SYNTHIC

Playbook · Startup founders

Incumbents own the training data. You can own the retrieval.

Engines re-read the live web constantly. A startup that structures its story for machines today can be in tomorrow's answers — the one channel where small and fast wins.

FIG.00 — a score across eight weekly audits · illustrativeSTARTUP FOUNDERS

Founder

$49/mo

1

brands

1

seats

5

engines

01

The situation

Where startup founders stand.

A founder's first hundred customers now ask an assistant before they ask a search engine — "best X for a two-person team", "X vs Y", "is there a cheaper Z". The engines answer with whoever they already know, and they know the incumbents. Your launch post won't change that on its own.

Exhibit · the day-zero checklist4 artefacts
  1. 1

    robots.txt

    Allow the AI agents — all sixteen checked against your live file.

  2. 2

    llms.txt

    Generated from your pages; drop it at the site root.

  3. 3

    JSON-LD

    Organization and Product schema for <head>, from your own content.

  4. 4

    First audit

    Founder persona, your category keywords, all five engines.

02

The playbook

Four plays, in order.

01

Claim machine readability

Ship llms.txt and JSON-LD before your launch post. Synthic generates both from your real pages, so the first time an engine reads you, it reads you right.

02

Audit your category prompts

"Best X for startups", "X vs Y", "how do I do Z" — run the questions your first hundred customers actually ask, through the founder persona, across every engine.

03

Target the gap, not the giant

Share of voice shows which incumbent owns each prompt and where the engines hedge. Hedged answers are open answers — write the page that closes them.

04

Guard the story as you grow

Every pivot and price change is a fresh chance to be misquoted. Hallucination scans catch stale claims so the engines describe the company you are now.

03

The first thirty days

What week one actually looks like.

  1. Day 0

    Create the brand, drop in llms.txt and JSON-LD generated from your pages, allow the AI agents in robots.txt.

    Schema & llms.txt · Crawler Access

  2. Day 1

    Run the first audit through the founder persona on your category keywords, all five engines. This is your baseline.

    AI Search Audits

  3. Week 1

    Read the share-of-voice table. Write the page that closes the prompt where the engines hedge.

    Share of Voice · Content Optimizer

  4. Month 1

    Re-audit after the page ships. Scan for hallucinations after every pricing change.

    AI Search Audits · Hallucination Defense

04

Why Synthic

What startup founders actually get.

01

Founder pricing

A real plan at seed-stage money — not an enterprise quote with a startup sticker.

02

No sales call

Sign up, connect your brand, audit. The product is the demo.

03

Evidence, not vibes

Every metric links to a verbatim engine answer you can screenshot into your investor update.

04

Minutes a week

Run an audit, fix what it flags, get back to building.

05

The plan

Founder, $49 a month.

All five engines, 50 audits a month, the generators and share of voice — one brand, one seat.

  • 1 brand workspace
  • All 5 answer engines
  • 50 AI audits / mo
  • 2× multi-run confidence
  • Schema & llms.txt generator
  • Share-of-voice tracking
  • 1 seat
Modules this playbook runs on4
  • AI Search Audits
  • Share of Voice
  • Hallucination Defense
  • Schema & llms.txt

Find out what the engines say about you.

Run a live audit — the product is the demo.

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