Joined December 2023
- Tweets 285
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- Followers 332,040
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151 Photos and videos
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Jun 3
The next big Dataline milestone: announcing the Data Launch Partner Program, opening the initial cohort.
Building the data layer for the next era of AI. Internet and crypto should be unified, not walled gardens.
Your AI is evolving. Shouldn't your data be too?
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Jun 11
Coinbase now lets AI agents trade crypto autonomously.
Execution is solved. Trading well is a data problem: stale prices, mispriced funding, thin books all kill an agent's P&L.
Dataline ships the reads that fix that, per call. Spot, funding, prediction odds, freshness baked in.
Jun 11
JUST IN: Coinbase now allows AI agents to trade crypto autonomously.
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Jun 11
Welcome @SentientAGI to the Dataline Launch Partner cohort.
When ROMA's agents act on crypto data, Dataline is the call: spot, perp funding, prediction markets in one structured response, ready for the Planner / Executor / Verifier loop.
One integration. All markets.
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Jun 9
Welcome @GoKiteAI to the Dataline Launch Partner cohort.
Kite Chain settles agent transactions in sub-second finality. Dataline is the data layer those agents call before settling: spot, perp funding, prediction markets, in one structured response.
Data → Decision → Settle.
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Jun 5
Every major crypto vendor shipped an MCP this year.
CoinGecko. CoinMarketCap. Coinbase. Cryptodotcom. BitGo. Base.
MCP hit 97M monthly downloads.
"Agent-native via MCP" stopped being a moat three months ago. Table stakes now.
Three places we think edge actually lives:
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Jun 5
3/ Settlement that fits machine traffic.
x402: 69k agents, $50M cumulative, $28k/day real volume. Coinbase shipped an AI Agent App Store on top.
Pay-per-call rails, M2M micropayments, schema settlement in the same response. The agent doesn't stop to coordinate.
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Jun 5
We don't ship "agent-native MCP" as the pitch. Every vendor in the category claims it now.
We ship cross-domain in one call. Confidence-scored. Metered per call.
Full write-up: dataline.xyz/blog/mcp-isnt-t…
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Jun 4
🤝🫰
Set-and-forget only works if you trust what the agent is reading before it moves.
That's the part @DatalineAI handles, and it sits right in front of where B3OS takes over to execute onchain.
Glad to be a Dataline launch partner.
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Jun 4
We are welcoming @b3dotfun to the Dataline Launch Partner cohort.
B3OS is the execution plane for crypto AI agents: workflows, nodes, and connectors that run set-and-forget. Dataline is the data layer those agents query before they execute.
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Jun 3
The next big Dataline milestone: announcing the Data Launch Partner Program, opening the initial cohort.
Building the data layer for the next era of AI. Internet and crypto should be unified, not walled gardens.
Your AI is evolving. Shouldn't your data be too?
Thread 👇
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Jun 3
Dataline is already running in action:
19.4M on-chain transactions
96.4% execution success rate
BNB Chain · Sui · TON
Three production agents live on top: ChatPilot, GhostDriver, FlowAgent.
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Jun 3
Slots are limited. Head to our site to learn more.
gtm.dataline.xyz/partner-sig…
What data would be helpful for your AI agent? Tag the project below.
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May 26
1/ Polymarket went dark in India last week.
Indian ISPs cut access after a government betting-platform directive. Kalshi could be next.
If your agent only reads Polymarket's API, it doesn't have a graceful fallback today. Here's what one schema across both venues looks like:
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May 26
3/ get("senate-2026-OH")
Dataline returns one response carrying both venues. Source IDs, freshness per source, divergence_flag = true when Polymarket and Kalshi sit more than 3pts apart.
The agent picks the median, the range, or the gap by reading one field.
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May 26
4/ When a venue disappears or a competitor takes share, the customer doesn't rewrite the agent.
The schema absorbs the change two layers down. Whether Polymarket comes back online or Kalshi extends its lead, the agent code stays.
more about using one Schema for both markets
dataline.xyz/blog/aggregate-…
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May 22
Building a trading agent? Imagine it operating on fee data that isn't clean.
For an agent, the gap between the quoted price and the executed cost isn't friction. It's a wrong trade. Here's what the real number looks like:
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May 22
3/ The displayed fee is incomplete. Slippage, bridge cost, routing markup, and gas all stack on top of the quoted percentage. If the agent reads only the quote, it ships decisions on a number that's already wrong by hundreds of bps.
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May 22
4/ Dataline returns every fee inline before the trade executes: pool quote, swap event log, price snapshot, freshness flag. The agent reads one response and decides on a number that doesn't move after the click.
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