Lead Software Engineer

Corlen vs Genlook vs Antla: which virtual try-on app should you choose? Quick answer Corlen, Genlook, and Antla are the three virtual try-on apps most visible in the Shopify ecosystem right now. Genlook is built around rendering quality and email capture toward a purchase. Antla is built around a share-for-discount viral loop. Corlen differentiates on body-size aware fitting, a strict no-face-recognition privacy model, and running beyond Shopify into an in-store kiosk and a developer API. All three install as a Shopify app embed; the real differences show up in what each one optimizes for. Virtual try-on stopped being a novelty feature a while ago and became a real category with several serious options competing for the same merchants. That is a good problem to have as a shopper or a store owner, and it also means the three names that keep coming up, Corlen, Genlook, and Antla, deserve an honest side by side look rather than a marketing page from any one of them. Corlen vs Genlook vs Antla at a glance. * Genlook focuses on high-fidelity rendering that preserves fabric texture and drape, plus an AI studio feature for generating marketing images, and integrates with tools like Klaviyo. It leans on a free plan and email capture to move a shopper toward checkout. * Antla generates a try-on from a single shopper photo and centers its product on a "share for discount" loop, where a shopper unlocks a coupon by posting their result, turning try-ons into user-generated content. It publicly lists integrations with tools such as Klaviyo, Attentive, and Postscript. * Corlen installs the same way, with no theme edits, and differentiates on body-size aware fitting, meaning the shopper indicates their own build rather than assuming the garment's stated size fits everyone, a strict privacy model with no face recognition and automatic photo deletion, and reach beyond the online store into an in-store kiosk and a developer API. This category moves fast and feature sets shift often, so treat this as a snapshot rather than a permanent ranking. Always check a provider's current site directly before deciding. How the three apps actually differ. Beyond the one-line summary, the real differences worth weighing come down to a handful of specific questions a merchant should ask before picking any of the three. * What is the growth mechanism built around? Antla's is explicit and public: a shopper shares their result to unlock a discount. That is a real acquisition channel if your brand is comfortable with public sharing and discounting. Genlook leans toward keeping the experience private and pointed at add to cart, capturing an email along the way rather than asking for a public share. Corlen also keeps the try-on private to the shopper, and adds a WhatsApp share option the shopper controls themselves, useful for markets and shopper habits where sharing happens in a private chat with family rather than a public post. * Does fit account for the shopper's own body? A garment labeled "large" means something different across brands, so a try-on that only renders the garment onto a photo without any signal about the shopper's own build can look flattering regardless of whether the size would actually fit. Corlen asks the shopper for their own body size as part of the flow and renders the fit accordingly, rather than assuming a uniform fit every time. * Where else does it run? All three are Shopify-first. Corlen is the option built to also run outside Shopify: the same generation engine powers an in-store try-on kiosk for a physical retail location, and a developer API for a store or platform that wants a custom integration rather than a packaged Shopify app. That matters specifically for merchants who sell in person as well as online, or who want to build their own experience on top of the underlying technology. * What is the privacy model? This is worth checking directly with any provider rather than taking a marketing claim at face value. Corlen's stated policy is explicit: no face recognition run on a customer photo ever, no sharing of the photo, and automatic deletion on a fixed schedule rather than indefinite storage. How pricing compares. Pricing across this category is usage based and changes periodically, so treat the figures below as a snapshot rather than a live quote, and confirm the current numbers directly on each provider's own pricing page before deciding. * Genlook publicly lists a free plan plus paid tiers starting around 9 USD per month, moving up through mid tiers with more monthly generations and a higher tier that removes Genlook branding from the widget. * Antla has no free tier. Its published plans start at 19.99 USD per month for 100 try-ons, with a 49.99 USD per month plan for 500 try-ons, plus a higher-volume tier above that for larger stores, each with a short free trial to test before paying. * Corlen publishes developer API pricing starting at 19.99 USD per month for 100 try-ons, scaling up through higher tiers for larger volume, plus a custom Enterprise tier for stores with real traffic to plan around. A Shopify merchant selects a plan directly inside the Shopify App Store listing rather than through the developer pricing page. Which one should you choose. There is no single right answer, since the three apps are optimized for different goals. If viral growth through public shopper shares and a discount incentive fits your brand, Antla's model is built specifically for that. If you want a free plan to test on your own catalog first and lean on high-fidelity rendering plus email capture, Genlook is worth evaluating. If what matters most is a fit that reflects the shopper's own body, a privacy model with no face recognition and automatic deletion, and the option to run the same technology beyond Shopify in a physical store or a custom integration, that is specifically what Corlen is built around. For a broader checklist beyond just these three names, see how to choose a virtual try-on app for your store. The most reliable way to judge any of them is to test a result on your own photo rather than trust a screenshot: try Corlen on your own photo in a few seconds, no account needed, or read the developer docs if you are evaluating the API directly. Frequently asked questions. What is the main difference between Corlen, Genlook, and Antla? They optimize for different things. Genlook is built around rendering quality and capturing high-intent emails toward a purchase. Antla is built around a share-for-discount loop that turns try-on results into social content. Corlen is built around body-size aware fitting, a strict no-face-recognition privacy model, and running the same engine on Shopify, an in-store kiosk, and a developer API rather than Shopify alone. Is Antla's share for discount feature worth it for my store? It depends on your brand. It is a genuine growth mechanism if you want shopper-generated content and are comfortable offering a discount in exchange for a share. It is a weaker fit for a premium brand that wants virtual try-on to feel private and purchase-focused rather than tied to a public post and a coupon. Does Corlen work outside of Shopify? Yes. The same generation engine also runs an in-store try-on kiosk and a developer API for a custom integration, so a merchant is not limited to a Shopify storefront if they also sell in person or want to build their own flow. See the developer docs for details. How much do Corlen, Genlook, and Antla cost? Genlook publicly lists a free plan plus paid tiers starting around 9 USD per month. Antla's published tiers start at 19.99 USD per month for 100 try-ons, with a higher plan at 49.99 USD per month for 500 try-ons. Corlen's published developer API pricing also starts at 19.99 USD per month for 100 try-ons; a Shopify merchant selects a plan directly inside the Shopify App Store listing. All three change their pricing periodically, so check each provider's current page before deciding. Do these apps store customer photos? This is worth checking directly in each provider's own privacy policy, since it varies and can change. Corlen never runs face recognition on a customer photo, never shares it, and deletes it automatically on a fixed schedule rather than keeping it indefinitely. Ready to add real try-on to your store? Install Corlen on Shopify in minutes, or build it into your own platform with the developer API. See it on your own photo Corlen shows your customers how any garment looks on their own body, in seconds. Try it free, no account needed.

Klaviyo reported second-quarter revenue of $370.6 million, up 26% year-over-year, and raised its full-year 2026 revenue guidance to $1.526 billion to $1.534 billion, representing 24% growth. The company's enterprise segment showed strong momentum, with customers spending $50,000 or more annually growing 36% to 4,477, now representing approximately 40% of total annual recurring revenue. International markets drove significant growth, with revenue outside the Americas up 35% and European revenue outside the UK up 41%. The company's AI-powered Composer agent attracted over 95,000 users in its first month. Klaviyo repurchased $240 million worth of shares during the quarter and ended with $833 million in cash. The company now serves more than 205,000 brands and stores over 9 billion consumer profiles.

Klaviyo buys Agency to build out its AI agents. Published · Aug 6, 2026 Why This is Noise An acqui-hire with undisclosed terms folding a 25-person team into Klaviyo's existing AI agents doesn't change the product, pricing, or any vendor decision for a Klaviyo customer today. Key Takeaways * Klaviyo has agreed to acquire Agency, a three-year-old AI customer success startup founded by serial entrepreneur Elias Torres, for undisclosed terms. * Torres joins Klaviyo as chief product officer, leading Agency's 25-person team to expand Klaviyo's AI agents. * Those agents are Composer, which builds marketing campaigns, and Customer Agent, which handles post-sale support like returns and order tracking. * Agency had raised $32 million from Sequoia, Menlo Ventures, and Felicis before the acquisition. * Klaviyo argues its years of customer data give its agents an edge over competitors like Decagon and Sierra. What happened. Publicly traded e-commerce marketing platform Klaviyo has agreed to acquire Agency, a three-year-old AI-powered customer success startup founded by serial entrepreneur Elias Torres, TechCrunch reported. The terms were not disclosed. Agency, founded in 2023, had raised $32 million from Sequoia, Menlo Ventures, and Felicis before the deal. As part of the acquisition, Torres joins Klaviyo as chief product officer, leading Agency's 25-person team. Torres will accelerate development of Klaviyo's two AI agents: Composer, which builds marketing campaigns, and Customer Agent, which handles post-sale support like returns and order tracking. Klaviyo CEO Andrew Bialecki said the goal is to bring those agents to the company's 200,000 businesses and eventually millions more. The deal is a full-circle reunion: Torres hired Bialecki as one of his first engineers at Performable back in 2010, and Bialecki later invited Torres to angel-invest in Klaviyo's 2015 seed round. Torres previously co-founded Drift, sold to Vista Equity for $1.2 billion in 2021, and Performable, acquired by HubSpot in 2011. Why it matters. The acquisition signals Klaviyo doubling down on AI agents as the next competitive front in marketing automation, betting its accumulated customer data gives it an edge over agent-native rivals like Decagon and Sierra. For marketing teams already on Klaviyo, it's a signal the platform's agent capabilities may deepen, though nothing changes in the product today. This is an acqui-hire with undisclosed terms, so its real scale is unclear, a 25-person team is a talent-and-product tuck-in, not a major platform shift. Whether Klaviyo's data advantage actually translates into better agents than purpose-built competitors is an unproven claim from the acquirer, not a demonstrated result. It's the next big tech revolution: agents. Let's get the band back together, and let's go build. Andrew Bialecki, CEO, Klaviyo Bottom line. Watch whether Klaviyo actually ships meaningfully improved agents under Torres, and whether its customer-data pitch holds up against agent-native competitors in real deployments. The martech agent race is getting crowded, and an acqui-hire is a starting move, not a finished product. For marketing teams on Klaviyo or evaluating e-commerce platforms, per Relve, an AI tools intelligence platform, this is context on where the platform is heading, not a reason to change tools now, worth revisiting once the combined agent product actually ships. Neelam Khan. Lead Editor Neelam Khan is a Lead Editor at Relve, covering AI news, tools, product updates, search trends, and business use cases. She filters noise from useful signals for founders and teams, drawing on her previous work in AI SEO, content strategy, and tool research with Wellows and AllAboutAI.