Agentic AI in Trading & Markets
19 companies using agentic ai technology in the trading & markets sector. Autonomous AI agents that execute actions independently
Directory
Companies by Funding
Wayfinder
AI agents to execute tasks across chains (swaps/bridging/etc.)
Fetch.ai (FET)
Decentralized agent network (ASI Alliance)
Spectral (SPEC)
No-code AI agents for DeFi automation
Slate
Universal AI agent for natural language on-chain ops
HeyElsa
EVM/Solana/Berachain DeFAI with gasless transactions
Axal
LLM crypto portfolio assistant + signals
Related
Other AI Technologies in Trading & Markets
Related
Agentic AI in Other Segments
Frequently Asked Questions
How is Agentic AI used in trading & markets?
Autonomous AI agents that execute actions independently In the trading & markets sector, Agentic AI is applied by 19 companies tracked by AIFI Map, with $197M in combined funding. Leading companies include Wayfinder (AI agents to execute tasks across chains (swaps/bridging/etc.)); Fetch.ai (FET) (Decentralized agent network (ASI Alliance)); Spectral (SPEC) (No-code AI agents for DeFi automation).
Which trading & markets companies use Agentic AI?
The AIFI directory tracks 19 trading & markets companies using Agentic AI, with a combined $197M in funding. Wayfinder, Fetch.ai (FET), Spectral (SPEC), Slate, HeyElsa, and 1 more. (Source: AIFI Map directory.)
What is the most funded Agentic AI trading & markets company?
Wayfinder is the most funded company using Agentic AI in trading & markets, with $85M raised. AI agents to execute tasks across chains (swaps/bridging/etc.) Followed by Fetch.ai (FET) ($62M).
How does Agentic AI compare to other AI technologies in trading & markets?
In the Trading & Markets segment, Agentic AI ranks #1 out of 8 AI technologies by adoption, with 19 companies and $197M in combined funding. The most widely adopted technologies in trading & markets are Agentic AI (19 companies, $197M funded); Reinforcement Learning (17 companies, $58.7B funded); LLM / NLP (17 companies, $103.5B funded). While Agentic AI focuses on autonomous ai agents that execute actions independently, alternative approaches include Reinforcement Learning, which reinforcement learning for trading and portfolio optimization, and LLM / NLP, which large language models for nlp, chat, document understanding, and text generation.