Nansen launched AI-driven crypto trading tools on Base and Solana on January 21, 2026, expanding its analytics platform into direct, user-initiated trade execution. The product pairing is designed to fuse on-chain intelligence with non-custodial execution, targeting high-activity networks where retail flow and rapid decision cycles dominate.
The new workflow allows users to place trades through conversational commands inside Nansen’s web and mobile apps, replacing traditional chart-and-order-book processes with what the firm calls “vibe trading.” The AI layer translates natural-language prompts into on-chain signal interpretation, using Nansen’s database of hundreds of millions of labeled addresses to generate actionable guidance before a trade is routed.
Last month, we launched Trading Beta for paid users.
Today, we're opening up a new way to trade for 𝒂𝙡𝒍 users.🧵 👇 pic.twitter.com/J5X5uTuMKV
— Nansen 🧭 (@nansen_ai) January 21, 2026
How execution is wired
Execution is structured as non-custodial through an embedded Nansen Wallet built on Privy’s self-custodied infrastructure. That custody posture keeps assets under user control, but it also concentrates operational dependence on wallet integration, routing logic, and the accuracy of the underlying signal interpretation. For liquidity and cross-chain routing, Nansen integrated with Jupiter for Solana, OKX DEX, and LI.FI for cross-chain execution, and it indicated the setup is intended to support additional networks over time.
Fees are explicitly tiered: trading costs start at 0.25% for free users and drop to 0.10% for Pro users. Clear fee framing improves cost predictability, yet it does not substitute for execution-quality verification when trades are routed through third-party liquidity paths.
What risk and compliance teams will pressure-test
For trading desks, treasury functions, and institutional users, the combined model centralizes research, analytics, and execution into one interface while preserving user custody. In practical governance terms, that reduces third-party custody exposure but heightens the need to validate routing transparency, slippage outcomes, and the reliability of labeled-address-derived signals before it can be used in formal workflows.
The shift to AI-mediated, natural-language execution also introduces market integrity considerations. Automated interpretation of signals paired with rapid routing can reshape order-flow patterns on Base and Solana, increasing the importance of surveillance for market-abuse vectors and anomalous execution behavior. Because analytics and execution are bundled, vendor due diligence also changes: compliance teams that previously treated analytics providers and brokers as separate controls now face a single stack that spans both decision support and transaction initiation.
Even with non-custodial design and fee disclosure, operational requirements remain. Institutions adopting the tooling will need documented policies for prompt usage, approval gates, segregation of duties, incident response, and recordkeeping that aligns with audit and supervisory expectations. The real-world test is whether the interface delivers better time-to-decision and execution outcomes without creating gaps in governance and reporting.
Going forward, market participants are likely to focus on measurable execution metrics, routing explainability, and how quickly new network support is added. The adoption curve will depend on whether the analytics-plus-execution bundle can deliver repeatable outcomes while meeting institutional standards for transparency, controls, and operational resilience.