AI trading bots

The taxonomy that survives the marketing

Bot	Type	Price	AI	Backtest	Paper	TradingView	Exchanges	US
Freqtrade	Self-hosted	free	yes	yes	yes	-	11	US
Gunbot	Self-hosted	$29/mo	yes	yes	yes	yes	20	US
Bitsgap	Cloud platform	$23-149/mo	yes	yes	yes	-	17	US
Coinrule	Cloud platform	0.02% of volume	yes	-	-	yes	20	US
Cryptohopper	Cloud platform	$29-129/mo	yes	yes	yes	yes	16	US
WunderTrading	Cloud platform	$0-100/mo	yes	-	yes	yes	18	US
3Commas	Cloud platform	$15-140/mo	yes	yes	yes	yes	9	US

Live values from our database - details and caveats in each review. "-" = not documented.

"AI" is the most overloaded word in this market, so the page starts with the disambiguation:

The four buckets behave differently in practice:

• Real automation - Cryptohopper's AI-assisted strategy design and allocation on paid tiers[1], 3Commas' assistant[2]: these draft and tune configurations. Useful, priced into subscriptions, and honest about being assistants.
• Agent plumbing - Coinrule and WunderTrading ship MCP integrations where an LLM agent proposes orders against your configured rules[3][4]. The architecture is sound (human approval in the loop); the security model is young.
• Optimization searches - backtest parameter fitting relabeled. Legitimate, useful, and identical to what quant shops called "parameter search" a decade ago[7].
• Marketing - "AI-powered" anything with returns attached. The CFTC's current fraud advisory documents generative AI used to fabricate identities, documents and even live video - the label is now the scammer's favorite costume[5].

What real ML in trading looks like

The contrast worth studying is Freqtrade's FreqAI: open-source machine-learning pipelines with feature engineering, train/test discipline and prediction integration - and a documentation culture that treats overfitting as the central problem[8]. That is what "AI trading" looks like when nobody is selling you a dream: a research workflow, not a button. The gap between FreqAI's workflow and a marketplace "AI strategy" is the gap between research and advertising.

The economics also stay honest: 7 platforms pass this page's AI filter, and the AI features sit on paid tiers priced ~$26/mo/mo at median - pay for drafting convenience if you like it, not for expected alpha; no vendor publishes verified alpha from an AI feature, and the absence of that evidence after years of "AI-powered" marketing is itself the finding.

The agent era, with its security bill

MCP integrations (Coinrule, WunderTrading, Altrady[3][4]) are the genuinely new thing: an LLM with access to a trade-ordering surface. The safe pattern is constrainable: agent proposes, you approve, keys are trade-only and IP-bound (the key security guide applies verbatim), and the agent never sees withdrawal rights. The unsafe pattern writes itself - standing authority, auto-approval, keys with broad scope. Our position: the drafting value is real, the autonomy is not - and anyone selling agent autonomy over funds is selling an untested attack surface.

Platform by platform, what you actually get

Cryptohopper layers AI-assisted strategy design and allocation onto its configurator on paid tiers[1] - drafting value, with the marketplace caveat that generated strategies still need your regime validation. 3Commas ships an AI assistant across its plan range[2] - configuration help on an established execution stack. Bitsgap markets AI-launched bots with portfolio mode - launch convenience with classical bots underneath. Coinrule and WunderTrading integrate MCP, letting LLM agents propose orders against your rules[3][4] - the newest, most interesting, and most security-sensitive bucket.

The contrast set is completed by the open-source lane: Freqtrade's FreqAI[8] publishes real ML workflows with the overfitting problem stated plainly - the reference point for what "AI in trading" looks like when the goal is research rather than conversion. And the sniper lane's "AI filter" marketing (our sniper hub) shows the label at its least substantive: parameter presets with a fashion term attached.

The pricing dimension stays honest in all buckets: AI features are upsell layers, not products. Cryptohopper gates AI modes by plan tier[1]; 3Commas spreads assistant features across its ladder[2]; the MCP integrations sit on the platforms' existing plans[3][4]. None of the four buckets changes custody (the key chain applies), execution physics (fees and rate limits apply) or market risk (the regime tables apply). That is the test of every "AI-powered" claim on this page: strip the label, and which classical feature got renamed?

What the numbers say

• 7 platforms pass this page's AI filter; ~$26/mo/mo is the median entry price across the subscription lanes - price the AI feature against its decision authority, not its demo.
• 4 offer trial windows and 71% offer backtesting - an AI feature you cannot test across a drawdown is marketing you subscribe to.
• 100% document US availability - the AI label changes no jurisdictional facts.

The evaluation questions that cut through

Before paying for any AI feature, four questions with checkable answers: one, what decision does the feature make without human input (execution, configuration, or nothing)? Two, what data does it train or optimize on, and can you see the regime coverage? Three, what does the vendor publish about failure rates - not testimonials, error bars? Four, what is the blast radius if the model is wrong once - a bad config, or a bad order? The taxonomy figure's buckets map cleanly onto the answers: real automation shows its logs, agents show their approval gates, optimization shows its parameter space, and marketing shows a countdown timer.

The same questions apply to the open-source route - FreqAI's documentation answers all four by construction[8], which is why it anchors this page's honest end. A vendor that cannot answer in documentation what a free project answers in code has told you which bucket it belongs to. Apply the four questions to your own expectations too: what decision were you hoping to delegate, and what does it cost when the delegation is wrong? The answers size the feature and the position.

Warnings

• "AI" plus promised returns is the 2026 flagship scam format. The CFTC documents generative-AI fraud infrastructure[5]; the FTC's fixed-return marker[6] completes the pattern. Our scam-check tool screens bot-branded sites.
• Backtests of AI-generated strategies are generated too. A strategy that exists to be sold will backtest beautifully - validate across regimes (the bot-vs-hodl guide shows how differently regimes score the same logic).
• Agent integrations are beta security. Human approval in the loop, minimal key scopes, per-service keys[3][4]. Revisit the setup after each platform update.
• AI risk management is usually classical rules wearing the label - check the docs for what the "AI" actually decides before paying a premium for it.
• Marketplace AI strategies inherit every marketplace pathology - survivorship, overfitting, seller incentives. The scam patterns guide is the standard filter.
• The label migrates faster than the technology. Parameter search became "AI" became "agentic AI" across three years; the underlying feature never changed. Evaluate the decision authority each time the vocabulary shifts - our taxonomy figure is version-proof by design.
• Trustpilot-style widgets and self-reported ratings are operator-sourced data - the same applies to AI leaderboard screenshots. Independent, dated evidence or nothing.
• Agent integrations access your keys through the same chain as any cloud bot - the custody trade of the signal-automation lane applies to MCP flows unchanged, plus the new surface of prompt-driven actions[3][4].