Case studies — AI APP · SAAS
ReplyMagic
Multi-tenant SaaS that connects to Instagram Business accounts, monitors incoming comments in real-time, and generates brand-voice-aware replies.
ZipLyne built the entire platform on Cloudflare, Workers, D1, KV, R2, with an 8-layer spam gate that classifies every comment before spending a single AI credit. Each merchant gets an isolated brand profile; replies either auto-send or queue for human review.
Every layer, from scratch.
Bot detection → keyword filter → language detection → sentiment pre-screen → rate limit → block-list → pattern match → confidence threshold. Every comment classified before touching the LLM.
Merchants paste examples of their ideal replies. The system extracts tone, style rules, and vocabulary constraints, embedded into every generation prompt. Replies sound like the brand, not a bot.
High-confidence comments fire immediately. Edge cases route to a human approval queue. Merchants set their own confidence threshold per campaign, full control without manual overhead.
Each merchant has isolated D1 tables, separate KV namespaces, and a separate brand profile. Workers, D1 (SQLite), KV (session/cache), R2 (media), zero external infrastructure.
How the AI works.
Fast, cheap reply generation. Brand voice system prompt injected on every call. Falls back to secondary model automatically on rate-limit.
Rule-based layers run before any LLM call. Only comments that pass all 8 gates consume AI credits, keeps cost-per-reply low at scale.
Reply volume, approval rate, spam catch rate, cost per reply, surfaced per merchant in real-time. Know exactly what the system is doing and what it costs.
What it runs on.
On the bench.
- Cloudflare Workers
- Cloudflare D1
- Cloudflare KV
- Cloudflare R2
- OpenRouter
- Gemini Flash
- Instagram Graph API