The Prompting Company

What do they actually do

The Prompting Company is a SaaS that finds the specific questions people ask AI systems (ChatGPT, Perplexity, Gemini, Claude) about a product category, writes short, structured answers, and publishes simplified “AI‑optimized” pages that models and agents can easily read and cite. They also host those pages and provide “routing” so agents land on machine‑friendly versions without popups or heavy UI, improving the odds of being referenced in answers (homepage, routing FAQ).

Customers get prompt tracking/analytics, connectors across major LLMs, hosted pages, and enterprise options like SAML SSO and white‑glove onboarding (homepage pricing & features). The company targets fintech, developer tools, and enterprise SaaS; coverage reports a Fortune‑10 customer, ~0.5M pages hosted, and client traffic in the double‑digit millions per month (TechCrunch). Effectiveness depends on whether LLMs/agents crawl and cite the hosted pages, and LLM mentions don’t guarantee conversions; customers still need solid funnels (routing FAQ, TechCrunch context).

Who are their target customer(s)

• Head of Growth at a fintech startup: AI assistants don’t mention their product in category queries, causing lost discovery. They want reliable ways to be cited by ChatGPT/agents for relevant prompts (TechCrunch).
• Product marketing or docs owner at a developer-tools company: Existing docs are long and human‑oriented, so LLMs don’t pick them up. They need short, structured Q&A pages that models can parse and cite (homepage, routing FAQ).
• Head of SEO / organic growth at an enterprise SaaS: Search behavior is shifting to AI answers. They lack visibility into which prompts mention their brand across LLMs and whether those mentions correlate with outcomes. They need prompt tracking, cross‑LLM connectors, and analytics (homepage).
• Enterprise procurement / IT lead at a large company: They need secure hosting, predictable onboarding, and enterprise controls (SAML, SLAs) before adopting vendor‑hosted pages that affect brand representation (homepage, TechCrunch).
• Founder or brand/PR manager: LLM answers can omit or mis‑describe the product. They want authoritative, machine‑readable pages to influence how agents describe and cite their brand (TechCrunch, routing FAQ).

How would they acquire their first 10, 50, and 100 customers

• First 10: Run focused, high‑touch pilots via YC/network and targeted outbound to fintech and dev‑tools teams. Offer a low‑cost audit, publish a handful of AI‑optimized pages, and run a routing test to quickly show citations; close with white‑glove onboarding and one strong case study (homepage, TechCrunch).
• First 50: Use pilot results as proof. SDR outreach with a tailored “prompt gap” report to Heads of Growth/PMMs; convert mid‑market buyers to Pro (self‑serve or low‑touch) and publish before/after examples to drive inbound (pricing & features, pricing FAQ).
• First 100: Add channel partnerships (docs platforms, agencies, LLM/agent vendors) and an enterprise motion. Ship SAML/SLAs, hire a small enterprise sales/onboarding team, and automate page generation/hosting to lower CAC while closing larger accounts (TechCrunch, routing FAQ).

What is the rough total addressable market

Top-down context:

Anchored to enterprise software (~$257–$280B in 2025) and global digital ad/marketing spend (hundreds of billions), reallocating even 0.2%–1% toward AI discovery infrastructure implies low‑single to high‑single‑digit billions in annual TAM (Precedence Research, digital ad spend summaries).

Bottom-up calculation:

Assume ~300k–600k global mid‑to‑large companies care about LLM/agent discoverability (US mid‑market ~200k as an anchor). With ACVs from ~$2k–$75k, scenarios land around ~$0.6B–$1.5B+ ARR, consistent with the top‑down range (NCMM report).

Assumptions:

• A small share (0.2%–1%) of enterprise software + digital marketing budgets shifts to AI discovery/agent infrastructure.
• 300k–600k mid‑to‑large companies globally will prioritize LLM/agent discoverability (US mid‑market ~200k anchor).
• Blended ACVs of ~$2k–$75k depending on SMB vs. enterprise mix.

Who are some of their notable competitors

• Yext: Enterprise brand visibility platform with a knowledge graph and AI search visibility features (e.g., Scout) that help structure data for LLMs and monitor how brands appear across AI answers—overlapping with tracking and AI‑readable content goals (AI Search explainer, Scout/visibility blog).
• BrightEdge: Enterprise SEO platform adding capabilities for AI Overviews/SGE monitoring (e.g., BrightEdge Generative Parser) and guidance to optimize for generative search—adjacent to LLM discoverability budgets (AI Overviews guide, SGE guide).
• Conductor: Enterprise SEO provider publishing workflow guidance and tools for Google’s AI Overviews/SGE and broader AI discoverability—competes for the same “be present in AI answers” budget line (Conductor blog on AI Overviews, SGE academy guide).
• Mintlify: Developer documentation platform that markets docs “built for both people and AI,” supports llms.txt/MCP, and ships an AI Assistant that answers questions from a product’s docs—overlaps for dev‑tools buyers seeking AI‑readable, citable content (homepage, AI Assistant docs).
• Rankshift AI: A GEO/LLM visibility startup offering tracking and playbooks to measure citations/mentions across AI engines (e.g., Perplexity) and optimize content for AI—directly overlaps with LLM mention tracking and optimization (Perplexity tracking guide, GEO for Perplexity).