Reputation Score

Reputation Score

Reputation Score

Reputation Score

THE MULTI-BILLION DOLLAR INEFFICIENCY

THE MULTI-BILLION DOLLAR INEFFICIENCY

Protocol treasuries hold billions of dollars in tokens as CAC but allocate these highly ineffectively.

Optimized Airdrops

Stop rewarding tokens blindly. Reward the right users at the right time at the optimal token amount.

Monitize AI's Onchain LTV Score calculates the potential Web3 LTV of a given user for a given protocol based on historical onchain behavior.

Dynamic Token Emissions

Pre-defined token emission models are highly ineffective unless your token is Bitcoin.

Optimize token emissions & treasury management dynamically. Price collapses when you give away too many tokens, but give too few and you miss out on growth.

Developers can collaborate on agent development in a trustless way, retaining fair ownership with objective attribution and no code disclosure. Enabled by advanced innovations in mechanism design, game theory and cryptography.

UA Campaigns with Tokens

UA Campaigns with Tokens

Run targeted user acquisition campaigns with native tokens based on Web3 LTV to acquire high-quality users.

Native tokens are Web3 CAC. Optimize native token rewards per user from lookalike communities to achieve healthy unit economics.

Ask ChatGPT to solve a complex problem requiring specialized expertise, it will struggle. The future of AGI will be shaped by millions of highly specialized models. Agents built on our protocol run on specialized models with no reliance on centralized LLM providers like OpenAI.

PARTNERS

Trusted & approved by some of the leading protocols in the space.

Trusted & approved by some of the leading protocols in the space.

CITYVERSE

TYCOON

MYSTERY

SOCIETY

HARVEST

BULIEVERSE

CITYVERSE

TYCOON

MYSTERY

SOCIETY

HARVEST

BULIEVERSE

Companies we worked with via Monitize AI or Vader Research

Companies we worked with via Monitize AI or Vader Research

Comprehensive Evaluation

The Onchain LTV Score evaluates users based on their on-chain activities across multiple blockchains and off-chain market movements, integrating both on-chain and off-chain data to provide a comprehensive view of the potential value of any given user.

WHALE

LOYALTY

SENTIMENT

LONGEVITY

ENGAGEMENT

Tailored Score

We tailor the Onchain LTV Score for each category (Gaming, DeFi, L1, DePin, Infra, Social, Memes, etc.) to help protocols acquire, retain, and reward the ideal users for their specific communities.

GAMING

DeFI

L1

RWA

INFRA

SOCIAL

Hierarchical AI Agents

We develop, train, and test multiple competing ML models to achieve maximum predictive power and out-of-sample performance. We further create hierarchical AI agents to manage data perturbations, noise, and tuning effectively.

SCORE

Large Scale Model Training

The competing models are trained on a massive on-chain dataset spanning multiple blockchains and corresponding transactions. These figures continue to grow daily, enhancing the accuracy of our model and compounding the sophistication of our ML algorithms.

Dynamic Supervision

The score is dynamic, and continuously updated via simple reflex AI agents with new data from on-chain and off-chain sources. Given the volatile user behaviors, the adaptive and evaluative supervision of the models ensures that the score accurately reflects each user's current state.

TEAM

Purpose built team experienced in crypto and AI.

Purpose built team experienced in crypto and AI.

  • Mete Gultekin

    CEO

  • Engin Iyidogan

    AI Engineer

  • Veysel Tascioglu

    Data Engineer

  • Mete Gultekin

    CEO

  • Engin Iyidogan

    AI Engineer

  • Veysel Tascioglu

    Data Engineer

PROTOCOL FEATURES

Empowering scalable, composable, and highly specialized AI Agent systems.

Composable Multi-Agent System

Develop AI Agents that can be composed like building blocks to create sophisticated Multi-Agent Systems.

Agents are transparently scored and dynamically composed to maximize performance, efficiency and accuracy.

Collaborative Agent Development

Developers can collaborate on agent development in a trustless way, retaining fair ownership with objective attribution and no code disclosure.


Enabled by advanced innovations in mechanism design, game theory and cryptography.

Developers can collaborate on agent development in a trustless way, retaining fair ownership with objective attribution and no code disclosure. Enabled by advanced innovations in mechanism design, game theory and cryptography.

Highly Specialized Models

Highly Specialized Models

Ask ChatGPT to solve a complex problem requiring specialized expertise, it will struggle. The future of AGI will be shaped by millions of highly specialized models.

Agents built on our protocol run on specialized models with no reliance on centralized LLM providers like OpenAI.

Ask ChatGPT to solve a complex problem requiring specialized expertise, it will struggle. The future of AGI will be shaped by millions of highly specialized models. Agents built on our protocol run on specialized models with no reliance on centralized LLM providers like OpenAI.

MULTI-AGENT SYSTEM FRAMEWORK

MULTI-AGENT SYSTEM FRAMEWORK

The protocol automatically combines specialized Agents to form the most efficient Multi-Agent System for any given problem.

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