather than generic internet knowledge. Customisable brand voice and behaviour - Merchants can control how Aurevia communicates, including tone, behaviour and the type of sales experience they want customers to receive. Human handover - Conversations that require human involvement can be handed over rather than forcing customers through an automated interaction. Response corrections and merchant control - Merchants can correct or refine how Aurevia answers specific questions, helping keep the agent aligned with the business. Conversation analytics - Gives merchants visibility into what shoppers are asking and how conversations are developing. Recurring question discovery - Identifies questions and topics that repeatedly appear across shopper conversations. Customer objection insights - Helps merchants understand the concerns or uncertainties shoppers commonly raise before buying. Product-level conversation insights - Highlights products receiving high levels of questions, interest or shopper attention. Product-page content gap detection - Helps reveal information customers repeatedly need but may not be able to find clearly on the product page. Buying-friction insights - Helps identify areas where customers appear confused, hesitant or unable to make a decision. Customer intent insights - Gives merchants a better picture of what shoppers are actively looking for, not just what pages they visit. Persuasion and conversation-quality analysis - Helps evaluate whether conversations are actually progressing towards meaningful buying actions rather than simply generating chat volume. Sales and marketing intelligence - Conversation data can be used to improve product pages, merchandising, messaging, campaigns and conversion optimisation. Sales-first architecture - Aurevia is designed primarily around helping customers buy rather than functioning as a ticketing or help-desk system with AI added on.
- Best suited for:
- Helping shoppers who do not know exactly what to buy - Aurevia can ask questions about needs, preferences, budget or intended use and narrow the catalogue down to suitable products. Reducing choice overload - Useful for stores with large catalogues where shoppers may become overwhelmed by too many similar products or variants. Helping customers compare similar products - Shoppers can ask Aurevia to explain the practical difference between two or more options instead of manually comparing multiple product pages. Supporting high-consideration purchases - Particularly useful for categories where customers typically need more explanation, reassurance or comparison before purchasing. Answering specific pre-purchase questions - Customers can get immediate answers to detailed questions that may otherwise cause them to leave the website or delay buying. Helping fashion shoppers choose products or variants - Can assist with product discovery, style preferences, suitability and available sizing information. Helping beauty and skincare shoppers navigate complex catalogues - Useful when customers need help understanding differences between products, ingredients, routines or intended use based on available brand information. Helping jewellery shoppers choose between products - Supports comparison, gifting, preferences and higher-consideration purchase decisions. Helping customers shop for gifts - A shopper can describe the recipient, occasion, budget and preferences and receive relevant suggestions. Helping electronics customers understand specifications and compatibility - Useful when technical product differences are difficult to interpret from a standard product page. Guiding customers through home, lifestyle or specialist products - Helps shoppers determine which product best fits their particular requirement or use case. Replacing rigid ecommerce filters with conversational discovery - Customers can describe what they want in ordinary language rather than trying to work out which category or filter combination to use. Recovering shoppers who are close to buying but still uncertain - Aurevia can resolve last-minute questions or objections before checkout. Reducing cart abandonment caused by unanswered questions - Useful where shoppers have already demonstrated purchase intent but still need reassurance, clarification or help. Increasing average order value - Relevant upsells and complementary cross-sells can be introduced naturally during the buying conversation. Recommending complete product combinations - Useful when several products are commonly used together or form a logical bundle. Providing an always-available sales associate during evenings, weekends and peak periods - Allows shoppers to get buying assistance when human teams may not be available. Handling spikes in storefront traffic - Helps stores maintain personalised assistance during campaigns, seasonal periods, product launches or other high-traffic events. Reducing repetitive pre-sale enquiries for human teams - Aurevia can deal with routine buying questions while allowing staff to focus on conversations that genuinely require human involvement. Providing consistent product guidance across the storefront - Gives shoppers access to the same approved product and brand knowledge regardless of when they visit. Identifying products that need better PDP content - If customers repeatedly ask the same question about a product, merchants can use that signal to improve the product description, specifications, imagery or FAQs. Finding customer objections that standard analytics cannot show - Traditional analytics can show where someone dropped off; Aurevia conversations can help reveal what they were uncertain about before they left. Understanding why certain products create more buying friction - Merchants can investigate products generating disproportionate questions, comparisons or objections. Discovering unmet customer demand - Repeated requests for particular features, products, variants or use cases can reveal potential merchandising or product opportunities. Improving product merchandising - Conversation data can show which products customers naturally compare, which alternatives they consider and what attributes matter most to them. Improving marketing messaging - Real shopper language and recurring questions can help teams understand which benefits, concerns and use cases matter most to customers. Improving conversion-rate optimisation - Merchants can use conversation patterns to identify friction points that would be difficult to detect through clicks, sessions or funnel analytics alone. Improving ecommerce search and navigation - Customer conversations can reveal terminology shoppers use that may differ from the store’s own categories or product naming. Learning why shoppers hesitate or leave - Aurevia gives merchants qualitative context behind conversion behaviour rather than only reporting numerical drop-off rates. Giving Shopify brands an AI sales layer without turning the experience into a traditional help desk - Particularly relevant for merchants who want AI to participate directly in product discovery, decision-making and conversion rather than mainly handling support tickets.
Traffic sources
Oct 2026
Traffic breakdown
Channels
- Direct39%
- Organic Search37%
- Referrals9%
- Social6%
- Other10%
Countries
- India100%
Search
Domain authority —Domain registered 2024-11-26
| Keyword | Monthly volume |
|---|---|
| aurevia | 6,760 |
| aurevia feed | 260 |
| aurevia globai pte. ltd | 250 |
| aurevia feed addra | 210 |
| aurevia marketing | 200 |
Traffic data: Vaneform
Pricing
Free
Free
100 AI messages a month · 1 seat
Trial: Starter, Pro and Scale each start with a 14-day free trial · Free tier included · Observed 2026-11-04 · Pricing page
Pages & changes
Tracked since 2026-10-05
Key pages
Weekly snapshotsaurevia.io/ Snapshot 2026-11-04
Changes
No pricing, plan, or positioning changes detected since tracking started.
Questions & evidence
- How much does Aurevia cost?
- Free: Free. Observed 2026-11-04. Check the source for current billing terms, usage limits and taxes.Source
- How much website traffic does Aurevia get?
- Vaneform estimates <5K website visits in 2026-10. Visits can include repeat visits; this estimate measures web traffic separately from paying customers or revenue.Source
- What is Aurevia and what platforms does it support?
- Aurevia is catalogued under AI Support Agents: One AI sales agent. Every channel.. Supported platforms: Web.
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