Lilypad x Akave

Alison HaireAlison Haire
3 min read

Lilypad and Akave are thrilled to announce a formal strategic partnership that brings together two foundational primitives of the decentralized AI stack: compute and storage. This collaboration is a bold step toward building a truly modular, community-owned AI infrastructure that rivals centralized platforms.

As Lilypad continues to evolve into the nexus of a decentralized AI cooperative, this alliance with Akave strengthens our ability to support verifiable workflows, secure model outputs, data provenance, and composable AI pipelines.

2. Meet Our Partner: Akave

Akave is a Filecoin Layer 2 decentralized data management network that enables secure, programmable data storage, access, and monetization. Designed to empower the next generation of data-driven applications and marketplaces, Akave delivers cost-effective and performant decentralized storage for AI, Web3, and DePIN ecosystems.

Akave’s architecture supports both public and permissioned data buckets, policy-enforced access, and full data provenance—making it the perfect partner for AI systems that require secure storage and traceable lineage.

3. Shared Vision: Infrastructure for Open AI

Akave and Lilypad are aligned by a clear and ambitious goal: building infrastructure for decentralized intelligence.

  • Decentralization-first: Both platforms reduce dependency on opaque, centralized cloud providers

  • Composable AI primitives: Compute and storage as modular services

  • Data provenance and monetization: Transparent value flows and auditability baked into system design

  • AI accessibility: Empower developers and creators with verifiable infrastructure at every layer

This partnership is more than integration—it’s the emergence of a decentralized foundation for building, training, and deploying AI applications.

4. Synergistic Strengths

What Lilypad Brings:

  • Serverless decentralized GPU compute

  • On-demand model hosting, inference APIs, and agent workflows

  • Verifiable job execution and API-first architecture

What Akave Brings:

  • Decentralized object storage with programmable data buckets

  • Full support for on-chain provenance and usage policies

  • Optimized infrastructure for large LLM and ML workloads

🔧 Short-Term Use Cases

  • RAG Integration Pilot: Showcase a reference architecture for retrieval-augmented generation using Akave-stored data and Lilypad inference

  • Model Caching: Use Akave to store fine-tuned models and intermediate outputs

  • Job Output Storage: Enable users to preserve inference results and synthetic datasets with cryptographic traceability

🚀 Mid-Term Roadmap

  • Plugin-like Integration: Build native ingestion and retrieval pipelines between Akave and Lilypad

  • Co-hosted Agent Workflows: Empower developers to deploy agents that retrieve, compute, and store data using both networks

  • Synthetic Data Provenance: Enable tracking and monetization of AI-generated data across the full pipeline

  • Reputation Transparency: Store Lilypad job provider statistics and performance metadata using Akave’s provenance infrastructure

5. Strategic Impact

This collaboration delivers:

  • A fully modular decentralized AI stack

  • Real value for users: fast, flexible, censorship-resistant compute and storage

  • Clear provenance for models and data outputs, a critical need for commercial and regulated AI

  • Blueprints for the ecosystem: example architectures that others can replicate and build on

Together, Lilypad and Akave move the ecosystem beyond theory to execution, showing what a real decentralized AI infrastructure can look like.

6. Long-Term Ecosystem Vision

This is only the beginning. The long-term vision is a global, modular, permissionless infrastructure layer for AI:

  • Lilypad powers verifiable computation and AI agent execution

  • Akave anchors decentralized storage and data integrity

  • Together, they offer an open foundation to train, fine-tune, and deploy models with full transparency and composability

With upcoming POCs such as Waterlily 2.0 (artist attribution via model fine-tuning) and data-to-agent reference architectures, the potential for future impact is vast.

7. Looking Ahead

This announcement is only the first beat of a new rhythm. The decentralized AI stack is forming.

  • 🌐 Signup for Akave testnet: https://akave.ai/testnet

  • 🧠Join Lilypad ecosystem to deploy, run, and monetize models: https://docs.lilypad.tech

Let’s build decentralized intelligence infrastructure - together.

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Written by

Alison Haire
Alison Haire

Let's talk about the real things. Founder @ Lilypad Compute Network prev-@Protocol Labs | @Filecoin | @Lilypad_Tech PM | Advisor @GodwokenRises | prev-@IBM TechJam Podcast Co-Host | coder, engineer, dog lover 🐕, global citizen 🌏, entrepreneur 👩‍💻, aspiring francophone 🥐