What Are Agents?
At the core of ChartGenie are its AI agents — smart, specialized tools designed to handle specific aspects of the crypto trading process.
Last updated
At the core of ChartGenie are its AI agents — smart, specialized tools designed to handle specific aspects of the crypto trading process.
Last updated
Instead of offering one generic assistant, ChartGenie gives you three focused agents, each trained for a different job.
Think of them like expert teammates, each with a role:
One focuses on coin analysis.
One predicts market movement.
One helps you with risk analysis.
Each agent is powered by models trained on real crypto data, and built to give fast, actionable insights — all in a simple interface.
🤖 What makes them different? Unlike many bots that offer surface-level summaries, each agent in ChartGenie is trained to deliver detailed, context-aware insights — built on real-time data and practical use cases.
Most crypto bots or dashboards try to do everything in one place — and end up doing it poorly.
ChartGenie takes a different approach: it gives each core function its own intelligent agent, so it can perform deep analysis, all seperately without hindering the other agents.
👀 Not only can these agents operate independently, but they can also work together — like a swarm. Here’s how: each agent shares its output with the others, allowing them to build on each other’s insights. This collaborative approach enhances the overall analysis, with each agent performing its task based on enriched, real-time data from the others.
As given above, the agents that make up what ChartGenie is, can work independently, but also in a swarm. You can enjoy individual outputs of each agents, but under the hood, a lot is going on. The agents are constantly sending each other data and are constantly communicating to make your request come true.
Below is an overview of the different communications between each agent:
🔁 Sentinel → Scribe Sentinel shares top holders and risk analysis data with Scribe. Scribe uses this to flag tokens that present high risk due to concentration or suspicious holder behavior.
🔁 Sentinel → Oracle Oracle receives token risk scores from Sentinel. This data is used to apply penalties to price predictions and to adjust the confidence of each forecasted data point.
🔁 Scribe → Sentinel Scribe provides transactional data (e.g., buys/sells, volume patterns) to Sentinel. This allows Sentinel to detect bundles, wallet behavior, and enhance its risk scoring mechanisms.
🔁 Oracle ← Scribe + Sentinel Oracle combines both structural data from Scribe and risk insights from Sentinel. This dual input allows Oracle to generate more reliable and context-aware predictions.
Want to know more about the individual agents? Head over to the tab!
