Tearline Rebrands to Dataline, the Data Lifeline for Autonomous AI Agents

British Virgin Islands, 13th May 2026, ZEX PR WIRE - What separates an experimental AI agent from a truly capable one is its intelligence or the strength of its underlying model. Rather, it's the strength of the underlying data. Clean, reliable, and comprehensive data is the foundational layer that makes autonomous action possible.

Data is the lifeblood of agents.

Today's agents are quite capable. They are beginning to trade, interpret probabilistic markets, and interact directly with on-chain systems. However, agents can only act upon the data they receive, meaning the better the data, the better the decision-making.

That's where Dataline comes in. Tearline is rebranding to Dataline, repositioning itself not only the most comprehensive data provider for agents but also as the most trustworthy, execution-grade data infrastructure for agents to act autonomously.



Unifying, not fragmenting

Crypto is a series of islands, each built using their own tech stack and communities. This poses additional integration complexity when trying to build capable AI agents in crypto. And as any crypto builder knows, the more complex the code, the more room for devastating errors.

Most systems today rely on fragmented data stacks. Hyperliquid SDK for perpetuals, Polymarket for probability signals, Coingecko for token metadata, and more....

Before an agent executes a single trade or reasoning step, it is already operating on top of a heavily engineered coordination system.

Dataline is designed to remove this layer of fragmentation by replacing it with a single structured execution interface for data-intensive agents.

Every single request returns:
1. Natural language intent
2. Structured cross-market output
3. Source attribution
4. Confidence scoring for execution risk

Better data, better decisions

AI agents need to consume data in a language they understand, not one built for humans.

At the core of Dataline is a deterministic pipeline that replaces ad hoc data orchestration:

Intent parsing → Route selection → Schema normalization → Multi-source aggregation → Structured output generation

This architecture converts natural language queries into consistent, cross-market financial outputs, designed specifically for agent-native environments.

Agents are quickly becoming real market participants, executing trades, transfers, and prediction markets. As a result, it is even more important that these agents have access to the best, most comprehensive data to power their decisions.

19.4M transactions as production validation

Dataline is already operating at a meaningful scale:
- 19.4M+ on-chain transactions processed
- 96.4% execution success rate
- Coverage across BNB Chain, Sui, and TON
- 2.5M+ AI agent interactions via ChatPilot

Dataline is not a prototype; it's the data lifeline already supporting production-level agent activity.



Confidence as a first-class primitive in crypto data systems
In crypto markets, a raw number is structurally incomplete.

BTC = 67,123 may appear identical across contexts, but the underlying reliability can vary dramatically depending on source quality, freshness, and market dispersion.

Without visibility into these factors, agents operate with false certainty.

Dataline addresses this through a confidence model defined as

Data agreement × source reliability × freshness

Each response is paired with a confidence score between 0 and 1, enabling agents to evaluate for themselves whether data is suitable for execution before acting on it-not after failure occurs.

Confidence is not a feature-it is a contract between data and execution logic.

All-in-one

Dataline consolidates previously siloed data domains into a single structured schema:
- Crypto markets (spot, derivatives, funding rates)
- On-chain state (balances, transactions, positions)
- Prediction markets (Polymarket, Kalshi)
- News and social signals (X, Farcaster)
- Web2 APIs and long-tail data sources

Rather than increasing data volume, the focus is on ensuring coherence across execution environments, allowing agents to reason across price, position, sentiment, and narrative in a single request cycle.

Monetization scales with usage

Dataline is now live under its new branding, with developer access available for direct integration and testing. Its commercial model reflects the same shift toward autonomous systems:

- Subscription tiers for predictable workloads
- Pay-per-call crypto rails
- Machine-to-machine micropayment infrastructure

The Dataline model is explicitly designed for machine-scale, high-frequency, usage-driven environments.

Data is no longer just information. Data is the lifeblood of AI agents, and Dataline is building the infrastructure to help agents prosper.

About Dataline
Dataline is building the Full-Chain AI Stack for Web3-composable, secure, and modular AI agents that perceive, reason, and execute across smart contracts, dApps, and traditional websites. Our three flagship products ChatPilot, GhostDriver, and FlowAgent are redefining how people interact with DeFi.

Website: www.dataline.xyz

This release was published on openPR.