# Overview ### **What is Molecule?** Molecule is the infrastructure for tokenizing, funding, and accelerating scientific research onchain via autonomous, agent-driven science. It provides three interlocking primitives: * A **modular Onchain Lab** that acts as a sovereign, programmable container for research projects; * A **data layer** that captures every artifact generated during R\&D and exposes it through APIs; and * An **AI agent layer** where autonomous research agents operate within Labs to analyze data, generate hypotheses, and publish findings with full onchain provenance. These primitives form a closed loop. A researcher creates a Lab, uploads data, and authorizes an agent. The agent queries literature, analyzes datasets, generates hypotheses, and records outputs back into the Lab. Findings accumulate. IP is minted, fractionalized, and funded. Research compounds whether the researcher is actively working or not. ### **Core problem** Scientific research runs on broken, outdated rails. Funding is slow, opaque, and gated by institutions. Intellectual property remains illiquid for years - locked in legal structures that prevent it from being valued, traded, or built upon. Early-stage science is inaccessible to most investors, and researchers struggle to raise capital. Data and results are fragmented across siloed institutional systems with no programmatic access, experimental outputs are routinely lost, and valuable scientific output compounds inefficiently - if at all. AI agents capable of autonomous experimentation - has no native infrastructure to operate on. There is no programmable research entity that an agent can read from, write to, fund, and be held accountable within. ### Solution Molecule is building the onchain infrastructure addressing the above core problems via on-chain labs. Each Lab acts as a sovereign container with a persistent identity, where research outputs are recorded, IP is minted and fractionalized, and funding is raised transparently. This turns scientific research from illiquid institutional output into liquid, investable, and verifiable onchain assets with a continuous track record. Researchers can fund work directly, investors can access early-stage science, and ownership is shared through transparent, programmable structures. At its core, Molecule provides primitives to: * **Create an Onchain Lab** that unifies all research assets under one identity * **Store research data** with encryption and granular access control * **Tokenize intellectual property** - mint IP as NFTs and fractionalize ownership via tokens * **Raise capital** through transparent, community-driven funding * **Deploy AI agents** that operate autonomously within Labs ### **The Three Pillars** #### *(i) Modular Onchain Lab* A sovereign smart contract wallet bound to an NFT. It holds assets, executes transactions, stores data references, and interacts with protocols - all under a persistent onchain identity. Its modular architecture (ERC-7579) allows new capabilities to be installed over time: licensing, governance, oracles, tokenization, and AI agent execution. Modules are gated by an attestation registry. The Lab is also a platform for tokenizing any research asset - IP can be minted as NFTs, fractionalized into tokens, and made available for trading and community ownership. Transfer the LabNFT and you transfer the entire project - treasury, data, IP, and history - in a single transaction. #### *(ii) Data Infrastructure & API Access* Every action within a Lab generates data. Datasets are stored on decentralized infrastructure (IPFS, Arweave) with provenance tracking and encryption. Access is configurable per-file: token-gated, credential-gated, payment-gated, or time-locked. The DeSci API provides programmatic read and write access to Lab data rooms, transforming each Lab from a static wallet into a live data endpoint that agents and integrations can operate on continuously. #### *(iii) AI Agents for Autonomous Science* Molecule is integrating BioAgents — an open-source AI scientist framework by bio.xyz achieving state-of-the-art results on the BixBench scientific reasoning benchmark. BioAgents runs specialized agents for planning, literature search, data analysis, hypothesis generation, and reflection. It will operate as an executor module on Lab accounts: the Lab's treasury funds compute, the data room provides datasets, and all outputs are written back as versioned data references. Labs support two modes — Fully Autonomous (agents run independently within safety boundaries) and Human-Directed (agents assist while researchers retain strategic control). ### **Who Uses It?** Researchers create Labs, upload data, register IP, and raise funding — with or without AI assistance. AI agents operate within Labs as authorized modules, reading data, running analyses, and recording findings. Investors discover projects through onchain track records and fund research through IP Token crowdsales. Developers build and register modules that extend Lab capabilities. ### **What Makes It Different?** Traditional science cannot fractionalize IP, let communities fund research directly, or give AI agents a programmable entity to operate within. Molecule can. IP-NFTs make intellectual property liquid and tradable—turning years of locked, illiquid output into assets with price discovery and secondary markets. IP Tokens let anyone own a stake through crowdsales. Smart contracts automate royalties, licensing, and treasury management without intermediaries. The Onchain Lab ties it all together—a persistent, transferable research identity where data flows in, agents operate, findings accumulate, capital gets deployed, and IP gets tokenized, all verifiable onchain. Molecule enables community stewardship of tokenized intellectual property, replacing broken, illiquid research rails with a global, programmable system for funding and advancing science. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.molecule.xyz/introduction/readme.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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