This topic covers verifiable AI trading assistants and crypto trading bots: agentic systems that execute market strategies, connect to exchanges and on‑chain data, and produce auditable decisions. It’s timely in 2026 because institutional and retail adoption of automated crypto trading has grown alongside stricter audit, governance and compliance expectations. Market volatility, DeFi composability, and regulatory focus on algorithmic trading increase demand for systems that can prove provenance, reproducibility and safety. Key categories include AI Agent Marketplaces (discover and exchange prebuilt trading agents), Agent Frameworks (build and test agent logic), AI Tool Marketplaces (integrate data and models), AI Automation Platforms (orchestrate live workflows and risk controls), and Market Intelligence Tools (real‑time pricing, on‑chain signals, and backtesting). Representative technologies in this space: AutoGPT and AgentGPT provide ways to spin up autonomous workflows and no‑code agent instances; LangChain supplies engineering primitives and stateful tooling for reliable agent behaviour and evaluation; Windsurf (formerly Codeium), GitHub Copilot, Tabnine and Tabby accelerate development, testing and private model deployment for strategy code and connectors. Practical priorities for verifiable trading assistants include signed execution logs, versioned models and prompts, deterministic backtests, access controls, and explainable decision traces. Alternatives to GateAI will differ by deployment model (self‑hosted vs cloud), ease of audit, and integration with market intelligence feeds and exchange APIs. Evaluating tools requires assessing reproducibility, latency, governance features, and integration with risk‑management workflows. This topic helps teams compare frameworks and platforms to build, verify and operate AI trading agents in regulated, high‑velocity crypto markets.