Artificial intelligence is advancing at record speed, with global AI spending projected to surpass $375 billion in 2025 as per UBS and CIO. Yet, most systems still operate in black boxes where data origins, model creators, and contributor rewards remain hidden. OpenLedger (OPEN) tackles this challenge by introducing the first AI-native blockchain, built to make data, models, and agents transparent, traceable, and rewardable in real time, ensuring that contributors are credited and the AI economy becomes both explainable and fair.
Backed by $8 million in seed funding from Polychain and Borderless, along with notable angels like Sreeram Kannan of EigenLabs, ex-Coinbase CTO Balaji Srinivasan, and Polygon co-founder Sandeep Nailwal, OpenLedger has quickly built momentum in the AI + blockchain sector.
Discover OpenLedger (OPEN), the first AI-native blockchain that makes data, models, and agents transparent and rewardable. Learn how it works, the utility and tokenomics of the OPEN token, and practical steps to trade it on BingX.
What Is OpenLedger and How Does It Work?
OpenLedger is a blockchain built specifically for AI. Unlike traditional blockchains designed for DeFi or NFTs, OpenLedger focuses on making every step of the AI lifecycle, data contribution, model training, inference, and deployment, transparent and rewardable. Its core innovation is Proof of Attribution (PoA), which tracks how data influences model outputs and distributes rewards accordingly.
From a user’s perspective, OpenLedger is EVM-compatible and built as an OP Stack rollup with AltLayer as its RaaS partner. This means it works with familiar Ethereum tooling, wallets, and bridges. The OPEN token serves as gas on the L2 and powers attribution-based rewards, making the ecosystem seamless for developers and accessible to contributors.
Practically, the platform combines three key tools:
• Datanets: shared, community-owned data networks with verifiable provenance.
• ModelFactory: a no-code dashboard for fine-tuning and testing AI models.
• OpenLoRA: a cost-efficient serving system that can host thousands of models per GPU.
This pipeline makes AI development faster, cheaper, and more transparent while ensuring contributors are credited whenever their work is used.
All About the $OPEN Airdrop
OpenLedger also launched an OPEN token airdrop starting from September 8, 2025, to reward its earliest supporters and testnet participants. Eligible users included those who pre-registered, contributed data or ran nodes during the testnet epochs, as well as active community members from campaigns, Cookie DAO snapshots, and real-world events.
Tokens were distributed during the Token Generation Event (TGE) in September 2025, with the option to claim directly to wallets or stake for boosted rewards. This airdrop marked the first step in decentralizing token ownership and aligning incentives across the OpenLedger ecosystem.
What Makes OpenLedger Different?
Unlike general-purpose blockchains or AI projects that only focus on compute and storage, OpenLedger is AI-first at the protocol level. Its Proof of Attribution (PoA) records every dataset, training step, and model inference on-chain, ensuring contributors are credited and rewarded.
With tools like Datanets for community-owned datasets, ModelFactory for no-code fine-tuning, and OpenLoRA for cost-efficient deployment, OpenLedger transforms data, models, and agents into transparent, monetizable assets, making AI not just on-chain, but explainable, rewardable, and production-ready.
What Is OpenLedger's Proof of Attribution (PoA)?
PoA is the protocol’s core. It maps which data influenced a specific output, then routes rewards accordingly. The June 2025 PoA whitepaper describes two approaches:
1. Influence-function approximations for smaller models
2. Suffix-array-based token attribution for LLMs that checks output tokens against compressed training corpora to detect memorized spans.
That influence score becomes the basis for inference-level payouts.
OpenLedger's PoA feature makes AI more transparent, fair, and trustworthy. With explainability, you can trace a model’s answers back to the data that shaped them; with fairness, contributors are rewarded whenever their input drives results, not just when they upload it; and with compliance, the system provides clear provenance records that help with licensing, auditing, and meeting regulatory standards.
An Overview of the OpenLedger Stack
To understand how OpenLedger works in practice, it helps to look at its core building blocks. The platform combines tools for data sharing, model training, and cost-efficient serving into one unified ecosystem, making AI development more transparent and accessible for everyone.
1. Datanets
Datanets on OpenLedger | Source: OpenLedger
Think of a Datanet as a public, on-chain “data club” for a specific topic, e.g., legal contracts, medical snippets, DeFi exploits. Anyone can contribute. Every contribution is hashed, attributed, and queryable later. During training and inference, PoA can measure each contribution’s influence and allocate rewards.
What makes Datanets useful
• Transparent provenance for audits and licensing
• Incentives for quality data (not just volume)
• A clean source of domain-specific datasets for specialized models
2. ModelFactory
ModelFactory on OpenLedger
ModelFactory is a GUI-only fine-tuning interface (no CLI needed). Choose a base model, e.g., LLaMA/Mistral/DeepSeek, request permissioned datasets from Datanets, configure LoRA/QLoRA, and monitor training from a dashboard. It also ships a chat/eval interface and RAG attribution to see why an answer cites certain sources.
3. OpenLoRA
OpenLoRA focuses on cost-efficient inference: it loads LoRA adapters just-in-time, merges them on the fly, and supports streaming + quantization. In practice, this lets you host thousands of fine-tuned variants behind a shared base model with low latency, instead of spinning up a separate server per model.
Why that matters: if you’re an app with many niche models by client, country, product line, OpenLoRA keeps GPU costs predictable while maintaining speed. This “many adapters per GPU” pattern is consistent with broader LoRA-serving research trends.
How to Try OpenLedger as a Beginner
You don’t need deep technical skills to explore OpenLedger. Here are four simple ways to get started:
1. Explore on Testnet: Register on the testnet, set up your wallet, and try out features without risk. Technical users can run a node (via Docker or similar) to support the network and earn points.
2. Contribute to a Datanet: Pick a Datanet in your area of expertise, such as finance, health, or security. Upload clean, structured data with proper metadata like source and license. Quality contributions may later earn attribution rewards when models use your data.
3. Fine-Tune a Model in ModelFactory: Use the no-code dashboard to select a base model like LLaMA or Mistral, set parameters, and fine-tune with LoRA or QLoRA. Test outputs instantly with the chat module, and enable RAG attribution to make responses source-cited and trustworthy.
4. Serve Your Model with OpenLoRA: Deploy your fine-tuned models efficiently by uploading LoRA adapters. Dynamic adapter loading and token streaming keep latency low, while letting you scale across multiple clients or domains without extra servers.
OPEN Token Utility and Tokenomics
The OPEN token is the backbone of the OpenLedger ecosystem, designed to connect contributors, developers, and users under one economic system. It powers essential functions that keep the network running and ensures participants are fairly rewarded:
• Gas & Fees: OPEN is the native gas token for OpenLedger’s L2. Every transaction, smart contract execution, model deployment, or data contribution requires OPEN, making it the fuel of the ecosystem.
• Governance: Token holders gain voting rights through a modular Governor framework, allowing them to decide on protocol upgrades, incentive programs, and attribution policies that shape how the ecosystem evolves.
• Attribution Rewards: Thanks to Proof of Attribution (PoA), data providers, model builders, and AI agents earn OPEN automatically whenever their work contributes to model training or inference, ensuring ongoing recognition beyond the initial upload.
• Payments & Settlements: OPEN also functions as the medium of exchange across AI applications, decentralized marketplaces, and agent-to-agent transactions, enabling seamless settlement for services built on the platform.
OPEN Token Distribution
OPEN token allocation | Source: OpenLedger docs
The OPEN token (ticker: OPEN) follows the ERC-20 standard with a total supply capped at 1,000,000,000 tokens, with an initial circulating supply of 21.55%.
• Community & Ecosystem Allocation: 61.7%, largest share to contributors, builders, and ecosystem growth
• Investors: 18.3%
• Team: 15%
• Ecosystem Partnerships: 10%
• Liquidity: 5%
How to Trade OPEN on BingX
OPEN/USDT trading pair on the spot market, powered by BingX AI insights
The OPEN/USDT pair is live on BingX, giving traders direct access to the ecosystem’s native token.
1. Create & Verify Your BingX Account: Sign up and complete KYC for full access.
2. Deposit USDT: Add funds via card, bank transfer, or by transferring crypto from another wallet. Move it to your Spot account.
3. Search OPEN/USDT: On the Spot market, enter “OPEN/USDT.”
4. Choose Order Type:
• Market Order → buy instantly at the current price.
• Limit Order → set your price and wait for the market to reach it.
5. Confirm Trade: Enter the amount and click Buy or Sell.
6. Use BingX AI Tools: Summarize market news, set a DCA (dollar cost averaging) plan, or monitor volatility before making moves.
Tip: Watch for BingX’s listing campaigns, early deposit or trading campaigns may include prize pools or bonus rewards.
Conclusion
OpenLedger aims to bring fairness, transparency, and accountability to AI by making data, models, and agents traceable and monetizable on-chain. With Proof of Attribution, contributors can finally be recognized and rewarded whenever their work shapes AI outputs. For users, trading OPEN/USDT on BingX provides direct exposure to the project, while tools like Datanets, ModelFactory, and OpenLoRA make it practical for builders and data providers alike.
That said, OpenLedger is still an emerging ecosystem. As with all crypto projects, risks remain, from smart contract vulnerabilities and token volatility to regulatory uncertainty. If you decide to participate, start small, follow official channels, and only commit what you can afford to lose.