Pantera, Coinbase back Surf’s $15M push to build crypto-native AI models

cointelegraphPublished on 2025-12-10Last updated on 2025-12-10

Abstract

Surf, an AI platform for digital-asset analysis, has raised $15 million in a funding round led by Pantera Capital, with participation from Coinbase Ventures and DCG. The funds will support the development of Surf 2.0, which includes more advanced AI models, expanded proprietary data sets, and new agents for multi-step analytical tasks. Since its July launch, Surf has generated over one million research reports and achieved significant annual recurring revenue, serving major exchanges and research firms. Its multi-agent architecture analyzes onchain data, market behavior, and social sentiment through a chat interface, reducing manual workloads. The article also notes the growing convergence of AI and crypto, citing recent funding rounds for AI startups like Nous Research and Catena Labs, as well as Coinbase’s AI tool “Based Agent.” Additionally, a “human vs AI” trading competition hosted by Asterdex is currently underway, with human traders leading in returns as of mid-December.

Surf, an AI platform built for digital-asset analysis, raised $15 million in a round led by Pantera Capital with participation from Coinbase Ventures and DCG, to expand its AI models and enterprise tools.

The company offers a domain-specific model used by exchanges and research companies to analyze onchain activity, market behavior and sentiment. The funding will go toward Surf 2.0, which will introduce more advanced models, broader proprietary data sets and additional agents designed to handle multi-step analytical tasks.

Surf said its platform has seen rapid uptake since its launch in July, generating more than one million research reports and claiming millions in annual recurring revenue, with usage from a large share of major exchanges and research firms.

Surf’s model uses a multi-agent architecture that evaluates onchain data, social sentiment and token activity, delivering its analysis through a chat interface for research and reducing manual workloads for analysts and traders.

Related: How to turn ChatGPT into your personal crypto trading assistant

The continued integration of AI and digital assets

Artificial intelligence and blockchain are increasingly intersecting as more companies develop tools that leverage both technologies.

In April, decentralized AI startup Nous Research closed a $50 million Series A round led by Paradigm. The company is developing open-source AI models powered by decentralized infrastructure and uses the Solana blockchain to coordinate and incentivize global participation in training.

In May, Catena Labs, led by Circle co-founder Sean Neville, announced it had raised $18 million to develop a bank built around native AI infrastructure. The company said the system will be designed for both AI agents and human contributors, with AI handling day-to-day operations under human supervision.

In October, Coinbase introduced “Based Agent,” a tool that lets users create an AI agent with an integrated crypto wallet in just a few minutes to perform onchain actions such as trading, swapping, and staking.

As crypto and AI continue to converge, the role of human traders may also be shifting. The decentralized exchange Aster is running a “human vs AI” trading showdown, funding up to 100 human traders with $10,000 each to compete against top-performing AI agents Dec. 9–23.

Though the competition still has 13 days to go, Team Human was in the lead as of Wednesday, with a return on investment (ROI) of 13.36% compared to Team AI’s ROI of 0.54%.

Human vs. AI trading scoreboard. Source: Asterdex.com

Magazine: Quantum attacking Bitcoin would be a waste of time: Kevin O’Leary

Related Reads

UBS: The Crowdedness of A-Share Tech Stocks Is Far From Reaching Historical Peaks

UBS: A-share tech stocks still far from peak crowding levels A-shares' technology sector has seen a strong rebound, with trading activity hitting record highs, raising concerns about market crowding. However, UBS Securities argues that a key indicator of institutional positioning suggests the current crowding level remains well below historical peaks. While the large-cap tech sector's share of total A-share trading volume and market capitalization have reached historical highs, the overweight ratio of domestic mutual funds in this sector stood at 9.9% in Q1 2026. This is down from 11.6% in Q3 2025 and significantly lower than the historical peak of 14.1% in Q4 2015. It also pales in comparison to the historical peak overweight of 18.7% for the consumer sector. UBS notes that typical cycles from a low to a peak in fund overweighting last about three years, and the current outperformance of the tech/growth style has lasted less than two years since the policy pivot in September 2024. UBS expects A-share earnings recovery to accelerate, providing fundamental support. It forecasts 2026 A-share profit growth to rise to 11% from 3.9% in 2025. Non-financial A-share profits grew 11.8% YoY in Q1 2026, with gross and net profit margins at their highest since 2023. Persistent fund inflows, the expansion of thematic ETFs, and a recovery in private fund issuance are supporting market liquidity. In tactical allocation, UBS favors growth and cyclical styles under its "slow bull" base case, with overweight ratings on six sectors: Electronics (benefiting from semiconductor inventory recovery and AI innovation), Communications (driven by AI computing demand), Machinery (aided by domestic capex recovery), Non-ferrous Metals (due to rising copper/aluminum prices), Chemicals (supported by anti-involution policies), and Electrical Equipment (driven by policy support and AI data center power demand).

marsbit44m ago

UBS: The Crowdedness of A-Share Tech Stocks Is Far From Reaching Historical Peaks

marsbit44m ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of S (S) are presented below.

活动图片