

GTM Coach GPT is a purpose-built AI mentor for Go-To-Market (GTM) practitioners — from growth marketers and revenue operations leaders to sales strategists and customer success managers. It delivers real-time, role-specific guidance grounded in proven GTM frameworks, market trends, and cross-functional best practices — transforming how teams plan, execute, and optimize their market entry and expansion efforts.
Getting started takes seconds: create a free account, describe your GTM challenge — whether it’s launching a new ICP, refining messaging for an enterprise vertical, or diagnosing funnel drop-offs — and receive structured, actionable recommendations powered by domain-trained AI.
GTM Coach GPT is developed by KNITLY INC., a company founded by former GTM executives and product-led growth operators who built scalable market strategies at Series B–D SaaS companies.
Sign up for free access today: https://app.gtmcoachgpt.com
A specialized AI coach engineered exclusively for GTM professionals — combining strategic rigor with conversational agility to support faster learning, smarter execution, and measurable revenue impact.
No setup or onboarding required. After signing up, simply ask questions like “Help me build a tiered pricing model for SMB vs. mid-market” or “Draft a cross-functional GTM kickoff agenda” — and get production-ready outputs in seconds.
Yes — the core coaching experience, including unlimited queries, strategy generation, and template creation, is 100% free forever. Premium tiers (if introduced) will focus on advanced integrations and team analytics — never paywalls on foundational GTM intelligence.
It spans the full GTM lifecycle: market research & segmentation, product-led growth design, demand & pipeline strategy, sales motion calibration, customer onboarding & expansion playbooks, and cross-functional alignment frameworks.
It doesn’t just answer — it *reasons*. Using layered logic, contextual awareness, and embedded GTM mental models (e.g., RICE scoring, Jobs-to-be-Done mapping, Flywheel analysis), it surfaces trade-offs, risk factors, and implementation pathways — turning ambiguity into executable clarity.