MarginWard's answer

Founders and teams building AI SaaS on flat or subscription pricing, products where LLM tokens are a real per-customer cost. From solo founders to small product teams who need their true unit economics, not just their MRR.

Handler's answer:

Handler is made for app founders, growth marketers, mobile app teams, indie app builders, and agencies that use TikTok to grow consumer apps.

MarginWard's answer

MarginWard is the only tool that joins your LLM costs with your Stripe revenue to show gross margin per customer. Cost-tracking tools show spend; revenue analytics show MRR, neither tells you which customers cost more than they pay. MarginWard does, and alerts you the moment one turns unprofitable.

Handler's answer:

Handler is built specifically for app marketers who want to find what is already working on TikTok. Instead of guessing content ideas, Handler helps teams discover outlier TikToks, understand winning patterns, and decide what to test next.

MarginWard's answer

Observability tools track your LLM spend but don't know your revenue; SaaS analytics track revenue but ignore token cost. MarginWard is built for the intersection, gross margin per customer, with alerts on unprofitable accounts. Read-only Stripe key, plugs into Langfuse/OpenRouter or a simple ingest API, set up in ~15 minutes. Flat pricing, never a percentage of your spend. There's also a free calculator, no signup.

Handler's answer:

Handler is focused on TikTok research for app growth, not generic social media management. It helps marketers move faster from “what should we post?” to clear creative direction based on real winning TikToks.

MarginWard's answer

MarginWard was built by a solo founder running his own AI SaaS. One month he realised his biggest customers were also his least profitable, burning more in LLM tokens than they paid, and Stripe never told him. So he built the tool he wished existed: the real margin of an AI product, customer by customer.

Handler's answer:

Handler was created because app teams spend too much time manually scrolling TikTok trying to understand what content works. We built it to make TikTok research faster, clearer, and more repeatable for app marketers.

MarginWard's answer

Next.js, TypeScript, Supabase (PostgreSQL), Stripe, Vercel, Tailwind CSS, Resend, with Langfuse and OpenRouter integrations for LLM cost data.

Handler's answer:

Handler uses AI analysis, TikTok content research, video metadata extraction, creative pattern detection, and a web-based dashboard to help app marketers find and understand winning TikToks.

Handler's answer:

Handler is currently early, so we are not publishing customer names yet. The product is built for app founders, consumer app teams, growth marketers, and agencies working on TikTok-based app growth.