Head to head · Assistants reached by message · October 2026 research run

asaply vs Orchid

Orchid scores 20.2 (F) on agent readiness against asaply's 7.6 (F), and leads in 4 of 7 scored categories. Both do assistants reached by message.

Best AI personal assistants that act for one person · All 834 assistants comparisons

Which one, for what

asaply F

Best for People in covered neighbourhoods who want coffee, lunch, tickets and rides handled by text.

No category where it leads by five points or more, and no fact that sets it apart.

Watch for

No API, MCP server or A2A endpoint for an outside agent.

Orchid F

Best for A founder or operator who wants Gmail and calendar triage by text with approval before anything leaves.

Ahead on

  • Reliability, 50 against 10
  • Payments & pricing, 10 against 0
  • Maintenance & community, 24 against 2
  • Transparency & trust, 60 against 43

Watch for

No API, MCP server or A2A endpoint for an outside agent.

Score by category

CategoryWeight this runasaplyOrchidEdge
Reliability16%201050Orchid +40
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.21010even
Agent ergonomics13%16.200even
Security & auth14%17.500even
Payments & pricing10%12.5010Orchid +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.8224Orchid +22
Transparency & trust7%8.84360Orchid +17
Negative events≤1500
TotalF 7.6/100F 20.2/100

Facts side by side

FactasaplyOrchid
KindPlatformPlatform
VendorAsaply Inc.Zero Email, Inc.
Hosted endpointno (local only)no (local only)
Transports
AuthOAuth or keyOAuth or key
PricingPay per usePaid
x402nono
LicenceClosed service under asaply's Terms of Service, Privacy Policy and Messaging Terms (Asaply Inc., a Delaware corporation, last updated 11 October 2026).Closed service under Orchid's Terms of Service (Zero Email, Inc., last updated 16 January 2026).
Read-only variant documentednono
llms.txtyesyes
Terms last updated
Privacy policy last updated
Customer content may train models
Terms restrict automated access
Terms restrict benchmarking
Terms or service can change without notice
Arbitration or class-action waiver

Verdicts

asaply

asaply is a text-only errand assistant in early access that orders, books and pays through Apple Pay after showing the total, and can read and change a connected Google Calendar and Gmail. No outside agent can call it, the service fee isn't published, and no status page or security contact was found.

Orchid

Orchid is a paid executive assistant over iMessage, SMS and Telegram that holds drafts and calendar holds until the owner approves, with a public status page and a named subprocessor list. No outside agent can call it, there's no free tier, and its privacy policy allows training a personal model while its blog says it never trains.

Before you call either

asaply

  1. Don't plan to call asaply from another agent. It answers only texts from the owner's phone number and group chats it joins.
  2. Tell the owner each errand adds an unpublished service fee to the order total.

Orchid

  1. Don't plan to call Orchid from another agent. It answers only the owner's iMessage, SMS and Telegram threads.
  2. Check status.orchid.ai before telling the owner Orchid is down. The 7 August incident moved it to a new number.
  3. Tell the owner that drafts and holds wait for their approval unless they widen it.

Questions

Which is better for AI agents, asaply or Orchid?

Orchid scores 20.2 (F) on agent readiness against asaply's 7.6 (F), and leads in 4 of 7 scored categories.

Other comparisons with asaply or Orchid

Disclosure

asaply competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.

Orchid competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.

Machine-readable

For companies

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