AI Rig Complex ($ARC) Investment Research Report
Introduction to AI Rig Complex ($ARC)
AI Rig Complex is a cutting-edge, open-source framework for building AI applications. The framework is written in Rust, a programming language known for leveraging its performance and safety. It has several modular modules, each having a different purpose, functionality and integration within the framework.
Developers able to build and manage powerful and lightweight AI agents powering ARC framework. These agents combine LLM (Large Language Model) capabilities with secure blockchain operations such as executing complex on-chain interactions. This makes the framework ideal for applications ranging from DeFi (Decentralized Finance) to gaming and beyond. Currently, the framework operates on Solana and EVM ecosystems.
The native cryptocurrency of the AI Rig Complex is the $ARC token. $ARC has multiple purposes within the ecosystem, from rewarding contributors to enabling access to advanced features and tools. For instance, contributions such as improving AI models, submitting research, or building new features are recognized and compensated through a prize pool mechanism. This encourages continuous innovation and collaboration within the ARC ecosystem.
The AI Rig Complex was created by Playgrounds, a company co-founded by experts in AI and blockchain infrastructure. Jephthah (Tachi) plays a key role in shaping the technical architecture of AI frameworks, ensuring a strong foundation for ARC. Thierry, another co-founder, serves as the Chief Product Officer (CPO) of Playgrounds and is also a member of the Technical Advisory Board at Graph Protocol, bringing strategic expertise to the project. Christophe, the Chief Technology Officer (CTO) and co-founder, focuses on the software architecture of the ARC framework, ensuring its efficiency and scalability. Together, they are building AI Rig Complex as an innovative system that integrates AI and blockchain technologies.
AI Rig Complex forefronting its modular, scalable, efficient architecture to build next-generation AI applications while powering cutting-edge LLMs. Being Rust-based sets it apart from other AI Agent frameworks and contributes to its prominence. This feature makes it easier for AI Rig Complex to establish itself within the growing Solana ecosystem, enabling existing Solana developers to build AI-powered applications seamlessly.
Architecture Behind AI Rig Complex
Rig Framework
The core of the AI Rig Complex. The framework provides a foundational rust-based system for building and managing lightweight, powerful and efficient AI agents. It contains core libraries, multi-agent support and on-chain integrations.
Rig framework supports several model providers, such as OpenAI, Gemini, Deepseek, Perplexity, Anthropic and Ollama. Developers are able to use various vector stores, including MongoDB, LanceDB, Neo4j, Qdrant, SQLite. Also, third-party plugins like X integrations in the roadmap.
The framework provides high performance and low-latency execution of AI processes. Modular AI task execution allows agents to run specialized models tailored to different applications.
Rig’s on-chain kit fills the gap between AI and blockchain, enabling secure and trustless interactions with smart contracts and on-chain data. With on-chain kit, AI agents can sign and execute blockchain interactions, read real-time on-chain data, do security monitoring, make DeFi strategies, and governance participation without requiring centralized control.
ARC Complex
AI Rig Complex runs two distinct programs — Handshake and Arc Forge — designed to connect developers with the platform and streamline the development of AI Agents.
The handshake program is an open call to developers who want to build on top of the rig framework. ARC is looking for innovative projects, not just another chatbot. Developers building unique projects can propose their projects to ARC and get a chance to be listed on the ARC registry page. To prevent spam attacks, ARC charges 500 $ARC to everyone who applied. Here is the some ideas ARC looking for:
- swarm intelligence systems
- creative data pipelines
- agents that do things on-chain
- report/insight generators
- pattern recognition at scale
- knowledge crawlers
On the other hand, ARC Forge, a streamlined token launch platform built atop Meteora’s dynamic liquidity market maker (DLMM) and integrated with Jupiter routing. The selected handshake projects are able to deploy and manage tokens for their AI agents while enjoying benefits of ARC Forge. Forge provides multiple advantages:
- Deep & Efficient Liquidity: ARC Forge leverages Meteora’s DLMM model, which structures liquidity into targeted price bins. It increases capital efficiency, allowing deep liquidity while minimizing price impact and slippage.
- ARC-centric Routing: Every trade with ARC Forge is routed through $ARC, ensuring continuous trading volume and capturing fees within the ecosystem. This fee-driven model reduces $ARC’s circulating supply over time, directly benefiting token holders by creating a deflationary effect.
- Sniper Prevention: Thanks to Meteora’s configurable bonding curve, mitigates exploitative first-block sniper activity by imposing steeper price impacts on early trades. After this initial phase, project teams can actively reposition liquidity to promote sustainable price discovery and long-term trading stability.
- Expanded Reach: Tokens launched through ARC Forge are recognized by Jupiter’s routing system, making them tradable via popular trading bots such as Bonkbot, Trojan, Photon, and BullX. This ensures that the tokens gain broader exposure to a wider audience.
- Launch Partners: ARC helps promote high-quality and vetted projects launched through ARC Forge.
With these advantages, ARC Forge establishes itself as a next-generation launch and liquidity platform, seamlessly integrating with the ARC ecosystem while prioritizing efficiency, security, and long-term growth.
Competitive Analysis
Competitive analysis is crucial when we need to understand weaknesses and strengths of a project. Instead of a single competitive analysis, we opted for two distinct approaches. This approach allows ARC to be evaluated from two essential perspectives: framework capabilities and AI economics.
Based on Framework
In this section we chose three different projects for competitive analysis of AI Rig Complex, based on framework approach. These projects are ElizaOS, ZerePy and Anda. To provide a clearer comparison, we examine key differentiators such as blockchain compatibility, programming language, plugin ecosystem, and scalability.
ElizaOS
ElizaOS is a lightweight, open-source AI agent development framework that enables the creation, deployment and management of autonomous AI agents. Founded by Shaw, one of the co-founders of ai16zdao.
The key difference of ElizaOS from ARC, is that it is written in Typescript. ElizaOS used its first mover advantage and gained a lot of attention. This attention also reflects metrics, used by the widely-distributed Typescript developer community and ElizaOS has gained more than 14000 stars on GitHub. Currently, ElizaOS accounts for about %60 of the current web3 AI agent development market.
ElizaOS has wide-range plugin support more than 80, including client, blockchain and other plugins. ARC’s plugin support is quite poor compared to ElizaOS, this is an important disadvantage. ElizaOS is supporting most chains, Solana, EVM-based, Aptos, Sui and altVMs like Starknet and Fuel. Also, ElizaOS is supporting PostgreSQL, redis, supabase, SQLite.
ElizaOS stands with various supported AI models and wide plugin support. It’s leading AI agent development market, thanks to a large developer community, unique features and capabilities.
ZerePy
ZerePy is an open-source, Python-based AI agent development framework which has blockchain and social media integrations. It is developed by Blorm Network, top of Zerebro backend.
The main advantage of ZerePy is that it is a Python-based framework which means existing Python developers are able to develop AI agents easily. According to Statista’s report, Python is the third programming language used by developers across the world. There are more than ten million Python developers. It’s an advantage for ZerePy to onboarding new AI agent developers. Currently, ZerePy has more than 550 stars on GitHub. Note that ZerePy is a new framework compared to ElizaOS and ARC.
ZerePy supports 10 AI models such as OpenAI, Ollama, GROQ, and Anthropic. ZerePy has more plugin support than ARC but not as much as ElizaOS. It has X, Farcaster, Echochambers, and Discord social media plugins and is supporting Solana and EVM-based chains such as Sonic, Base, Polygon, and Ethereum. There is no info about supported databases.
ZerePy is promising with its advantage to onboarding new developers to the AI agent development process. It needs more contributions to its framework in order to provide a more steady and stable system.
Anda
Anda is an open-source, Rust-based AI agent development framework, built by ICPanda DAO.
Anda targets Rust developers due to its Rust-based infrastructure, making it the AI agent development framework that aligns most closely with ARC. Initially developed for the ICP blockchain, its Rust foundation also makes it well-suited for Solana. It has been stated that Anda will support other blockchains as well. Currently, Anda has over 240 stars on GitHub.
The AI models supported by Anda are not explicitly listed, but it appears to support OpenAI, DeepSeek, xAI, and Grok. There is no available information on the databases it supports, and its plugin ecosystem remains unclear. One distinguishing feature of Anda is its support for TEE (Trusted Execution Environment), which is a capability only shared with ElizaOS among the frameworks compared.
With its Rust-based design, Anda can be considered a direct competitor to ARC. However, it is still a relatively new framework, which stands out. ARC’s longer development history gives it an advantage in terms of maturity and stability.
Based on AI Economics
Olas
Olas Network is a decentralized protocol designed to support and scale AI-powered autonomous agents in Web3. It provides an infrastructure that enables the creation, management, and coordination of AI agents, allowing them to interact seamlessly with decentralized applications (dApps), smart contracts, and other on-chain services. By leveraging blockchain technology, Olas ensures that AI agents operate in a trustless and permissionless environment, removing reliance on centralized systems and enabling open participation.
One of the key innovations of Olas Network is its tokenized incentive model, which allows AI agents and their developers to be fairly compensated for their contributions. Through a unique reward system, Olas fosters the growth of decentralized AI economies, where agents can perform tasks such as data analysis, governance assistance, market-making, and security monitoring. Additionally, the protocol integrates advanced mechanisms for agent collaboration, ensuring that multiple AI agents can work together efficiently while maintaining transparency and accountability.
Both Olas and ARC are designed to support AI agents, enabling autonomous AI-driven applications in blockchain without reliance on centralized control. Both are open-source projects, encouraging collaboration and innovation through community contributions. Another similarity is the token incentive mechanism. ARC uses $ARC tokens to reward open-source contributions and maintain liquidity in its ecosystem, while Olas has a tokenized economy that supports AI agents through value-sharing mechanisms.
ARC primarily is a framework which focuses on creation and deployment of AI agents while Olas is a protocol which focuses on coordinating AI agents across multiple decentralized ecosystems. Olas focuses more on the economic model of AI agents rather than their direct execution. While ARC is integrated with Solana and EVM chains, Olas is chain-agnostic, meaning it supports agent coordination across multiple chains.
Fetch.ai
Fetch.ai is a decentralized artificial intelligence network which enables the development of an AI empowered decentralized digital economy. The project is not just focusing on AI agents on blockchain, it is welcoming agents working in different industries such as supply chain logistics, solid record-keeping systems, and finance.
Agents registered with Almanac, Fetch.ai network, are able to discover and recognize other agents. In there, the Fetch.ai network offers a layer of truth and trust by inherently being open. Also, Fetch.ai introduces a self-sustaining AI agent economy, where autonomous economic agents interact, trade, and optimize resources without human intervention. The native token of Fetch.ai, $FET, fuels the AI agent economy by serving as transaction currency, asset for incentivize, and staking&governance catalyzer.
Both Fetch.ai and ARC enables AI-driven automation through agents that can interact with dApps and blockchains without reliance on centralized intermediaries. Both of them use tokenized incentive models to encourage participation, reward contributions, and power AI-driven economies. Both projects emphasize open-source AI agent development, allowing developers to build and deploy AI-powered applications.
The key difference between these projects is that ARC is an AI agent execution framework for on-chain automation while Fetch.ai is an AI agent network enabling decentralized AI collaboration. While ARC is a Rust-based framework for execution, on-chain signing and DeFi strategies, Fetch.ai is using a multi-agent system for AI coordination, ML (Machine Learning), and economic optimization.
Bittensor
Bittensor is a decentralized machine learning protocol that enables AI models to contribute, collaborate, and earn rewards in an open, blockchain-based AI network. Unlike traditional AI infrastructures controlled by large centralized entities, Bittensor decentralizes AI model training, data exchange, and computation, creating a tokenized AI ecosystem powered by the $TAO token.
Bittensor’s key innovation is its incentivized AI economy, where machine learning models compete and collaborate to improve efficiency, accuracy, and computational power. The network is designed to allow AI models to interact, learn from each other, and be rewarded based on their contributions.
Bittensor and (ARC) both operate within the decentralized AI landscape, but they serve different purposes. Bittensor is focused on creating a decentralized marketplace for AI models, rewarding the best-performing models with $TAO tokens. It’s designed for large-scale machine learning applications and AI collaboration rather than agent-based interactions.
ARC, on the other hand, is an AI agent development framework that allows for on-chain execution of AI-powered transactions, DeFi automation, and governance participation. Its agent-centric approach makes it more suitable for blockchain-native AI applications.
Tokenomics and Financial Model
The native token of AI Rig Complex, $ARC (61V8vBaqAGMpgDQi4JcAwo1dmBGHsyhzodcPqnEVpump), was launched via Pump.fun in December 2024. Its launch through Pump.fun positions it as a blend of both the AI and meme trends. The total supply is approximately 1 billion $ARC, and its tokenomics is structured into three main allocations:
Circulating Supply (90%): 900 million tokens were made available for trading on the Solana network through Pump.fun. This open distribution allowed for broader adoption and community-driven growth, enabling $ARC to establish its value in the open market.
ARC Prize Pool & Treasury (5.5%): Tokens allocated to reward contributors and incentivize the expansion of the ARC ecosystem. They are used to fund ARC experiments, competitions, and prize pool participants.
Team (4.5%): Tokens reserved for the core developers of the ARC framework, ensuring continued innovation and development. The tokens allocated to the team are locked in escrow addresses to ensure long-term alignment and prevent market disruptions. These tokens have a one-year vesting period. The escrow addresses are as follows:
- Ap5X6HmtL4fcy2zCcAVhmhRZhrhKJjDagmkQZURUWGqV
- E38PbYFWsMV6csnSSDkfz3YVgxHka5BZhv9b1mqFHDoX
- DWMZSspWKYa1gZzhr8KQVtKBrzU778vhYuMCo59nCC7Z
- 8baRPufxZrZYq4wwkTsBkpTyz17w6JgbpPrzHWfqqrqL
- 7ziUixTvfbhum67VcaqxDH88PbvxNiSpgsxRFoKfm3EA
- 5o7tdWMcHaruJZNcKxZeqnaXytN86D5qsTH4d1hZgmZx
- EVfLDLqWGkPzGQbGtxYZmLdE2auN7DtuzRuifaRhvB3k
- 9td9nntEdY5uWy7mzcqMQkWAHszajunV6zKWan1QtQyA
- 6kqHBNdyRJ9QzJX8eBZcEQWRLpwky2bZkyPfZTqa2yoL
However, upon closer analysis, it is observed that the team tokens are still held in a single address and have not yet been transferred to escrow addresses. Currently, the tokens allocated for the team are located at the following address:
- EWYCEwXHZxYFEM3hR4g9fKeUZ2Vuw6xYEN3km93z8VoX
Our analysis has revealed several additional findings. The number of $ARC holders is 203,000, and the top 10 holders collectively control 19.3% of the total supply. Within this 19.3%, 4.5% is allocated to the team, 3.2% is held by Bitget, 2.89% by Gate.io, and 1.38% by the Raydium pool. The remaining addresses do not have any labels, leading to the assumption that they belong to whales.
We can see the changes in $ARC’s top 10 holders over time in the graph below. A total of 36 addresses appear in the chart, indicating that the top 10 holders have changed over time.
As seen in the graph below, the next analysis focuses on the number of holders within specific token ranges. The majority of holders have less than 1,000 $ARC, indicating that most investors made an investment of less than $200. The number of investors who invested between $200 and $20,000 is close to 14,000, which accounts for approximately 7% of the total. Meanwhile, only 1,068 investors have invested more than $20,000, making up less than 0.5% of the total.
The analysis changes when we examine how much supply each holder range controls. As seen in the graph below, despite the overwhelming majority of investors — 188,000 holders — investing less than $200, they only control 0.58% of the total supply. In contrast, the 14,000 investors who invested between $200 and $20,000 hold 14.5% of the supply. The largest percentage is held by 134 investors who invested between $200,000 and $1 million, collectively controlling approximately 27% of the total supply.
The $ARC tokenomics stands out due to its low allocation to the team and strong community focus. With the majority of the supply already in circulation, the risk of price instability due to newly unlocked tokens is minimized. This suggests that price movements are primarily driven by market conditions and trends. Since the tokens allocated to the team will remain locked for at least a year, potential selling pressure would only come from the prize pool and treasury allocations. Given that these will be released in multiple phases, no sudden increase in circulating supply is expected. The key point to note here is that the majority of the total supply is concentrated in the hands of a small group. While the risk of new tokens entering circulation is low, if this group decides to sell their holdings, the resulting price movements could be severe.
The question in here is that does an AI agent development framework really need a token? If the goal is to establish an AI-driven economy and incentivization mechanism, then yes. ARC aims to fulfill this purpose. However, the limited allocation for incentives raises questions about the long-term sustainability of this mechanism.
Risk Assessment and Challenges
Adoption Risk
- Risk: AI agent frameworks are proliferating (ElizaOS, ZerePy, Anda). There is a risk that a well-funded competitor might outpace ARC in adopting web3 functionalities.
- Mitigation: ARC’s open-source, Rust-based approach creates a strong moat in Solana developer accessibility. Additionally, forging partnerships and growing the plugin ecosystem helps solidify ARC’s standing.
Regulatory & Compliance
- Risk: As a web3/AI project,ARC may face evolving regulations around data privacy, KYC/AML, or token issuance.
- Mitigation: The project team can adopt a global compliance approach, working with legal counsel to ensure that the token model (utility, governance) is structured to meet regulatory guidelines.
LLM & Plugin Security
- Risk: AI “agents” that can transfer tokens or execute trades on behalf of users carry inherent security and privacy risks.
- Mitigation: The runtime must incorporate robust permissioning, limit potential exploits, and implement a red-teaming process to ensure safe usage of these automation features.
Token Utility Risk
- Risk: If the token does not become truly integral (i.e., if developers and users can bypass it), demand might remain low, and the token’s price may stagnate.
- Mitigation: Ensure the token is a crucial gateway for advanced agent features, staking for resource prioritization, and governance. A well-designed token utility makes it indispensable.
Ecosystem and Community Growth
ARC has certain advantages in terms of developer engagement and adoption due to its open-source nature and Rust-based infrastructure. With over 3,000 stars on GitHub, it has already started building a developer community. Being written in Rust makes it well-aligned with the ongoing Solana trend, increasing its popularity and helping establish a strong developer ecosystem. However, to further streamline the AI agent development process, ARC needs to improve its documentation, SDKs, and integration tools, which is currently an area where it lacks completeness.
The fair distribution of $ARC token through Pump.fun played a significant role in establishing a community-driven ecosystem and contributed to its initial growth. ARC’s blend of AI and memetic culture has proven successful in the short term. Additionally, ARC’s AI-driven economy is supported through prize pools and ecosystem incentives, which could play a crucial role in expanding the community further. However, how ARC will sustain AI agent developer incentives in the long run remains an open question. While its initial growth has been strong, a potential stagnation period could arise in the future if the incentive model is not continuously refined.
Currently, ARC has ecosystem partnerships with Solana, Send AI, Eternal AI, Hyperbolic, Shuttle Dev, Arbitrum, Abstract, and MongoDB. Given that ARC’s token is still relatively new, these partnerships are likely to expand over time. The project has also built a notable social presence, with over 48,000 followers on X (Twitter) and more than 4,000 members in the Portal channel on Telegram.
Actionable Insights and Recommendations
$ARC is positioned between AI and memecoin but closer to the AI trend. If AI tokens gain traction again, $ARC could ride the broader AI narratives in crypto. But, we should consider that the memetic nature of its launch via pump.fun, short-term price movements may be highly speculation-driven.
When we consider the potential catalysts for price action, it can be new partnerships such as AI model providers, developer tooling, and DeFi protocols, which could introduce new utility use cases, creating fundamental reasons for token demand. The integration with other blockchain networks also can be a catalyst for price movements. Another important factor is CEX listings. According to the CoinGecko data, currently $ARC is listed only CEXes like Bitget, Gate.io, MEXC. There is an opportunity to $ARC’s listing on more Tier1 and Tier2 CEXes. This could trigger price movements.
From a risk perspective, while ARC’s high initial circulation supply (90%) reduces inflationary concerns, the potential sell pressure from the Prize Pool & Treasury (5.5%) remains a factor to monitor. The market’s ability to absorb these allocations without price impact will be key in determining ARC’s long-term sustainability.
Another critical factor is the concentration of supply among a small number of holders. The top 10 holders collectively own 19.3% of the total supply, with a significant portion held by whales rather than centralized entities. While part of this is allocated to the team (4.5%) and exchanges (Bitget 3.2%, Gate.io 2.89%), the remaining share belongs to unidentified addresses, likely whales. Additionally, analysis of holder tiers shows that while 188,000 investors hold less than $200 worth of ARC, they collectively control only 0.58% of the supply, whereas just 134 investors (holding between $200K–$1M worth of ARC) control 27% of the total supply.
This heavy concentration of tokens in a small number of wallets presents a key risk — if these large holders decide to sell, it could trigger extreme price volatility and downward pressure. The impact of such movements should be carefully monitored, especially in the absence of significant new demand drivers.
For short-term trades, monitoring liquidity, partnerships, and AI market sentiment is crucial to capitalize on volatility. For long-term trades, the key factors to watch are ecosystem adoption, treasury dynamics, and exchange listings, as these could define whether ARC sustains its value beyond initial hype.
Conclusion
Finally, ARC has started its career as the leading-forward AI agent development framework, blending the efficiency of Rust with decentralized AI executions. It has set the grounds for developing DeFi and AI-powered automation and scalable agent-based applications by utilizing Solana and EVM ecosystems. With the concept of open-source, ARC has laid the strong foundation of the developer community based on its escalating GitHub presence and ecosystem partnerships.
Despite all these, ARC is strong with its technology, but it faces challenges in adoption, documentation, and plugin expansion compared to older frameworks like ElizaOS. Further, its internal economics and community-based launch via Pump.fun provided it a good push to get into some traction; however, sustainability will depend on its ability to provide token utility, attract developers, and deliver real AI use cases.
ARC is positioned from an investment perspective somewhere in the convergence between AI and memecoins, making it very susceptible to market fluctuations and the broader AI narrative. Exchange listings and partnerships could serve as key catalysts for growth, yet the selling pressure from prize pools and treasury allocations is still an aspect worth monitoring. It must navigate regulatory challenges and competitive pressure to consolidate its spot in the AI blockchain sphere.
Ample opportunity exists for ARC to become a leading AI agent framework; however, it will have to act fast in ensuring that its implementation is timely and effective and in becoming the focal point for continued innovation. The coming months will determine if ARC can transcend short-term speculative interest and establish itself as one of the foundational AI infrastructures of Web3.
Disclosure
This report is for informational and educational purposes only and does not constitute financial, investment, or trading advice. The views expressed are those of the author based on publicly available information and independent research at the time of writing. While efforts have been made to ensure the accuracy and reliability of the data presented, no guarantees are given. The author does not hold any material position in ARC or have any financial relationship with the ARC team or its affiliates at the time of publication. Readers should conduct their own research and consult with a qualified financial advisor before making any investment decisions.
