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ASO — 9 Jul 2025
The Ultimate Guide to 40 AI Tools for App Marketing Teams in 2025
Anastasiya Starovoytova
Anastasiya Starovoytova 
Most growth marketers stop at ChatGPT. But what about other tools?
Here’s a breakdown of next-gen AI tools that can be useful for app marketing — including what they’re best at, what they offer, and what type of AI powers them.
This article also features opinions of Thomas Kriebernegg, SplitMetrics Agency General Manager, about different AI tools.
For me personally, number one tool is definitely ChatGPT. I use it for almost everything — both professionally and personally — on a daily basis. It’s absolutely essential to my workflow.
I also use Midjourney quite a lot for generating images. It’s become a go-to tool whenever I need something visual.
And then, not daily, but at least weekly, I use AI-powered code tools like Cursor or Windsurf. These are really helpful for tasks related to coding or debugging — super handy for developers like me.
These tools use generative AI to create ad copy, metadata, push notifications, and more — helping you speed up iteration while aligning tone, format, and brand intent.
Best for: Generating ad copy, email content, push notifications, and product descriptions.
What it offers: Copy.ai is a generative AI tool built specifically for marketers. It offers pre-trained templates for various content types — headlines, CTAs, email subject lines, social posts — and can adjust tone, format, and audience targeting. It’s optimized for speed and marketing intent, making it ideal for rapid creative testing across campaigns.
AI type: Generative.
Example of usage: You’re running UA campaigns for a productivity app and need 10 Facebook ad variations. You enter your value prop (“reduce distractions, organize your day”) and let Copy.ai generate different ad versions: motivational, professional, casual.
Best for: Long-form content with a conversational, context-aware tone.
What it offers: Claude is known for its more “aligned” responses — polite, nuanced, and coherent in long conversations. It’s excellent for writing assistant-style work like onboarding flows, help center content, or complex push journeys. Claude retains context better over longer sessions compared to ChatGPT.
AI type: Generative.
Example of usage: You’re building an in-app onboarding chatbot for a health tracker. Claude helps write a 5-step welcome sequence that adapts tone by user goal: weight loss vs. improved sleep. It even suggests tone adjustments if the copy feels overly clinical or too informal.
Best for: Research-backed content, summaries, and idea validation.
What it offers: Perplexity is a search-powered AI assistant that gives you real-time, sourced answers from the web. It’s like ChatGPT with citations. Marketers use it to validate claims, find competitor angles, or summarize trends before creating content.
AI type: Generative.
Example of usage: Before writing a pitch on what to do for improving your app based on your competitors’ efforts, you use Perplexity to pull up the latest data, compare app store reviews, and cite stats in your copy. It saves hours of manual Google searches and reduces factual errors in content.
Best for: Integration with Google tools + real-time, fact-based content.
What it offers: Gemini is designed for productivity — it pulls from Google Search, Docs, Sheets, and YouTube, making it ideal for marketers working within the Google ecosystem. Gemini is especially good at live data use, spreadsheet generation, and summarizing long-form research.
AI type: Generative.
Example of usage: You’re preparing a performance summary for your app’s Q1 acquisition. Gemini accesses your Google Sheets (media spend, CPI, ROAS), summarizes key insights, and drafts an internal report with a visual bullet breakdown. Bonus: it can link to relevant YouTube videos or data sources in your report.
Best for: Brand-consistent, multi-channel marketing content.
What it offers: Jasper is tailored for marketing teams that want to generate on-brand content across blogs, emails, ads, and web. You can upload brand voice guidelines and product positioning, then let Jasper generate content that adheres to them. It supports workflows for teams, with review and approval features.
AI type: Generative + prescriptive.
Example of usage: You’re launching a new premium feature in your budgeting app. You enter the feature details, target persona, and brand tone (“friendly, expert, modern”). Jasper outputs a launch email, app banner copy, blog announcement, and Instagram captions — all consistent in tone and positioning.
Best for: Writing short-form marketing copy like push notifications, social captions, and app descriptions.
What it offers: Rytr is a generative AI writing assistant that helps you create punchy, context-aware content quickly. It supports dozens of use cases. You input your key idea, select the tone, and Rytr generates several optimized variations. It works in 30+ languages and is lightweight enough for fast, daily use.
AI type: Generative.
Example of usage: You’re promoting a flash discount for 1-hour grocery delivery in select cities. You turn to Rytr for short, effective push notifications.
Best for: Writing and optimizing social media posts across multiple platforms.
What it offers:Buffer’s AI Assistant helps you ideate, draft, refine, and repurpose social content, all within Buffer’s scheduling tool. It auto-adjusts tone, format, and length for each platform. Editing options let you iterate without retyping. Bonus: it’s free and unlimited for up to 3 channels.
AI type: Generative.
Example of usage: A growth marketer at a fitness tracking app uses Buffer’s AI Assistant to announce a new 7-Day Step Challenge across social channels. They describe the campaign goal and target audience, and the tool instantly generates platform-specific posts: a fun, emoji-filled caption for Instagram, a concise version for Twitter, and a polished announcement for LinkedIn.
From app icons to screenshots and promo banners, these tools help turn prompts into visuals. Whether you’re building ASO assets or experimenting with creative directions, AI can now support your efforts.
I’d say it’s more at the concept stage right now. With the latest release of GPT-4.0 — which brought a major boost to image generation capabilities — I think it’s definitely possible to create solid ad creatives, especially static ones like banner graphics.
Of course, we could debate whether those outputs are final-ready. In most cases, they serve more as advanced inspiration. You’d probably still want to bring those concepts into a tool like Figma or Canva to polish and recreate the final version.
Best for: Generating illustrative-style app icons, feature graphics, and conceptual visuals.
What it offers: DALL·E generates high-resolution images from natural language prompts. You can use it to create custom, themed app icons, mockups for store listings, or stylized visuals for seasonal campaigns (e.g., Halloween-themed icons). With inpainting support, you can also edit or extend images.
AI type: Generative.
Example of usage: You want a fresh app icon for a mindfulness app — something soft, with “a peaceful moon and mountain in pastel gradients.” You describe it in DALL·E and get multiple icon-ready options. You use inpainting to adjust contrast and add your logo subtly in the corner.
Best for: Artistic, stylized visuals with creative depth.
What it offers: Midjourney excels at rich, detailed visuals that feel hand-crafted. It’s especially good for concept art, lifestyle imagery, or mood-based assets that need more emotion or texture. It works via Discord-based prompts and is favored by creators for its painterly look.
AI type: Generative.
Example of usage: You’re designing launch visuals for a fantasy RPG app. You prompt Midjourney with “epic dragon flying over ancient city at dusk, cinematic lighting.” The result? Ad creatives that look like a movie poster — perfect for UA campaigns.
Best for: Quick asset production for app store and ad creatives.
What it offers: Canva’s Magic Design suggests layouts, visuals, and templates based on your text or brand input. With Magic Media (Pro), you can also generate new images using AI — helpful for crafting social ads, or promotional banners on tight timelines.
AI type: Generative + prescriptive.
Example of usage: You’re announcing a major app update across your social channels. You input the text: “New Dark Mode is Live!” Magic Design generates five clean, scroll-stopping Instagram story templates using your app colors and logo.
Best for: Fast, watermark-free generation of app icons with full usage rights.
What it offers: This lightweight generative AI tool is purpose-built for developers and marketers who need quick, clean app icons. Unlike most free AI generators, it produces icons without watermarks, giving you assets ready for testing or publishing. It’s intentionally simple: enter a short, clear prompt and get unique icon visuals instantly.
AI type: Generative.
Example of usage: You’re testing new value propositions for your mindfulness app. With the AI App Icon Generator, you quickly create 4 visual variations (“minimal lotus,” “moon and stars,” “pastel head silhouette”).
Best for: Generating icons, character art, and gaming visuals.
What it offers: Leonardo is trained on styles optimized for game development and mobile content. It supports fine-tuning, so you can train a model on your app’s visual style and use it for consistent iconography or in-game artwork.
AI type: Generative.
Example of usage: You want 5 variations of a health app icon with an abstract pulse symbol in different color schemes. Leonardo lets you generate these in a unified style, aligned with your brand.
Best for: Generating high-quality app icons and marketing visuals in a wide range of styles.
What it offers: Shutterstock AI is a generative image tool trained on content from Shutterstock’s contributor base. It’s particularly effective for app marketing teams looking to produce app icons, store visuals, concept art, or ad creatives across various design styles. You simply input a prompt and generate royalty-cleared visuals ready for commercial use.
AI type: Generative.
Example of usage: You’re launching a wellness app with a new seasonal campaign and need themed app icons and banner illustrations. With Shutterstock AI, you generate winter-themed icon variants using prompts like “minimal snowflake design with blue palette” or “cozy winter cabin in flat style.”
Best for: High-quality, on-brand visuals for app store creatives.
What it offers: Adobe Firefly is a professional-grade generative AI tool for creating visuals from text prompts. It supports multiple styles, lighting presets, and reference uploads to fine-tune brand consistency. Integrated with Adobe Express, it enables seamless editing of assets like icons, screenshots, and display ads, making it easy to localize or version for different campaigns.
AI type: Generative.
Example of usage: You’re preparing a new App Store campaign for your budgeting app targeting Gen Z. You want a set of eye-catching screenshots with visuals in a bold flat-design style. Firefly lets you generate multiple variations quickly.
Need cinematic trailers, UGC-style promos, or animated explainers? This new wave of video AI tools lets you generate and edit video content — with support for scripting, voiceovers, camera movement, and character consistency.
I’d even go one step further and say that in maybe half a year, or a year at most, these tools could be capable of generating full Hollywood movies. The progress is happening incredibly fast — it’s really exciting.
Best for: Ultra-realistic, cinematic short-form videos with native audio — ideal for high-fidelity promos and app launch teasers.
What it offers: Veo 3, part of Google’s Gemini and Flow platforms, generates clips in high-quality resolution, complete with ambient audio, sound effects, and dialogue directly from prompts. It excels at real-world physics, visual fidelity, and precise prompt adherence. Users can also provide reference images for consistent characters, control framing and motion with camera tools. Veo 3 is currently available only in the U.S.
AI type: Generative.
Example of usage: You want a high-impact teaser for a mystery puzzle game. You write: “A lone detective in 4K walks into a foggy alley, picks up a glowing artifact, then hears footsteps.” Veo 3 returns a cinematic clip with natural ambient city noise, dialogue cue, and dynamic lighting.
Honestly, I think we’re already at a really advanced point with tools like Google Veo 3 — if you have access to it, there’s a lot you can do. Especially when it comes to user acquisition creatives, it’s changing the game.
Traditionally, there’s been this mindset that UA creatives need to be super polished and high-end. But I’d argue that’s not necessarily the case anymore — or at least, not in the same way.
I’ve been in this industry for over 20 years, and I remember the days when companies would spend thousands of dollars creating corporate videos — hiring videographers, filming in multiple locations, going through long production cycles just to get a highly polished final product. Today, tools like Veo 3 are making that process significantly faster and more accessible.
I don’t think that level of high-end production is necessary anymore. The demand for ultra-polished, high-budget video has really dropped — especially now that people are used to seeing content made by individuals or small teams. With today’s AI tools, you can already do a lot in terms of user acquisition. The quality is more than good enough for most use cases, and the speed and flexibility are a huge advantage.
Best for: Creating viral-ready short-form videos fast.
What it offers: Crayo is an all-in-one AI video tool built for short-form content. It helps you script, narrate, subtitle, and style videos using templates optimized for TikTok, Reels, and YouTube Shorts. Key features include fake text chat videos, Reddit story-to-video conversion, AI voiceovers, split-screen edits, and background music or vocal removal — making it perfect for quick, social-native video production.
AI type: Generative.
Example of usage: You want to create a short clip promoting a new feature in your fitness tracker app. You write a fake text exchange showing two friends planning workouts, then use Crayo to auto-generate the visuals, voiceover, and subtitles.
Best for: AI-powered video editing and remixing.
What it offers: Runway lets you generate, edit, and remix videos using AI. It offers features like background removal, motion tracking, AI green screen, and text-to-video generation. It’s great for motion-based creatives in playable ads.
AI type: Generative.
Example of usage: You want a 6-second promo for an educational app. You input your script, select a motion template, and use Runway’s AI to create a visual sequence with animated text, background effects, and transitions, no editor needed.
Best for: Versatile AI video creation with high flexibility and model selection.
What it offers: Pollo AI supports text-to-video, image-to-video, and video-to-video generation, along with consistent character animation and advanced AI effects. It also includes tools for lip sync, face swaps, object removal, upscaling, and video extension — plus text-to-image and image-based generation from models like DALL·E 3, Imagen 3, and Stable Diffusion 3.
AI type: Generative.
Example of usage: You’re promoting a character-driven RPG app and want a short cinematic trailer. You upload concept art of the main character, add a prompt for an action sequence, and use Pollo AI’s image-to-video tool with lip sync and animation. The result is a dynamic teaser with voice, motion, and visual effects.
Best for: Advanced AI video generation with camera control and character consistency.
What it offers: Kling AI supports text-to-video and image-to-video workflows, with features like lip-syncing, camera movement, motion brush, face modeling, and video extension. Its “Elements” feature lets you upload multiple images for consistent characters or objects across frames. You can also upload specific start/end frames for finer visual control, and choose between generation modes depending on quality or speed needs.
AI type: Generative.
Example of usage: You’re building a cinematic reveal for a new language-learning app. Using Kling AI, you upload a branded character image and write a prompt: “The character opens a glowing textbook in a modern classroom; words float into the air.” Kling’s motion brush and camera tilt features help animate the floating text and create an entrance shot.
I’ve been using Kling AI. What it does quite well is generate videos from images — you can create short clips, usually around five to ten seconds. I use it from time to time to create fun, visually interesting content and just experiment a bit.
Best for: Fast, creator-driven video generation from ideas and sketches.
What it offers: Pika burst into the spotlight with its viral Pikapocalypse ad — a cinematic demo that showcased the platform’s potential. Built by Stanford AI researchers, Pika is a text-to-video and video-editing platform focused on creative flexibility and ease of use. It allows users to generate video from scratch or modify existing footage using voice or text commands. With support for character animation, 3D movement, and evolving cinematic styles, Pika positions itself as the “imagination engine” for creators. It’s frequently updated based on user requests.
AI type: Generative.
Example of usage: You’re launching a new productivity app for Gen Z students. Instead of hiring a full production team, you use Pika to create a 15-second short: “A teenage girl conquers a mountain of tasks on her phone while the world transforms from chaos to calm around her.” You generate scenes with stylized transitions, edit them via voice commands, and tweak movement and pacing.
Best for: Scalable, avatar-based video creation for app tutorials, feature explainers, short ads.
What it offers: Synthesia enables app marketers and product teams to create professional-quality videos with AI avatars and voiceovers in 140+ languages, with no camera crew or voice talent needed. Features include branded video templates, your own avatar, voice cloning, and seamless team collaboration.
AI type: Generative.
Example of usage: You’re rolling out a new budgeting feature in your fintech app. To explain it clearly to users in multiple markets, you script a 45-second walkthrough and generate versions in English and Hindi using Synthesia. Each version features a trustworthy-looking avatar explaining how to set spending limits, with screen UI visuals.
These tools help UA and growth teams make smarter, faster decisions with predictive and prescriptive models.
I see these tools popping up here and there, but I haven’t tested most of them yet. From what I can tell — and based on how we’re approaching the topic — I’d say many of these AI tools are well-suited for beginners starting out with user acquisition. When you’re new and unsure what to do, AI can really help guide you through a lot of the initial steps.
But for more advanced campaigns — especially on platforms like Meta or TikTok — success often comes down to deeply understanding all the fine-tuned settings and how to configure them properly. And in my opinion, no AI tool is quite there yet in outperforming a human expert when it comes to that level of detail.
On the other hand, with Apple Ads, I genuinely think AI is already at the same level, maybe even better than a human. Mainly because it’s mostly about keywords, not creatives.
Best for: AI-powered performance insights and campaign decision-making.
What it offers: Adjust Growth Copilot is a conversational AI assistant built specifically for mobile marketers. It transforms raw data into contextual insights, helping you understand campaign performance, creative effectiveness, and budget allocation in real time. Instead of pulling reports manually, you can ask natural-language questions and get clear, actionable responses.
AI type: Prescriptive + predictive.
Example of usage: You’re running multiple campaigns for a finance app and want to know which creatives are underperforming on Android. You ask Growth Copilot directly in the chat interface. Within seconds, you get the necessary info — all without needing to dig through dashboards.
Best for: Autonomous optimization of digital advertising campaigns.
What it offers: Albert.ai is a self-learning AI platform designed to manage and optimize digital advertising across channels like Google Ads, YouTube, Facebook. It automates the planning, building, optimization, and reporting of ad campaigns — from keyword grouping and ad variations to budget allocation and bid strategy. Albert identifies untapped audiences, adjusts spend dynamically, and tests creative variations to maximize performance with minimal human oversight. The AI acts as a tireless digital marketer, helping brands scale ad performance efficiently.
AI type: Prescriptive.
Example of usage: You’re launching a new fitness app and want to run cross-platform ads without manually managing dozens of ad sets. You feed Albert your target audience and creatives, and it automatically builds and optimizes campaigns across Facebook and Google. Within days, Albert reallocates budget to top-performing ad groups, tests new creatives for conversion lift, and uncovers a high-converting demographic you hadn’t considered.
Best for: Scaling and optimizing creative performance across user acquisition campaigns.
What it offers: AppsFlyer’s Creative Optimization is an AI-powered solution that helps UA and BI teams understand which ad creatives drive the best performance — from impressions to LTV. It analyzes creative assets scene by scene, surfacing patterns, visual elements, and formats linked to higher click-throughs, lower CPIs, and stronger retention. By centralizing granular creative data, it replaces guesswork with reliable, testable insights. This enables teams to make high-impact creative decisions faster, align cross-functional workflows, and scale up winning variations with confidence.
AI type: Prescriptive + predictive.
Example of usage: You’re running a gaming campaign with multiple ad variants. With Creative Optimization, you discover that short intros with gameplay footage outperform animated explainer scenes by 40% in day-7 retention. You iterate based on this insight and double down on top assets across channels
Best for: Instant natural language insights into marketing performance and ROI.
What it offers: Singular now integrates with Claude, enabling marketers to query live marketing data using natural language — no dashboards, no code. Powered by Anthropic’s Model Context Protocol (MCP), this integration connects LLMs directly to Singular’s unified datasets. Users can ask questions like “Which creatives are fatiguing?” or “Where is CPI rising fastest?” and receive structured insights, charts, and actionable suggestions. It supports campaign-level and creative-level analysis across all major platforms, helping marketers make faster, data-driven decisions.
AI type: Prescriptive + generative.
Example of usage: You’re managing multiple app campaigns and want to know which ad partners are underperforming. Instead of running SQL queries or digging through dashboards, you ask Claude via Singular: “Which partners delivered the lowest ROI last week?” Within seconds, you get a ranked list with visual breakdowns and optimization suggestions — ready to act, no technical expertise needed.
Best for: Scaling and optimizing Apple Ads with predictive AI.
What it offers: SplitMetrics Acquire is a performance marketing platform built specifically for Apple Ads. It combines robust automation and campaign management with Samba 2.5, its built-in predictive AI for bid optimization. Samba dynamically adjusts bids across campaigns based on real-time performance data, helping you hit ROAS targets faster and with less manual effort.
AI type: Predictive.
Example of usage: You’re running Apple Ads for a budgeting app in 10 markets and need to hit a specific ROAS without increasing spend. With SplitMetrics Acquire and Samba 2.5, you set your ROAS goals and let the AI automatically reallocate bids across campaigns.
Understanding what users think — in app reviews, on social, or in support tickets — is essential for product and marketing. These tools analyze user feedback at scale to identify friction points, emotional tone, and unmet needs.
Best for: No-code sentiment analysis from reviews and social media.
What it offers: Uses ML to classify sentiment, extract topics, and highlight emotion in app store reviews or social comments.
AI type: Predictive + prescriptive.
Example of usage: You launch a new feature and see mixed reviews. Feed recent app reviews into MonkeyLearn. The AI flags a common pain point: “slow load time.” You escalate it to the dev team and set up a push campaign clarifying feature use.
Best for: Mobile app support and marketing teams for scalable analysis of user feedback and support tickets.
What it offers: Breaks down sentiment, syntax, and entities. Useful for turning qualitative feedback into trends.
AI type: Predictive.
Example of usage: You analyze 10,000 customer support logs to find recurring frustration around billing. Sentiment tagging and topic extraction reveal it peaks after free trials expire. You revise trial flows and trigger earlier upgrade nudges.
Best for: Emotional tone detection in user reviews or marketing content.
What it offers: Detects deeper emotions like fear, joy, sadness — critical for tone-sensitive brands.
AI type: Predictive + prescriptive.
Example of usage: You’re rebranding your wellness app. Use Watson NLU on existing ad copy to detect emotional mismatches (e.g., anxious tone where you intended calm).
Best for: Identifying app feature gaps through App Store review analysis.
What it offers: ReviewMind uses AI to analyze up to 500 recent App Store reviews and extract actionable insights via sentiment or SWOT analysis. It highlights what users love, hate, or wish for — and surfaces patterns, bugs, pricing friction, or UX issues. Ideal for product teams, indie makers, or marketers researching competitors or validating product ideas.
AI type: Generative + prescriptive.
Example of usage: You’re planning to build a new note-taking app. You run ReviewMind on the top 3 category leaders and discover repeated complaints about syncing issues and missing markdown support. You prioritize seamless sync and markdown in your MVP and export a sentiment report for stakeholder review.
Best for: Quick AI-driven summaries of recent App Store reviews.
What it offers: ReviewWizard generates instant reports from up to 50 recent App Store reviews using GPT-4o. Users paste an app link and get a sentiment-driven summary with key positives, negatives, and feature trends. It’s lightweight, privacy-conscious (local storage), and runs on your own OpenAI API key — perfect for indie developers and early-stage product research. Currently in beta and limited to last month or last quarter’s reviews.
AI type: Prescriptive + generative.
Example of usage: You’re exploring monetization gaps in fitness apps. You paste a competitor’s App Store link into ReviewWizard and generate a report in seconds. It surfaces consistent friction around subscription prices and hidden features, helping you validate a freemium-first approach for your own app.
Best for: ASO teams who want to combine app review analysis with broader optimization strategies.
What it offers: App Radar’s AI App Review Summaries feature helps you monitor and analyze user feedback on any app in the App Store or Google Play — including your competitors. You can generate AI-powered summaries for selected countries and date ranges, receive highlights weekly or monthly, and quickly identify strengths, weaknesses, feature requests, and UX pain points.
AI type: Generative + prescriptive.
Example of usage: You’re launching a fitness app in Germany and want to understand your competitors’ weak spots. You select three rival apps in App Radar, pick the German market, and generate AI summaries of recent reviews.
Best for: Monitoring what people are saying about your app on social media and beyond.
What it offers: Brandwatch is a social listening tool that helps app marketers stay ahead of conversations happening across social media, blogs, forums, and news outlets. It uses AI to provide real-time sentiment analysis, trend identification, and audience insights. You can track how users feel about your brand, competitors, or key features — and filter data by platform, topic, or geography.
AI type: Predictive + Prescriptive.
Example of usage: After releasing a new onboarding flow, your app’s store reviews stay neutral, but Brandwatch detects a spike in negative sentiment on Reddit, citing login bugs. AI flags this pattern before it reaches critical mass, allowing your team to fix the issue and update your messaging before it impacts ratings or retention.
These tools help you scale across markets with tone-aware, visually verified, and brand-consistent language — from UI copy to video dubbing — often with in-context editing and automation.
Best for: Enterprise-level localization.
What it offers: Smartling goes beyond translation with AI-powered quality estimation, emotion/context alignment, and visual previews. It adapts language tone and readability to match user segments (e.g., professional vs. casual). Also includes human-in-the-loop workflows and centralized vendor management.
AI type: Predictive + prescriptive.
Example of usage: You’re localizing for LATAM and Spain. Smartling detects that your Spanish translation for “Track expenses” reads as formal in Spain but awkward in Mexico. It flags tone inconsistency and offers alternative phrasing optimized per region.
Best for: Developer-first localization of an app’s UI and content with AI-enhanced tools.
What it offers: Tolgee is an open-source, developer-focused localization tool that uses AI for auto-translation and context handling. It supports in-context editing directly in the UI, making it easy for marketers and product teams to see how translations will render inside the app.
AI type: Generative + prescriptive.
Example of usage: You’re updating your onboarding flow and want instant previews in French and Italian. Tolgee lets you click on the UI, type translations, or use AI suggestions, and see exactly how text appears in-app.
Best for: End-to-end localization pipelines for growth-stage teams.
What it offers: Phrase supports automation, collaboration, and integration at every step of the localization process. Its AI capabilities include translation memory, auto-tagging, string validation, and tone consistency checks. It’s a good all-rounder for growing teams scaling internationally.
AI type: Prescriptive.
Example of usage: Your finance app is scaling into Southeast Asia. Phrase auto-tags reused strings (e.g., “monthly budget”) and applies consistent, localized versions across markets while flagging financial/legal terms that need human review.
Best for: Accurate, culturally-aligned Chinese localization.
What it offers: DeepSeek is an AI language model trained on massive Chinese corpora, making it ideal for translating or creating content in Simplified Chinese with fluency. It can generate or refine Chinese-language UI copy, app store descriptions, and ads that feel truly native to a Chinese-speaking audience.
AI type: Generative.
Example of usage: You’re preparing for an App Store launch in mainland China. DeepSeek helps localize your app description and feature highlights into fluent, persuasive Chinese — avoiding awkward direct translations and aligning better with user expectations and norms.
Best for: End-to-end AI-powered translation management at scale with human-AI collaboration.
What it offers: Smartcat is a full-stack AI localization platform built for teams translating content into multiple languages — websites, apps, videos, e-learning, and more. Its standout feature is the Smartcat Marketplace of 500,000+ vetted linguists and the ability to automate everything from translation to payment. Smartcat uses adaptive AI engines that match each language pair and content type to the best-performing translation model. It also learns from human edits and previous projects.
AI type: Generative + prescriptive.
Example of usage: You’re launching your productivity app in 8 new markets. You upload your in-app text, onboarding scripts, and App Store metadata to Smartcat. The system auto-selects the best-fit AI engine for each language, pre-translates your content, and assigns region-specific linguists for human review — all inside one dashboard.
Best for: Scalable, AI-powered video and audio localization (dubbing, subtitles, and voice cloning).
What it offers: Rask AI is a powerful platform for automating video and audio translation into 130+ languages. It offers AI-generated dubbing, voice cloning, lip-syncing, subtitle generation, and multi-speaker support — all optimized for marketing, education, and creator-led content. It’s available both as a web platform and via API for high-volume localization. With VoiceClone and Lip-Sync, it preserves the authenticity of original creators — an ideal solution for localizing influencer videos, app tutorials, testimonials, and UGC.
AI type: Generative + prescriptive.
Example of usage: You’re running a campaign with influencers who film short reviews and how-to videos for your fitness app. Instead of re-recording voiceovers or subtitling every version, you use Rask AI to automatically dub their UGC into French, Korean, and Arabic — while keeping the original creator’s voice style via VoiceClone.
Best for: Fast, high-quality translation of in-app copy, onboarding flows, and campaign assets.
What it offers: Lokalise AI combines generative AI translation with a built-in TMS, making it ideal for mobile teams localizing UX content at scale. It supports one-click rephrasing, tone adjustments, and SEO optimization — useful for web landers, banners, and push copy. Style guides and glossaries keep voice consistent, while integrations with Figma and Google Sheets streamline collaboration across product and growth teams.
AI type: Generative + prescriptive.
Example of usage: You’re localizing onboarding screens and promo banners for your productivity app. Lokalise AI translates everything in bulk, applies brand tone, and lets your team tweak phrasing for layout fit directly in Figma.
