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Blockchain & AI

AI Agents & On-chain Analytics

Applied AI, not an AI page

  • Agents
  • Analytics
  • Telegram
2.5M+
Users on NOTAI
240K
On-chain holders of ZORO
AI Agents & On-chain Analytics
AI chat workspace · the agent showing its work
Stack
  • Self-hosted Llama / DeepSeek
  • Vector bases
  • Telegram mini apps on TON
  • Pump.fun auto-deploy
  • ERC-20 / BEP-20 generation
  • On-chain analytics

Cases behind this

Products in this line that are running in production, with real users on them.

The applied-AI core

Applied AI where it changes the product rather than the pitch: the model plumbing – inference, agents, tooling – and the interface around it, shipped inside products with real users on them.

  • AI Agents & On-chain Analytics — AI agents & in-product assistants

    AI agents & in-product assistants

    Agents that act inside the product, not a chat bolted onto it.

    • Assistants that act on a user's portfolio
    • Agent flows wired into the product's own actions
    • An in-product assistant that adapts to the user's behaviour
    • Portfolio advice and market forecasts
    • In-the-moment trading coaching
  • Model plumbing

    Inference, agents and tooling – the part behind the interface.

    • Self-hosted LLMs – Llama or DeepSeek family
    • A vector base over the product's own data: trades, charts, user activity
    • Analytics models trained on on-chain data
    • The interface around the model, built by the same team
  • Token generation from a prompt

    The NOTAI flow: from an idea in chat to a live token.

    • Pick a category, describe the idea – the flow returns the concept and the visual identity
    • A no-code ERC-20 or BEP-20 contract written for you
    • One-tap launch with automatic deployment to Pump.fun on Solana
    • An AI token launcher inside a trading terminal
    • Auto-sniping of new launches, in-app swaps with automatic pricing
    • A PnL dashboard for every token launched
  • On-chain & social analytics

    Analytics on every screen, not a separate tab.

    • Market trends, AI analytics and asset discovery inside the terminal
    • On-chain wallet data and top-trader tracking
    • Social analytics next to on-chain data, split by category
    • Discovery across 23 chains and 80+ decentralised venues
  • Asset scoring & verification

    The AI layer of an ADGM-regulated RWA platform.

    • Analysis and verification of what backs an asset
    • Scoring before capital: AI analytics, then investor validation, then a DAO vote
    • Insight across 12 asset classes, from real estate to music and film
    • On-chain data sync for tokenized assets

Modules you add

Each of these runs in production somewhere in the portfolio – switch them on where the product needs them.

  • AI Agents & On-chain Analytics — Model marketplace & agent hub

    Model marketplace & agent hub

    • A marketplace of tokenized AI models
    • A launch hub for AI agents
    • API keys for deploying agents
  • Fraud detection & audience scoring

    Scores that survive contact with bought followers.

    • AI scoring of KOL and campaign performance
    • Reward-pool campaigns run against real audiences
    • Fraud detection on reach and engagement metrics
    • Scoring and ranking of performers
  • Data labelling & ZKML

    A working annotation network, still running.

    • Onboarding lessons and skill-based tasking
    • Leaderboards, approver roles and DAO-driven quality control
    • On-chain task tracking
    • Specialist and Expert ranks, with an academy to qualify for harder work
    • Contributors in 100+ countries
    • ZKML data labelling – the model the network started on
  • Telegram superapp delivery

    Consumer scale through the app 950M people already have.

    • A Telegram mini app on TON
    • Chain abstraction: the Telegram handle is the wallet, no seed phrase
    • Gas paid in the product's own token
    • Gamified retention: quests, clans, mini-games, referrals, staking rewards

Around the model

What we run alongside the build when the AI is a feature of a bigger product.

  • Assistant integration

    Support and in-product assistants over your product's own data.

  • Training-data labelling

    Labelling through the annotation network we already run, with contributors in 100+ countries.

  • Built-in exchange AI

    The AI module of our exchange line: advice, forecasts and coaching wired into a venue's trades, charts and user activity.

Start

Have a product to build?

Tell us the stage you are at. We will tell you what it takes to ship it – architecture, timeline and team.

One business day · scope, timeline and team