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Deployment & Hosting🔴Developer
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Fleek

Edge-optimized platform for deploying and hosting AI agents with global distribution, serverless functions, and decentralized infrastructure.

Starting atFree
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💡

In Plain English

Deploy AI agents to servers around the world — your agents run close to users for fast, global performance.

OverviewFeaturesPricingGetting StartedUse CasesLimitationsFAQAlternatives

Overview

Fleek is an edge-optimized cloud deployment and hosting platform in the Deployment & Hosting category that offers a free tier with paid plans for scaling, designed for deploying AI agents and web applications with global distribution and minimal latency through serverless edge functions.

For AI agent builders, Fleek provides a deployment target that combines the simplicity of platforms like Vercel with edge-native performance. Agents deployed on Fleek run close to users worldwide through a global edge network spanning over 50 points of presence across North America, Europe, and Asia-Pacific, reducing latency for interactive agent experiences compared to single-region cloud deployments. The platform supports 3 production runtimes — Node.js, Python, and Rust — covering the major AI agent development languages and frameworks.

Fleek's GitHub-based CI/CD pipeline enables automatic deployment on every push, with branch-based preview environments and one-click rollbacks. Each pull request receives a unique preview URL for testing agent changes before merging to production. Custom domains, automatic SSL certificate provisioning, and environment variable management are included across all plans.

A distinguishing feature of Fleek is its decentralized infrastructure integration. The platform offers native support for IPFS and Filecoin, enabling content-addressed, immutable storage for agent data and outputs. This makes Fleek particularly well-suited for Web3-integrated AI agents, DAO automation, and censorship-resistant applications where decentralization is a core product requirement.

Founded in 2018, Fleek brings over 7 years of edge hosting and CDN experience to the AI agent deployment space. The company raised $25 million in a Series A round announced in 2022, demonstrating significant investor confidence in the platform's infrastructure vision. The platform has served over 50,000 sites and applications on its infrastructure, processing millions of build minutes per month across its user base. Fleek has undergone a platform rebuild transitioning to its current edge-native architecture, and some legacy features such as certain IPFS workflows may differ from earlier iterations. Developers evaluating Fleek for production use should review current documentation at fleek.xyz/docs for the latest feature set.

The multi-runtime serverless architecture means teams can combine Python-based LLM logic (using frameworks like LangChain or CrewAI) with Node.js orchestration layers and Rust performance-critical components within a single platform, avoiding the need to manage multiple hosting providers for different parts of an agent stack.

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Key Features

Edge-Native Serverless Functions+

Deploy AI agent endpoints to a global edge network with automatic scaling and minimal cold starts. Functions run close to end users worldwide, reducing latency for interactive agent experiences compared to single-region cloud deployments. Supports Node.js, Python, and Rust runtimes covering the major AI agent development languages.

Decentralized Infrastructure Integration+

Native integration with IPFS and Filecoin enables content-addressed, immutable storage for agent data, model artifacts, and outputs. This positions Fleek uniquely among the deployment platforms in our directory for builders creating censorship-resistant agents, DAO automation, or Web3-integrated AI applications. Combines traditional cloud convenience with Web3 primitives.

GitHub-Based CI/CD+

Automatic deployment on every push to GitHub with branch-based preview environments, build logs, and one-click rollbacks. Each pull request gets a unique preview URL for testing agent changes before merging. The workflow mirrors Vercel and Netlify patterns, making it familiar to most modern developers.

Multi-Runtime Support+

Unlike platforms locked to JavaScript/TypeScript, Fleek supports Node.js, Python, and Rust as first-class runtimes. This enables AI agent stacks that mix LangChain or AutoGen Python logic with Node.js orchestration and Rust performance-critical components. Standard package managers (npm, pip, cargo) work natively.

Managed Domains and SSL+

Custom domains, automatic SSL certificate provisioning and renewal, and HTTPS enforcement are included on all plans. Configuration is handled through the dashboard or API, eliminating manual certificate management for production agent deployments.

Pricing Plans

Free

Free

  • ✓Up to 3 edge serverless function deployments
  • ✓GitHub CI/CD integration with preview environments
  • ✓Custom domain with automatic SSL
  • ✓Community support
  • ✓250 build minutes per month and 100 GB bandwidth included
  • ✓Edge function execution limit of 10 seconds per invocation
  • ✓Up to 1 GB storage for deployments

Pro

$20/month (usage-based)

  • ✓Unlimited deployments with increased build minutes (1,000+ per month)
  • ✓Extended edge function execution limits up to 30 seconds
  • ✓Priority support with faster response times
  • ✓Advanced analytics and monitoring dashboards
  • ✓Team collaboration features with role-based access
  • ✓Up to 1 TB bandwidth per month
  • ✓Custom build configurations and extended storage

Enterprise

Custom pricing from $500/month

  • ✓Custom edge function limits tailored to workload with 60+ second execution windows
  • ✓Dedicated support engineer and guaranteed SLAs with 99.9%+ uptime commitments
  • ✓Advanced security and access controls including SSO
  • ✓Custom integrations and onboarding assistance
  • ✓Volume-based pricing for high-traffic deployments
  • ✓Unlimited build minutes and bandwidth
  • ✓Priority build queue and dedicated infrastructure options
See Full Pricing →Free vs Paid →Is it worth it? →

Ready to get started with Fleek?

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Getting Started with Fleek

  1. 1Create a Fleek account at fleek.xyz and connect your GitHub repository containing your AI agent code
  2. 2Configure your build settings and select runtime (Node.js, Python, or Rust) appropriate for your agent framework
  3. 3Set up environment variables for API keys, model endpoints, and other agent configuration requirements
  4. 4Deploy your agent with one click and test the global edge endpoints to verify optimal performance
  5. 5Configure custom domains and SSL certificates for production deployment of your AI agent endpoints
  6. 6Set up monitoring and analytics to track agent performance and usage across global edge locations
Ready to start? Try Fleek →

Best Use Cases

🎯

Global AI agent API deployment for applications requiring low-latency responses worldwide through edge distribution across multiple regions

⚡

Web3-integrated AI agents that need decentralized storage on IPFS/Filecoin or operation independent of traditional cloud providers

🔧

Edge-native conversational AI and chatbot endpoints where response latency directly impacts user experience and engagement metrics

🚀

Rapid agent prototyping with GitHub-based CI/CD for solo developers and small teams that want preview environments and instant rollbacks

💡

Multi-runtime agent stacks combining Node.js orchestration with Python LLM logic and Rust performance-critical components in a single platform

🔄

Censorship-resistant or trustless AI applications for crypto-native projects, DAO automation, or autonomous agent networks

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Fleek doesn't handle well:

  • ⚠Edge function execution time limits restrict complex AI agent processing such as long-running inference, fine-tuning, or multi-step reasoning chains
  • ⚠Less mature ecosystem than established cloud platforms with fewer enterprise features, compliance certifications, and managed database integrations
  • ⚠Decentralized features add architectural complexity and learning curve not needed for most standard AI agent deployments
  • ⚠Smaller community and support resources compared to mainstream platforms like Vercel, AWS, or Railway, meaning fewer Stack Overflow answers and tutorials
  • ⚠Platform has transitioned through a rebuild to its current architecture, so some older community resources or tutorials may reference deprecated features

Pros & Cons

✓ Pros

  • ✓Global edge deployment reduces latency for AI agent APIs compared to single-region cloud hosting by distributing workloads across 50+ edge locations worldwide
  • ✓Multi-runtime support across Node.js, Python, and Rust covers all major AI agent frameworks including LangChain, AutoGen, and ElizaOS
  • ✓Free tier available for development and prototyping without a credit card requirement, including 250 build minutes/month and 100 GB bandwidth
  • ✓Unique decentralized infrastructure with IPFS and Filecoin integration — one of the few platforms in our 870+ tool directory offering Web3-native hosting
  • ✓Founded in 2018 with 7+ years of edge hosting experience and $25M in Series A funding (2022), providing maturity in CDN and global distribution that newer platforms lack
  • ✓Simple GitHub-based CI/CD with automatic preview environments, custom domains, and SSL provisioning included on all plans

✗ Cons

  • ✗Less established ecosystem than Vercel or Railway for production workloads, with fewer enterprise features and SOC 2/HIPAA certifications
  • ✗Edge function execution time limits restrict complex AI agent processing such as long-running inference or multi-step reasoning chains
  • ✗Decentralized features add complexity and learning curve for developers coming from traditional cloud backgrounds
  • ✗Smaller community and fewer third-party integrations compared to mainstream cloud platforms like AWS, Vercel, or Google Cloud
  • ✗Platform has undergone a significant rebuild to its current edge-native architecture, so some legacy documentation or tutorials may reference deprecated workflows

Frequently Asked Questions

How does Fleek compare to Vercel for AI agent hosting?+

Both Fleek and Vercel offer edge deployment with global CDN distribution, but they differ significantly in scope and runtime support. Fleek adds decentralized infrastructure options (IPFS, Filecoin) and broader runtime support including Python and Rust, making it more suitable for diverse AI agent architectures. Vercel is more mature for Next.js and React applications with a larger ecosystem, while Fleek better supports Web3-integrated agents and Python-based frameworks like LangChain. For pure web app deployment, Vercel typically wins; for AI agents needing decentralized infrastructure or multi-runtime support, Fleek has the edge.

Can I run Python AI agents on Fleek?+

Fleek supports Python runtime for serverless functions, allowing deployment of Python-based agent frameworks like LangChain, AutoGen, CrewAI, or custom Python AI applications. The platform handles dependency installation through standard requirements.txt files, and you can deploy directly from GitHub repositories. Note that execution time and memory limits apply, so for long-running training or large model inference, you may need to pair Fleek with a dedicated compute platform like Modal or Replicate.

What are Fleek's decentralized features and when should I use them?+

Fleek can store agent data and assets on IPFS (InterPlanetary File System) and Filecoin, providing immutable, content-addressed storage that's not controlled by any single entity. This is useful for censorship-resistant agents, blockchain-integrated AI applications, or scenarios where you need cryptographic proof that agent outputs haven't been tampered with. Most traditional AI agent use cases don't require these features — they're most valuable for crypto-native projects, autonomous agents in DAOs, or applications where decentralization is a core product requirement.

Does Fleek support WebSocket and streaming for AI agent responses?+

WebSocket support depends on the specific runtime and plan tier you're using on Fleek. For streaming AI responses (such as token-by-token LLM output), the platform's edge functions support standard HTTP streaming and Server-Sent Events, which work well for most chat and assistant interfaces. Persistent WebSocket connections may require Pro tier plans or specific configuration. Check Fleek's documentation at fleek.xyz/docs for the latest WebSocket capabilities.

What are the function execution limits for AI agent workloads?+

Fleek's serverless functions have execution time, memory, and request size constraints that vary by plan tier — Free tier functions allow 10-second execution windows, Pro tier extends to 30 seconds, and Enterprise plans offer custom limits of 60+ seconds. For most AI agent workloads (a single LLM API call with response processing), these limits are sufficient. However, agents requiring multi-step reasoning, large context processing, or model fine-tuning will hit limits and need a hybrid architecture pairing Fleek edge endpoints with longer-running compute on platforms like Modal or AWS Lambda.
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Quick Info

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Website

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