Blockchain Research Platforms

In April 2026, SOL Strategies acquired Darklake Labs for $1.2 million, gaining ownership of Zyga, a zero-knowledge proof system built for Solana. Zyga allows parties to verify trade constraints and collateralization ratios without revealing underlying position data, settling in a single transaction. The system is designed to enable verifiable compliance for institutional DeFi without exposing sensitive trading information. Zyga is positioned as a building block for privacy-preserving financial applications on Solana, particularly in institutional trading and collateralized lending contexts. The acquisition sits alongside SOL Strategies' purchase of Houdini Swap, a privacy-focused cross-chain aggregator, extending the company's portfolio into privacy and verifiability at the protocol level. Together, these acquisitions reflect a broader thesis around trust-minimized infrastructure for institutional participants on Solana.

Corbits is a developer platform at the intersection of autonomous AI agents and blockchain payment infrastructure, built for what its founders call "agentic commerce." Its flagship open-source product, Faremeter, implements the x402 HTTP payment protocol, giving AI agents the ability to pay for API access per-request using stablecoins settled on-chain — with no account setup or credential management required. Solana serves as Corbits' primary settlement layer, accounting for an estimated 50–80% of all x402 transaction volume globally, driven by sub-second finality and fees of roughly $0.00025 per transaction. The platform integrates with Anthropic, Google Gemini, and OpenAI, meaning agents on any major AI provider can plug into Corbits' governance and payment rails without vendor lock-in.

HyperTek's Arete explicitly positions itself as an Agent-first Solana SDK, targeting the growing population of autonomous AI agents that build and operate on Solana. As AI agents take on roles in DeFi including trading, liquidity rebalancing, and protocol management, they need data primitives designed for machine consumption rather than human-readable interfaces. Arete addresses this by letting an agent describe its intent and then generating a minimalist, task-shaped SDK surface that strips out context the agent does not require, eliminating approximately seventy-two percent of the pre-product token expenditure that agents typically burn through during data retrieval, context reconstruction, and transformation. This AI-agent orientation represents a deliberate product evolution from HyperTek's earlier Hyperstack offering, which focused on developer ergonomics for human engineers. The company recognized that autonomous agents are becoming first-class application developers on Solana and that their data layer requirements differ substantially from those of traditional dApps. By providing pre-integrated context for major programs including Raydium, Kamino, and Drift, Arete gives agents immediate access to structured protocol state without requiring them to decode raw account data or reconstruct program logic from scratch, meaningfully reducing the computational overhead that makes agent-based on-chain activity expensive.

Meridian's core innovation was an AI agent that interpreted natural-language investment instructions and translated them into executable Solana transactions. Users could issue commands like "Buy $100 of Bitcoin every Friday" or ask "How is my portfolio doing?" and the agent handled the full execution pipeline, from routing to settlement. The AI layer was designed to surface insights proactively rather than only responding to direct queries. Its knowledge base was specifically trained on the Solana ecosystem, earning early reviewers' praise for the accuracy of its responses. Meridian represented an early production deployment of conversational AI as a primary interface to on-chain financial infrastructure.

Cloak's withdrawal mechanism relies on Groth16 zero-knowledge proofs generated in the user's browser, enabling holders of encrypted pool notes to prove ownership of a valid balance without disclosing which specific note they hold or how much it contains. When a user initiates a withdrawal, this ZK proof is passed to a permissionless miner network that submits and signs the transaction on the user's behalf, ensuring the originating wallet address never appears in the on-chain withdrawal record. The Groth16 proving scheme is verified directly on Solana's native execution environment, enabling settlement without the multi-minute delays common in Ethereum-based ZK privacy protocols. This architecture achieves what Cloak terms unlinkability: an on-chain observer sees only a pool-to-recipient transaction with no ability to associate a deposit address, transferred amount, or timing with any particular withdrawal. Miners additionally generate decoy transactions that are cryptographically indistinguishable from genuine withdrawals, preventing statistical analysis from narrowing the anonymity set when real user volume is low. The combination of in-browser proof generation, on-chain Groth16 verification, and miner-generated decoys represents a layered application of zero-knowledge cryptography to the practical privacy needs of Solana's stablecoin economy.

PlaiPin represents an early production example of on-device AI combined with blockchain-native protocols, embedding both layers directly in consumer hardware rather than routing through cloud intermediaries. Each companion uses local AI processing to learn its owner's habits, recognize frequent contacts, and develop a distinct personality shaped by cumulative interactions, while Solana provides the identity, payment settlement, and agent coordination layer that enables autonomous device-to-device interactions at scale. The PlaiPin Inter-Companion Protocol (PICP) relies on this combination: proximity-triggered authentication and micro-transactions are settled on-chain using decentralized identities, while the intelligence governing when and how companions interact runs entirely on-device. The project's x402 implementation further advances this integration by enabling ESP32-S3 microcontrollers to independently execute signed blockchain transactions, demonstrating a concrete architecture for AI-augmented IoT devices operating as autonomous economic agents.

attn.markets includes a dedicated agent credit product that issues credit lines to AI agents for approved on-chain services and tasks, positioning the protocol within the emerging infrastructure layer for autonomous agent commerce on Solana. The design enables agents to pay for APIs, compute, and other resources based on their prior payment history and revenue from completed jobs, creating a credit system that operates without constant human oversight. This directly addresses a practical constraint in AI agent deployment: autonomous agents operating in open-ended on-chain environments require financial capacity that does not depend on real-time human authorization for each transaction. The protocol's approach to agent credit mirrors its borrower credit model, with demonstrated revenue and payment history serving as the underwriting basis rather than human-assigned creditworthiness. During the current narrow public launch, agent credit lines are restricted to approved spending pathways while the system accumulates repayment data to inform future underwriting. The longer-term architecture documented by attn envisions agents operating with enforceable, verifiable financial autonomy across wallets, marketplaces, and payment cards, placing the protocol at the frontier of practical AI and blockchain integration on Solana.

GainForest builds AI verification infrastructure that bridges on-the-ground conservation fieldwork with Solana smart contract payment rails. Community monitors document field activity through an Android app, generating GPS-tagged photos and species identifications that AI models—trained on satellite deforestation data and cross-referenced against drone imagery—evaluate to confirm milestones before payments are released. Passive bioacoustic listening stations detect and classify forest species by sound while remote sensing pipelines track canopy gain and deforestation risk over time. GainForest publishes its AI and nature models on Hugging Face, including species detection and biodiversity analysis systems powered by the Bacalhau compute network. Tainá, an AI storytelling companion co-designed with Indigenous communities in the Greater Manaus region of Brazil, archives oral histories in local languages. Founded by David Dao, an ETH Zurich AI researcher with affiliations at Stanford, Berkeley, and MIT, GainForest exemplifies AI-blockchain convergence at the frontier of regenerative finance on Solana.

SubQuery's AskSubQuery platform applies AI to blockchain data access, replacing traditional GraphQL query syntax with conversational natural language interaction at asksubquery.xyz. Users describe the blockchain state they want to explore in plain English, and the platform routes requests across multiple data sources—including SubQuery, The Graph, Covalent, and Codex—through a GraphQL Agent MCP layer that abstracts provider-specific query languages. Announced in 2026 as a strategic pivot from SubQuery's decentralized indexer network, AskSubQuery represents a shift toward AI-mediated on-chain intelligence. SQT token holders receive complimentary daily query credits, and locking SQT grants ongoing free access to the platform. Solana data is expected to be accessible through the natural language interface as the transition progresses, extending AI-powered blockchain queries to the Solana ecosystem alongside the existing Soldexer-based indexing integration.

MCPay addresses one of the central open problems in the agentic AI economy: how autonomous software agents can transact economically for API access without human-managed credentials or subscriptions. The project implements the x402 payment standard on top of Anthropic's open-source Model Context Protocol — donated to the Linux Foundation's Agentic AI Foundation in December 2025 — creating a machine-readable payment signaling layer on standard HTTP that any MCP-compatible agent or framework can use. Founded in July 2025 with backing from Colosseum, Coinbase, Polygon, Vlayer, and ETHGlobal, MCPay is among the earliest and most complete implementations of pay-per-call MCP payments. Solana's sub-second finality and near-zero transaction costs make it the primary settlement chain for MCPay's per-request model, demonstrating how high-throughput blockchains can function as economic infrastructure for the emerging agent-to-agent economy. The project's multichain architecture — spanning Solana, Base, Avalanche, Polygon, IoTeX, and Sei — and its non-custodial security model, where client private keys remain entirely client-side and MCPay only receives payment proofs, position it as a reference implementation for autonomous blockchain payments in AI workflows. The Solana Foundation has actively promoted the x402 standard through developer documentation and official guides, aligning with MCPay's approach.

iMe integrates artificial intelligence into both its social and financial layers, developing proprietary AI tools that operate natively within a messaging environment. Neurobots are AI assistants trained on user-defined data sets that can suggest responses, answer questions, or act as personal assistants, and users can publish and sell completed Neurobots on the iMe AI marketplace, creating a user-generated market for specialized AI agents. A general AI assistant built into the app draws on multiple large language models including ChatGPT, Gemini, and Claude, accessible from within chats without geographic restrictions. AI-powered trading agents within iMe Wallet 2.0 apply real-time market analysis to DEX swap and portfolio tools, connecting AI decision support directly to on-chain financial activity. The combination of a user-built AI marketplace, multi-model assistant integration, and AI-driven DeFi tooling illustrates how iMe embeds intelligence across both the communication and blockchain layers of its platform.

NEAR Intents is specifically designed for AI agent execution, allowing autonomous agents to sign and broadcast cross-chain swap intents without managing gas, bridge approvals, or transaction sequencing across multiple chains. The intent model — where an agent expresses a desired outcome rather than an explicit transaction path — maps directly to how AI agents reason about goals, making NEAR Intents one of the few live cross-chain protocols architected with agent-native interaction in mind. NEAR Intents participates in the Open Agents Alliance alongside Coinbase AgentKit and Eliza Labs, positioning it as an execution layer for autonomous agent-driven transactions. The solver network handles all routing complexity, including sourcing liquidity, selecting chains, managing gas on destination networks, and settling cross-chain — freeing AI agents from operational transaction management that would otherwise require extensive custom tooling. As of mid-2026 the protocol has processed over 25 million swaps and $20 billion in cumulative volume, demonstrating that the intent model scales beyond experimental usage. Developer integrations are available through a REST API, React widget, and TypeScript, Go, and Rust SDKs, enabling AI agent frameworks to add cross-chain execution capability without managing custom bridge or liquidity integrations.

PayPerQ targets AI agent infrastructure as a primary use case, enabling autonomous AI systems to pay for data queries, API calls, and external tool access using on-chain micropayments. As AI agents become more capable of executing complex multi-step workflows, they require reliable mechanisms to access paid data sources and services without human intervention at each payment step — a problem PayPerQ is designed to solve on Solana. The platform's approach to AI-blockchain integration is practical: by providing a micropayment infrastructure that AI agents can use programmatically, PayPerQ enables agent-driven applications to access premium data and compute resources on-demand. This positions it within the emerging infrastructure layer for autonomous AI systems operating on public blockchains, where reliable payment for external services is a prerequisite for building capable and economically self-sustaining AI agents.

Unhosted AI is a companion research platform that routes queries through eight specialized analytical agents covering token analysis, wallet forensics, portfolio tracking, DeFi protocol evaluation, NFT analytics, token discovery, trading strategy generation, and social sentiment intelligence. An intelligent routing layer directs each query to the most relevant agent or combination, aggregating live on-chain data from Moralis, Exa, TaaAPI, and YFinance across Solana, Ethereum, Base, Polygon, BSC, and Arbitrum. The AI orchestration layer is built on Python 3.11 and FastAPI, with PostgreSQL and pgvector for storage, and the Agno framework for multi-agent coordination. The system supports multiple LLM backends including OpenAI, Google Gemini, Anthropic Claude, and xAI Grok. Practical features include smart money tracking, automated honeypot and approval risk scanning, real-time cross-chain P&L, KOL intelligence, and custom token screening calibrated to user-defined risk tolerance — all surfaced through a conversational research interface aimed at active traders.

DataHive AI is purpose-built at the convergence of artificial intelligence and blockchain, creating a decentralized marketplace for AI data, model training, and inference workloads. The protocol enables AI developers and enterprises to source high-quality datasets, commission model fine-tuning, and access distributed compute for inference — all coordinated on-chain, with Solana providing the settlement layer for permissionless participation by data contributors and model developers alike. By bringing AI infrastructure on-chain, DataHive AI addresses a core problem in model development: access to diverse, verifiable training data without depending on centralized data brokers. Smart contracts govern the terms of data licensing, contributor rewards, and model deployment rights, creating transparent and auditable workflows for AI development. The platform's approach represents one of the more direct implementations of blockchain as a coordination layer for AI supply chains, where data provenance, compute contributions, and model outputs are tracked and compensated on-chain.

Fuse has extended its payments infrastructure into the emerging AI agent economy, launching a native agent wallet capable of earning yield and supporting programmatic payments for autonomous systems. The network added support for the x402 payment protocol, which allows AI agents to settle payments without requiring bank accounts or third-party payment processors. This positions Fuse as infrastructure for autonomous agent commerce alongside its traditional consumer finance focus. The 2026 strategic direction emphasizes AI agent payments as a primary growth vertical, targeting a market where agents need to transact programmatically across the internet. By combining a gasless, account-abstracted architecture with agent-native wallets and protocol-level payment settlement, Fuse is building toward a model where AI agents can operate as independent economic actors. This direction builds on the same low-cost, high-speed transaction environment that underpins the network's consumer payments applications.

Project Zero's Zero Agent architecture represents a significant design effort at the intersection of AI and blockchain data. The system uses a modular multi-agent design with chain-agnostic ingestion pipelines, a real-time semantic knowledge graph, and a provenance-first prompt infrastructure built on ERC-7208 on-chain data containers. The prompt mining mechanism gives user-created prompts canonical identity, lineage, and micro-royalty capabilities, turning user contributions into composable intellectual assets that can be staked, validated, and earn economic value over time. The agentic design extends beyond data retrieval into autonomous execution. Before taking any action, the system surfaces human-readable transaction diffs and spend caps for user review, uses commit-reveal schemes to minimize mempool exposure, and enforces hard constraints through policy vaults. This preview-first execution model is intended to preserve meaningful human oversight even as agents act autonomously, and is documented in the project's published Zero Agent litepaper.

Automata Network integrates zero-knowledge virtual machines to compress hardware attestation quotes into affordable on-chain proofs. Without ZK compression, verifying a raw TEE attestation report on-chain can cost millions of gas; integrations with RISC Zero, Succinct, and Brevis reduce that cost to practical levels without sacrificing the cryptographic guarantees provided by the underlying hardware. This positions Automata at the intersection of TEE-based and ZK-based verification approaches. The practical result is that rollups and decentralized applications can access hardware-attested computation proofs at scale without prohibitive costs. Scroll and Linea use the Multi-Prover AVS, which combines TEE-based proving with ZK compression, as part of their path toward Stage 2 decentralization. Enhanced multi-prover support with expanded ZK integration shipped in January 2026.

Guru Network, formerly DexGuru, repositioned from a consumer DeFi tool into a multi-chain AI compute layer and orchestration infrastructure provider between 2023 and 2024. The platform's central claim is that blockchain applications need a coordination layer capable of modeling, automating, and executing complex workflows spanning both on-chain smart contracts and off-chain systems. AI processors on the network execute tasks including market analysis, alert generation, portfolio monitoring, and inter-protocol interactions. As of January 2025, Guru Network began deploying personal AI agents in messaging contexts, allowing users to interact in direct messages and group channels for token insights, price notifications, and wallet management. The Guru Framework, open-sourced on GitHub, packages the AI and orchestration infrastructure into a developer toolkit with smart contract templates and integration libraries. The GURU utility token powers the Atomic Franchise Mechanism connecting service consumers to compute providers.

Amadeus Protocol has established a partnership with zkVerify, a zero-knowledge verification layer developed by Horizon Labs, to enable cryptographic proof of AI computation correctness. The planned integration creates a proof settlement bridge between the two networks, allowing AI training and inference workloads to receive zk-proof validation. Phase 1 covers basic uPoW job validation, while Phase 2 scales to comprehensive AI computation verification, with the full rollout spanning Q4 2025 through Q2 2026. The zk-proof integration supports enterprise compliance use cases including provenance attestation, geofencing, and licensing verification. KZG-based proofs also enable cross-chain interoperability with EVM-compatible networks through the same verification layer. For agent operations requiring confidentiality, Amadeus supplements zk-proofs with Trusted Execution Environments, which protect sensitive inputs and intermediate states while still producing verifiable attestations of correct execution.

DappLooker AI is an intelligence API suite built as infrastructure for autonomous AI agents, next-generation DeFi applications, and algorithmic trading systems. It delivers natural language market intelligence, action feeds for autonomous decision-making, and structured outputs sized for agent context windows through Loky AI, which converts live on-chain signals into formats directly consumable by AI inference pipelines. The platform's agent-first design extends to payment infrastructure: x402 integration allows AI agents to autonomously purchase data access without human-in-the-loop authorization. The client list includes AI teams such as Virtuals and Sentient, reflecting growing demand for blockchain data infrastructure tailored to machine rather than human consumers. DappLooker positions this layer as foundational infrastructure for the emerging agent economy.

PublicAI builds decentralized AI data infrastructure at the intersection of blockchain and machine learning. The platform crowdsources the production of high-quality, human-verified training data — including RLHF datasets, text-to-speech recordings across 44+ languages, and aesthetics assessments — across a global contributor network compensated in $PUBLIC tokens tied directly to enterprise client revenue. Its Byzantine Fault Tolerant consensus mechanism applies blockchain-style adversarial resistance to data quality: AI handles bulk filtering while human validators adjudicate edge cases requiring genuine judgment. On Solana specifically, PublicAI deploys smart contracts to record RLHF voting hashes and timestamps immutably, decentralizing what was previously a centralized database of contributor decisions. Daily contributor votes are batched, hashed, and posted on-chain, with administrator signatures verified by contract logic. This design preserves full auditability of the human feedback process without exposing raw response data, making PublicAI one of the more technically concrete applications of blockchain consensus to AI training data validation on Solana. The $PUBLIC token is also deployed natively as an SPL token, with revenue-linked issuance ensuring new supply only enters circulation when enterprise clients pay for datasets.

Strawberry AI is a DeFAI platform — the convergence of decentralized finance and artificial intelligence — that applies large language models and autonomous agents to crypto research and on-chain decision-making. Its infrastructure indexes blockchain activity across Solana, Ethereum, and Layer 2 networks while simultaneously pulling from off-chain sources including news outlets, Twitter/X, and Telegram, routing all of it through a sentiment analysis and narrative-tracking layer that maps relationships between tokens, projects, and community discussions. Berry Chat R3 is the platform's primary research interface, enabling users to query DeFi projects, on-chain activity, market trends, and tokenomics through natural language and receive answers grounded in live data rather than static training cutoffs. The Luigi social intelligence agent extends this by tracking key opinion leaders across crypto social media, scoring sentiment around tokens and narratives, and surfacing trend signals before they reach broader market awareness. Berry Chain adds an infrastructure layer that creates tamper-resistant records of AI agent activity, addressing auditability concerns as autonomous agents begin executing transactions on behalf of users at scale.

Daemon Protocol addresses the emerging challenge of AI agent trust on Solana through two on-chain primitives: Proof of Agency and Agent Bonding. Proof of Agency uses a commit-reveal scheme to verify that an AI agent executed a specific action autonomously rather than through human override, creating an auditable record of agentic behavior. Agent Bonding requires AI agents to post on-chain surety bonds that are slashable for misbehavior, introducing economic accountability for automated systems operating without direct human supervision. These primitives contribute to an Agentic Reserve System — a broader framework for establishing trustworthy AI agent networks on Solana where participants can verify agent identity, track historical performance, and enforce consequences for failures. As AI agents take on larger roles in DeFi execution, oracle reporting, and protocol governance, Daemon's infrastructure provides the verification layer that allows human-designed systems to incorporate autonomous agents with measurable trust guarantees.