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Introducing Coinbase Apps

Mar 28, 2014 • 1 min de lectura

We’re excited to announce Coinbase Apps — our own app store for apps built using Coinbase platform and APIs.

As developers ourselves we set out to build Coinbase to be developer friendly from day one. Our API has been used for thousands of apps, all the way from small evening projects to integrations in apps like Pounce and Gliph. Even our own Android application is build completely on our public API.

If you’re an app developer and want to submit your application to Coinbase Apps, visit your OAuth2 applications page. If your app isn’t using OAuth but still features Coinbase integration, send us a note. To learn more about developing for Coinbase platform, head to our developer site.

Historias recientes

Singapore Sees 43% Drop in Crypto Scam Losses and Partnerships Like Ours Are Helping Drive the Change

Coinbase

Oct 13, 2026•Tiempo estimado de lectura: 2

TL;DR: Singapore’s crypto scam losses fell 43% year over year, from S$114.9 million to S$65.5 million, as a result of stronger enforcement, public education, and partnerships between the Anti-Scam Centre and industry leaders like Coinbase. Through four joint operations, Coinbase’s Global Intelligence team helped identify 720+ victims and prevent more than S$18.9 million in potential losses, while a new anti-scam awareness campaign reached Singapore retail customers.

International

Part 3/3 Owning Intelligence Series: How Coinbase Built, Evaluated, and Post-Trained a Fraud Agent

Yao Ma, Xuwei Tan, Akshit Trehan, Aman Choudhary, Anyscale Team: Eric Tang, Sumanth Hegde, Seiji Eicher, Jess Kong

Oct 8, 2026

TL;DR: Using SkyRL on Anyscale, we post-trained Qwen3.5-9B for Onramp fraud detection and served it with Ray Serve LLM and vLLM. On our benchmark, it exceeded Opus 4.5 across all four detection metrics, including 9.6% higher F1. In online inference, we reduced end to end latency by 55%.

Engineering

Part 2/3 Owning Intelligence Series: How Coinbase Built, Evaluated, and Post-Trained a Fraud Agent

Yao Ma, Xuwei Tan

Oct 7, 2026

TL;DR: Newer LLMs are not necessarily better at domain-specific tasks. On our fraud benchmark, newer Opus, Sonnet, and GPT versions all had lower recall, F1, and dollar-weighted recall—even when precision improved. The lesson: choose models using high-quality, domain-specific benchmarks, with reproducible evaluation and ideally deterministic scoring against verified outcomes. These findings also motivated our next step: post-training open-weight models for greater control over quality, cost, and deployment.

Engineering

Descargo de responsabilidad: Coinbase Financial Services Europe Ltd. ofrece el comercio de derivados a través de la plataforma Coinbase Advanced a clientes elegibles del EEE. (Licencia CySEC 374/19). Para acceder a los derivados, los clientes deberán pasar por nuestras verificaciones de evaluación estándar para determinar su elegibilidad e idoneidad para este producto.

Introducing Coinbase Apps

Historias recientes

Singapore Sees 43% Drop in Crypto Scam Losses and Partnerships Like Ours Are Helping Drive the Change

Part 3/3 Owning Intelligence Series: How Coinbase Built, Evaluated, and Post-Trained a Fraud Agent

Coinbase and Samsung Bring USDC to Samsung Wallet

Part 2/3 Owning Intelligence Series: How Coinbase Built, Evaluated, and Post-Trained a Fraud Agent

Coinbase está construyendo la plataforma de trading más completa

Part 1/3 Owning Intelligence Series: How Coinbase Built, Evaluated, and Post-Trained a Fraud Agent