NEAR Co-Founder Presents AI Pets, Private Trading, and Cross-Chain Payment Solutions

Illia Polosukhin, co-founder of NEAR, has presented 13 innovative application concepts involving AI pets, private trading systems, and cross-chain payment solutions, along with five strategies to assist developers in reaching their audience.

In a post on X dated October 3, Illia Polosukhin noted that both new and returning developers had been active on NEAR over the last few weeks, making development more accessible.

With reduced barriers to creation, he emphasized that developers should focus on product selection and distribution strategies.

“Building itself got easier too, so it’s really about what to build and how to stand out to get distribution.”

NEAR payment concepts link checkout and event deposits

Polosukhin proposed a universal checkout widget for merchants and app developers, enabling customers to pay using NEAR Intents through their already established wallets and blockchain assets.

He suggested that developers could provide this button directly to merchants, aiming for integration with Shopify, which he identified as a potential target for distribution.

For event organizers, he outlined a registration system that would keep attendees’ deposits in escrow until check-in, allowing participants to share the contributions afterward.

Building on a previous initiative called Kickback, he proposed expanding this model across various blockchains and assets to enhance the reliability of crypto event registrations.

Wallet compatibility was a significant aspect of his distribution strategy. He advised utilizing Aurora’s Intent Connect to enable users to access applications from other chains without needing to bridge or learn how to use NEAR.

A recent integration provided context for this suggestion. On September 17, Aurora Labs launched one-signature Sui execution, facilitating the access of supported assets from various networks into Sui applications through its Intents Connect product. Users can perform supported actions without needing to switch wallets, bridge funds, or acquire SUI for transaction fees, according to the company.

Aurora Labs noted that NEAR Intents provided the necessary liquidity, settlement infrastructure, and cross-chain connections, while applications could utilize this integration for lending, trading, staking, and yield generation.

AI pets would possess NFTs and computational balances

Polosukhin envisioned a consumer application featuring “AI Tamagochi,” encompassing digital characters represented by non-fungible tokens.

In his concept, each character would hold a NEAR balance to support AI reasoning, with NEAR AI executing verifiable inference based on prompts encoded on-chain. He proposed features like feeding and dressing for the characters, along with potential battle arenas and competitions.

This payment model already has supporting infrastructure. As reported by crypto.news on July 31, NEAR launched staking-based AI payments that convert locked tokens into monthly computing credits, covering 43 AI models at inception, including those from OpenAI, Anthropic, and Google.

Users retain ownership of their staked tokens and can recover them post-unstaking, while the locked balance determines the available computing credits.

For another informational product, Polosukhin proposed an AI encyclopedia where facts could evolve into ongoing prediction markets, drawing inspiration from the Augur model. Rather than community edits, his idea suggests that AI would generate content based on current market evaluations of each fact.

Additionally, he proposed a benchmarking initiative to test AI models against private datasets without revealing the underlying information. His plan included certified results tied to specific models and the identifying hash of the test set, with developers submitting either a testing framework or a privately hosted model.

Private trading proposals address counterparties and position management

In the realm of over-the-counter trading, Polosukhin highlighted the challenge of finding a counterparty within NEAR Intents’ current “private deals” feature.

He suggested creating a marketplace allowing participants to announce available deals, enabling others to fill them via NEAR Intents.

For social trading, he proposed selling viewing keys to grant select customers access to private transactions. In his proposal, traders could publicly display their profit and loss while restricting access to the activities they want their followers to copy.

Under the term “Never get liquidated,” he also recommended utilizing NEAR Intents to oversee lending and perpetual futures positions, aiming for interest income and managed liquidation risk, presenting this as an application idea rather than a guaranteed solution.

A separate strategy aimed to pair spot holdings with perpetual futures positions under a NEAR contract, managing transactions through Intents. Polosukhin described this concept as “Delta neutral anything.”

On September 29, Bitwise announced its U.S. NEAR ETF launch on NYSE Arca under ticker NRR, with a management fee of 0.75%. According to the asset manager, the fund holds NEAR directly and plans to stake its holdings, with rewards accumulating in line with net asset value.

In discussing Bitwise’s investment rationale, chief investment officer Matt Hougan highlighted NEAR Intents as a settlement infrastructure example for AI agents managing tasks such as payments and swaps.

Private AI tools for code, health data, and recordings

For software teams, Polosukhin suggested an agent capable of privately reviewing pull requests via NEAR AI, ensuring verifiable execution.

In healthcare, he proposed a front-end application that encrypts medical data end-to-end before sending it to NEAR AI for a secondary opinion. This proposal combines crypto and fiat payments with custom prompts stored in NFTs, allowing users to select different areas of expert knowledge.

For desktop users, he outlined a private transcription application inspired by Granola, where NEAR AI would handle transcription while retaining user records locally, with backups encrypted using personal keys.

In place of subscription payments, he suggested funding the transcription service through NEAR staking.

For companies seeking capital, he included a capitalization table tool with related fundraising options, support for crypto payments, and banking assistance.

On the distribution front, Polosukhin encouraged developers to collaborate with NEARLegion, engage other communities through cross-promotion, and utilize Product Hunt, similar discovery platforms, and X for product visibility.