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

Tab vs Town

Town scores 48.7 (D) on agent readiness against Tab's 10.7 (F), and leads in every scored category. Both do assistants reached by message.

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

Which one, for what

Tab F

Best for A person who wants a texting assistant that browses, calls and buys with tight checkout controls.

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

Watch for

Private beta behind a waitlist.

Town D

Best for An owner who wants a mail and calendar assistant whose routines other systems can trigger.

Ahead on

  • Reliability, 35 against 5
  • Schema & documentation, 33 against 0
  • Agent ergonomics, 49 against 0
  • Security & auth, 79 against 4
  • Payments & pricing, 30 against 0
  • Transparency & trust, 63 against 45

Also in its favour

  • Free to start without a card

Watch for

The privacy policy describes training with an opt-out and the trust page says training is opt-in.

Score by category

CategoryWeight this runTabTownEdge
Reliability16%20535Town +30
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.2033Town +33
Agent ergonomics13%16.2049Town +49
Security & auth14%17.5479Town +75
Payments & pricing10%12.5030Town +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85860Town +2
Transparency & trust7%8.84563Town +18
Negative events≤1500
TotalF 10.7/100D 48.7/100

Facts side by side

FactTabTown
KindPlatformPlatform
VendorTerrasoft, Inc.Town.com, Inc.
Hosted endpointno (local only)no (local only)
TransportsHTTP
AuthOAuth or keyOAuth or key
PricingPaidFreemium
x402nono
LicenceClosed service under Tab's Terms of Use (Terrasoft, Inc., effective 2 September 2026).Closed service under Town's Terms of Service (Town.com, Inc., updated 21 July 2026).
Read-only variant documentednoyes
llms.txtnono
Last releasenone2026-10-10
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

Tab

Tab is a private-beta texting assistant with a detailed security page on credential isolation and checkout binding, and a public updates page. No outside agent can call it, no price is published, and its privacy policy says nothing on training with user content.

Town

Town is a hosted assistant that works across the owner's mail, calendar and work apps, and other systems can start its routines through per-routine webhooks with rotatable secrets, idempotency keys and documented errors. A caller can't read a run's result. The privacy policy and trust page disagree on whether training is on by default.

Before you call either

Tab

  1. Don't plan to call Tab from another agent. It answers only the owner's Messages or WhatsApp thread.
  2. Tell the owner that access needs a waitlist place and no price is published.

Town

  1. Start a Town routine with POST to its webhook URL, Authorization Bearer whsec_ secret, and application/json or text/plain. Expect 202 only.
  2. Send X-Town-Idempotency-Key with a stable event id on every retry so Town doesn't start a second run.
  3. Treat 404 as wrong secret, disabled endpoint or missing endpoint alike, and ask the owner to check Routine Settings rather than retrying.
  4. Send account_email only if the owner allowed the override. It must match a connected account in full and can't widen the routine's scope.
  5. Ask the owner to keep routines that act on webhook input in approval-required mode, as Town's own docs advise.

Questions

Which is better for AI agents, Tab or Town?

Town scores 48.7 (D) on agent readiness against Tab's 10.7 (F), and leads in every scored category.

Other comparisons with Tab or Town

Disclosure

Tab 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.

Town 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.

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