Description
Dataline is designed to supercharge AI agents by providing clean, confidence-scored Web3 data. It bridges the gap between natural language intent and actionable data across a wide array of crypto markets, including Hyperliquid, Polymarket, and major DEXs, alongside essential Web2 sources. The platform's core offering is its Data API, which delivers structured data with confidence scores, allowing AI agents to process information reliably.
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Dataline's pipeline processes user intent through five stages: intent description in plain language, automatic source routing with multi-provider fallback, data normalization into a unified schema, aggregation for reliable output, and finally, the output of clean JSON with confidence scores. This ensures that agents receive consistent and trustworthy data, regardless of the original source's format or reliability.
The product stack includes the flagship Data API, the FlowAgent orchestration runtime for multi-step agent workflows, GhostDriver for browser-execution fallback on long-tail dApp UIs, and ChatPilot for deploying Telegram chatbots. This comprehensive suite empowers developers to build sophisticated AI agents capable of complex tasks.
Dataline emphasizes several design principles: a unified API for seamless integration across data sources, confidence scoring on every call to prevent agents from acting on unreliable data, and a non-custodial execution layer that allows agents to read and act directly on venues. It also boasts MCP-native integration for popular AI frameworks and flexible pricing models, including subscription, pay-per-call, and micropayments.
Use cases range from automated trading strategies like cross-exchange arbitrage and vault copy-trading to real-time signal generation from news and memecoin activity, liquidation hunting, and DAO governance research. Dataline aims to simplify the process of building and deploying AI agents by abstracting away the complexities of data aggregation and normalization.
- CategoryAI Data Analysis
- Pricing ModelSubscription, Pay-per-call, Micropayments
- DeploymentCloud
- PlatformsWeb
Dataline's Core Features
Natural language to structured data conversion
Confidence scoring for data reliability
Aggregation across multiple crypto markets (Hyperliquid, Polymarket, DEXs)
Integration with Web2 data sources
Unified API for diverse data sources
Non-custodial execution layer for acting on data
Orchestration runtime for multi-step agent workflows (FlowAgent)
Browser-execution fallback for dApp UIs (GhostDriver)
Telegram chatbot deployment (ChatPilot)
Five-stage data processing pipeline
MCP-native integration with AI frameworks
Multiple pricing models (subscription, pay-per-call, micropayments)
Production-tested with millions of transactions
How to use Dataline?
Define Intent: Describe your data needs in plain language.
Route Data: Dataline automatically selects the best sources.
Normalize & Aggregate: Data is standardized into a single schema and processed for reliability.
Receive Output: Get clean JSON data with confidence scores.
Integrate Agent: Connect your AI agent via API or MCP.
Act Non-Custodially: Utilize the execution layer for trading or other actions.
Dataline's Use Cases
- Automated Trading
- Vault Copy-Trading
- Real-time Signal Generation
- Memecoin Radar
- Liquidation Hunting
- DAO Governance Agent
- Prediction Market Betting
