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Verified Oct 15, 2026

ASI:One

Verified Oct 15, 2026 Active
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Fetch.ai's assistant and OpenAI-compatible API whose models hand work off to specialist agents

personal assistantagentic llmopenai compatible apiagent marketplaceContact sales

Listed on EffectHub ·

Web · API
Screenshot of the ASI:One website
#1240
asi1.ai as we captured it — our own screenshot, not the vendor’s press image.

Pricing

Pricing model
Contact sales

No plan cards or per-token rates appear on asi1.ai, which serves only a title and meta description to automated fetches, nor anywhere in docs.asi1.ai; the /pricing path returns 404, so no entry figure is recorded.

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Overview

About ASI:One

ASI:One is Fetch.ai's assistant layer, and it wears two faces. The consumer one is a personal AI that books flights, holds dinner reservations and manages a calendar while learning your preferences. The developer one is an OpenAI-compatible endpoint on its own api.asi1.ai host serving three models — asi1, asi1-mini and asi1-ultra — that plan multi-step work and hand individual steps to specialist agents registered on Fetch.ai's Agentverse marketplace. Because the API mirrors OpenAI's request shape, existing clients, LangChain and tools such as Claude Code or Cursor point at it with a base-URL swap. Neither asi1.ai nor the documentation publishes a price list or a per-token rate.

Platforms
Web · API
API
Yes
Last verified
Oct 15, 2026

Verified sources

  • Docs state ASI:One is built by Fetch.ai, exposes asi1, asi1-ultra and asi1-mini behind one key, accepts any OpenAI client pointed at api.asi1.ai/v1, and in planner mode delegates steps to Agentverse agents; no pricing, rate limits or per-token prices anywhere in the docs (15 October 2026)docs.asi1.ai ↗
  • asi1.ai serves a Next.js shell whose JSON-LD names Fetch.ai as parent organization and whose meta description pitches a personal AI that learns, socializes and takes action; no price list (15 October 2026)asi1.ai ↗
  • The /pricing path on the product site still returns HTTP 404 (15 October 2026)asi1.ai ↗
Fact check

Is ASI:One legit?

We don’t label tools safe or unsafe. Below are the records we checked ourselves, each with the date we read it.

Domain registered
Feb 5, 2025 (1 year ago)Registry record (RDAP), registrar GoDaddy.com, LLC, looked up Sep 15, 2026
TLS certificate
Issued by Let's Encrypt, valid until Dec 23, 2026Seen in our own connection to the site on Oct 15, 2026
Last checked
Oct 15, 2026The site answered
Operated by
Fetch.aiOur research, card verified Oct 15, 2026

How we collect these records

Editorial verdict

Pros & cons of ASI:One

low confidence

The idea worth taking seriously is routing: rather than one model trying to do everything, ASI:One plans the task and delegates steps to agents published on Agentverse, so capability grows with the marketplace rather than with the next training run. Making it OpenAI-compatible is a smart adoption shortcut — your existing client works after a base-URL change. What is missing is commercial clarity: no price list, no rate card, and a consumer pitch that promises far more than the developer docs demonstrate.

Pros

  • OpenAI-compatible API, so existing SDKs, LangChain and MCP-era tooling connect with a base-URL swap
  • Three model sizes — asi1-mini, asi1 and asi1-ultra — behind one interface
  • Models plan multi-step work and delegate to specialist agents rather than answering alone
  • Backed by Fetch.ai and tied into its existing Agentverse agent marketplace
  • Documented integration paths for Claude Code, Cursor and LangChain

Cons

  • No pricing of any kind is published — not per token, not per plan
  • The marketing site renders as an empty JavaScript shell to anything but a browser
  • Several documented doc paths return 404, so the reference material is incomplete
  • Answer quality depends on third-party agents on Agentverse, whose reliability is not vouched for
  • No country or legal entity for Fetch.ai is stated on either site

Best for

  • Developers already building on Fetch.ai's Agentverse who want a model that calls those agents
  • Testing an OpenAI-compatible alternative endpoint without rewriting client code
  • Anyone experimenting with delegation between a planner model and specialist agents

Not for

  • Production workloads that need published per-token pricing and a rate limit contract
  • Users expecting the consumer assistant promises — bookings and reservations — to work reliably today
  • Teams needing published evaluation results before switching models

Watch out: The consumer 'books your flights and dinner' framing on fetch.ai is much further ahead than the developer documentation, which describes an API and an agent marketplace and nothing about bookings.

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