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Building AI-powered apps traditionally involves lengthy development cycles, high costs, and the need for skilled developers to integrate AI functionalities like machine learning models or natural language processing.
As a founder or product lead, you're likely managing tight timelines and budgets while aiming to launch innovative apps that leverage AI for features such as personalized recommendations or automated workflows.
This is where Bubble offers a compelling alternative - it's a powerful no-code platform that enables users to visually build and scale web applications, with capabilities to integrate AI tools through APIs or plugins, significantly reducing the need for manual coding and speeding up the prototyping and deployment process of AI-powered solutions.
Choosing the right Bubble agency is essential because the wrong partner can result in inefficient builds, difficulties integrating AI APIs, or costly delays, while leading agencies deliver robust, scalable products that generate tangible business value.
On this page, we've curated top-performing Bubble agencies with demonstrated expertise in AI-integrated app development, featuring side-by-side comparisons, client performance benchmarks, and a practical checklist to help you evaluate and select the right partner for your project in 2025.
Why Bubble for AI-Powered Apps?
Bubble is a visual development tool that enables rapid creation of full-stack web applications without writing code, making it particularly suited for integrating AI functionalities like machine learning models, natural language processing, or predictive analytics. Technically, it offers a backend-as-a-service with database capabilities, workflow automation, and support for API integrations, which are essential for handling AI-related data flows. Strategically, it allows entrepreneurs and teams to prototype, iterate, and scale AI apps quickly and cost-effectively, reducing time-to-market compared to traditional development.
Bubble vs Alternatives for AI-powered Apps
Traditional Development: Building an AI-powered app with custom code (e.g., using Python with frameworks like Flask or Django, plus AI libraries like TensorFlow or PyTorch) requires skilled developers, significant development time, and higher costs (often $30,000–$100,000+ for a minimum viable product depending on complexity).
Bubble enables non-technical users to build functional apps in weeks at lower cost, including built-in hosting and deployment, though advanced AI capabilities may still require using external APIs.
Bubble vs Traditional development
Glide: Glide is effective for creating mobile-friendly apps from spreadsheets but lacks the advanced backend workflows, conditional logic, and API flexibility needed for more sophisticated AI use cases. This makes it less suitable for apps requiring real-time AI inference or complex data interactions.
-Adalo: Adalo specializes in creating native mobile apps and offers ease of use for visual development. However, it has limitations in terms of robust workflow handling, relational database logic, and external API orchestration compared to Bubble, making it less optimal for web-based or AI-integrated applications at scale.
Key Features of Bubble for AI-Powered Apps
Bubble’s capabilities make it technically viable for building AI-powered tools that generate content, analyze data, or provide personalized user experiences. Here are four notable strengths:
- Seamless API Integrations: Bubble's API Connector allows integration with AI services like OpenAI (e.g., ChatGPT), Google Cloud AI, or Hugging Face. Users can send and receive data to/from these AI endpoints without writing server-side code, allowing implementations such as chatbot interactions or content generation.
- Powerful Workflows and Backend Logic: Bubble allows creators to build backend workflows, including condition-based triggers and scheduled operations. This supports applications that need to automate data fetching, request processing from AI services, and response routing.
- Scalable Data Management: Bubble provides a privacy-rule-based, scalable cloud database that handles data types like lists, relationships, and even file uploads. This setup accommodates storage of AI outputs, user inputs, behavioral analytics, or other complex datasets, although performance at scale may benefit from third-party backend optimization.
- Responsive UI and User Authentication: Bubble offers fully customizable, responsive UI design for all screen sizes. It includes built-in tools for user authentication, authorization workflows, and session control, enabling secure and personalized use of AI features within web applications while supporting compliance with major data privacy regulations.
Evaluation criteria
We selected agencies for our “Top Bubble Agencies for AI‑Powered Apps” list based on five core factors that matter most when building intelligent, data‑driven solutions
Below are the five criteria we applied:
Real AI Experience
Have they shipped AI‑powered features on Bubble? We checked for proven chatbots, machine‑learning workflows, or predictive tools they’ve built and maintained.
Scalability in Practice
Can their apps handle growing data and users without bogging down? We favoured agencies that’ve taken projects from MVP to high‑traffic production.
API & Workflow Mastery
Bubble gives you an API connector and workflow engine- are they using it to its full potential? We looked for creative integrations and clean, reliable logic.
Design + UX for AI
AI is only as good as the experience around it. We scored agencies on how they design interfaces that make smart features feel intuitive and human.
Post‑Launch Support
AI models evolve and so do user needs. We prioritised teams that stick around for fine‑tuning, data monitoring, and ongoing improvements.
Top 5 Agencies for AI-powered Apps
1. Goodspeed
Goodspeed is a top choice for teams building AI-powered apps with Bubble. Their 4–6 week sprint model helps you launch fast, with clean architecture that’s ready to grow.
They’ve helped startups like Pockla raise £1.6M after launch, and supported MyAskAI in reaching $300K ARR and 40,000 users while improving performance and cutting costs.
Goodspeed handles the full build: UX, database, APIs, all within Bubble. After launch, they stay involved with feature updates, performance fixes, and product improvements.
If you need a team that moves fast, builds solid, and knows how to support scaling, Goodspeed is hard to beat.
2. Airdev
Airdev is one of the biggest Bubble agencies worldwide. They’re known for speed and precision, thanks to their custom Canvas framework that makes builds fast and repeatable.
They helped launch TheHair.App, an AI-powered salon tool that analyses photos to recommend personalised treatments based on hair type and face shape.
Airdev is great at handling complex logic, APIs, and user experience. They also offer ongoing support for improvements and growth.
If you’re building a large or complex app and want proven processes, Airdev is a reliable option.
3. Zeroqode
Zeroqode is known for its huge library of Bubble plugins and templates, over 800 and counting. This makes it easy to add AI features, like chatbots and content tools, without building from scratch.
Their AI Kit gives you a ready-made setup to launch fast, and all their templates are mobile-friendly and responsive.
They also keep their plugins updated and offer support and learning resources if you need help.
If you want to move quickly using pre-built tools and stay flexible, Zeroqode offers a plug-and-play approach that works well.
4. Rapid Dev
Keenethics OU combines Bubble development with deep AI expertise, integrating features like chatbots, recommendation systems, and image recognition directly into your app.
They focus on building AI tools that actually solve problems—whether it’s personalising user content or automating repetitive workflows—rather than adding tech for the sake of it.
Their team also prioritises clean, scalable architecture so your AI features can grow with your product.
If you need a practical, user-focused approach to AI in your Bubble app, Keenethics delivers both the brains and the build.
5. havenocode
havenocode is a no-code/low-code agency working across Bubble, FlutterFlow, Webflow, and Xano, with a strong focus on AI-powered functionality.
They integrate AI for tasks like natural language processing, predictive analytics, and process automation, making it easier to launch products that learn and adapt over time.
Their agile sprint process means you can get from idea to working AI product quickly, with room to iterate once you have real user data.
If you’re looking for a multi-platform team that can blend AI into web and mobile apps seamlessly, havenocode is a flexible, future-ready choice.
TL ; DR
Agency | Bubble Partner Tier | Avg Build Time | Starting Budget | Support | Notable Project |
Airdev | Gold | 4–8 weeks | ~$25K+ | Dedicated team, post-launch support | Dividend Finance (100K+ users, billions in loans) |
Zeroqode | Gold | 3–6 weeks (template-based) | ~$5K+ or prebuilt kits from $197 | 24/7 plugin updates, optional retainers | 500+ live Bubble apps, AI chatbot templates |
Goodspeed | Gold | 4–8 weeks | ~$15K+ | Full product team, | Pockla (raised £1.6M, AI content platform) |
havenocode | Silver | MVPs in ~3 weeks | ~$2K+ | Agile sprint process, multi-platform support | TalentHub – automates candidate screening using NLP and ranking. |
Rapid Dev | Gold | MVP in 2–4 weeks (web), mobile 12 weeks | $9,999 – $24,999 | Structured sprint-based delivery with dedicated project managers | ChurchSpace — a venue booking marketplace enhanced with AI-driven availability optimisation |
Case Study: MyAskAI – AI-Powered App (Built on Bubble)
My AskAI, is a conversational AI platform built on Bubble. It uses OpenAI’s GPT models to power custom chatbots over users’ own documents - PDFs, DOCX files or website URLs - providing instant, context-aware answers.
Behind the scenes, Bubble’s visual workflows handle file ingestion, vector indexing, prompt management and response post‑processing, while its database stores user sessions, document metadata and billing records.
Launched by a small, non‑technical team, My AskAI went from concept to live MVP in under six weeks, then scaled to 40,000+ users and $25K MRR without writing a line of backend code.
This demonstrates how Bubble’s integrated hosting, database, and API‑connector ecosystem enables rapid prototyping and production‑grade AI integrations without traditional development resources.
As they began to scale, My AskAI partnered with us to optimize the app performance. Read the full case study here.
Cost & Timeline Benchmarks
Building an AI-powered app with Bubble typically involves integrating AI functionalities like natural language processing, machine learning models, or predictive analytics via APIs (e.g., OpenAI, Google AI).
Costs and timelines vary based on complexity, starting from a basic MVP with simple AI features to scalable enterprise solutions with custom AI integrations.
Key factors influencing cost include the use of premium plugins for AI capabilities, third-party API integrations (which may incur ongoing fees), custom workflows or data handling for AI outputs, and team involvement
For a realistic estimate, consider these benchmarks as starting points; actual figures depend on scope, revisions, and whether you're building in-house or outsourcing.
Simple MVPs focus on core AI features with minimal UI/UX polish, standard builds add user authentication and moderate data processing, and complex ones include advanced scalability, custom AI models, and robust backend logic. Always factor in Bubble's subscription tiers (starting at $32/month as of 2025) and potential API usage costs, which can add approximately 10–20% to the total.
Tier | Description | Timeline Benchmark | Cost Benchmark (USD) |
Simple / MVP | Basic AI integration (e.g., chatbot, basic ML prediction) with limited features and users. | 4–8 weeks | |
Standard / Mid-complexity | AI workflows with dashboards, NLP chatbots, moderate integrations, and basic scalability. | 3–7 months | |
Complex / Scalable Builds | Advanced AI with custom models, high-volume data, enterprise systems, security, and full scalability. | 4–10 months |
Implementation Checklist
1. Scope the Project: Define the core features of your AI-Powered Apps, such as AI integrations (e.g., chatbots or image classification), target users, and success metrics.
Key questions: What problem does the app solve?
Deliverable: Project scope document.
2. Planning: Select AI tools (e.g., OpenAI API or Google Cloud AI) compatible with Bubble, and outline app architecture including data models.
Key questions: What AI capabilities are needed?
Deliverable: High-level plan and tech stack list.
3. Design the User Interface: Create wireframes and UI elements in Bubble's editor, focusing on intuitive AI interactions like input forms and result displays.
Key questions: How will users interact with AI features?
Deliverable: Wireframes and style guide.
4. Set Up Data and APIs: Configure Bubble's database for storing AI-related data (e.g., user inputs, AI-generated responses) and integrate external AI APIs securely using API connectors.
Key questions: What data privacy and compliance requirements (e.g., GDPR) must be met? Deliverable: Database schema and API connections.
5. Build Core Workflows: Develop backend workflows in Bubble to handle API requests to AI services, process responses, and manage errors or fallbacks effectively.
Key questions: How will API failures or latency be handled gracefully?
Deliverable: Functional workflows for key features.
6. Implement Frontend Logic: Add dynamic elements such as repeating groups for displaying AI outputs and conditionally show/hide components based on AI response data. Key questions: Is the UI responsive across devices and accessible for all users?
Deliverable: Interactive prototypes.
7. Test Thoroughly: Conduct unit tests for each module including AI integration endpoints, usability testing with real or sample users, and performance tests under simulated load.
Key questions: What are potential edge cases when the AI misinterprets or fails? Deliverable: Test report with identified issues and corresponding resolutions.
8. Launch and Monitor: Deploy the app on Bubble's hosting infrastructure, implement analytics tools (e.g., Google Analytics or Mixpanel) to monitor AI usage and user behavior, and plan for continuous improvement based on feedback.
Key questions: What KPIs and metrics will be tracked (e.g., AI accuracy, user retention)? Deliverable: Launch plan and real-time monitoring dashboard.
Ready to turn your AI-powered app idea into a validated, launch-ready reality? Book a free strategy call with our team today for customized guidance that helps accelerate your validation process and provides clear launch direction.
Is Bubble secure for AI-Powered Apps?
Yes, Bubble offers several security features applicable to AI-powered apps, such as automatic HTTPS, database privacy rules, and optional two-factor authentication. It also allows compliance with regulations like GDPR through user consent mechanisms and data handling practices.
Can I scale my AI-Powered App built on Bubble?
Yes, Bubble is built on scalable cloud infrastructure and allows dynamic capacity upgrades via its pricing tiers. It supports applications with a substantial user base, although performance tuning may be necessary for high-load use cases. For AI-powered features, you can integrate external services like OpenAI, Google Cloud AI, or AWS AI solutions. Scaling may also involve optimization strategies - such as processing data externally and then returning results to Bubble - to improve performance at scale, especially for enterprise-grade apps.
What happens after my AI-Powered App is launched?
After launch, Bubble developers or agencies often provide ongoing support services, including regular maintenance, feature updates, and performance monitoring. You can iteratively enhance AI functionalities, fix issues based on user feedback, and improve UI/UX. Some agencies offer tiered support packages, while others may operate on retainer or per-update models. This allows your app to adapt over time without requiring a rebuild from scratch.
Will I own the IP of my AI-Powered App developed by a Bubble agency?
Yes, in most cases, you will own the intellectual property of your AI-powered app developed by a Bubble agency, provided that this is explicitly stipulated in the contract. This includes rights to the app's visual design, workflows, and any custom-developed AI-related components. However, ownership does not extend to proprietary third-party services (e.g., the OpenAI API) used in the app. Always review and negotiate contracts to ensure there is no retained ownership or licensing ambiguity from the agency.
How does a Bubble agency integrate AI into apps?
Bubble agencies integrate AI through Bubble's API connector or plugins, enabling access to platforms like OpenAI (e.g., ChatGPT), Google Cloud Vision, or custom AI endpoints. While frameworks like TensorFlow aren't natively run within Bubble, agencies can connect Bubble to external services that run such models and return results to the app. These integrations are typically implemented with low-code workflows, making them user-friendly and efficient for rapid deployment of AI features like chatbots, recommendations, or language processing.
What are the costs involved in building an AI-Powered App with Bubble?
Costs for building an AI-powered app on Bubble can range from around $10,000 for basic apps to over $50,000 for complex, fully-featured platforms. Pricing varies based on app complexity, UI/UX requirements, AI integration effort, and agency expertise. Bubble's subscription plans begin at $32/month (as of 2025), and usage-based charges apply for third-party AI APIs like OpenAI.
How long does it take to build an AI-Powered App on Bubble?
Developing an AI-powered app on Bubble typically takes between 4 to 12 weeks, depending on the scope and AI features involved. Simple prototypes can be built in 1–2 weeks, while more complex applications with custom AI integration and user interfaces may take longer for revisions and testing. Using Bubble's no-code tools accelerates the development process compared to traditional coding, permitting faster iteration and deployment.
