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How a Solo Gaming SaaS Structures LLM Sales Call Summaries via JSON Schema

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A single-person gaming SaaS company needed its AI-generated sales call summaries delivered as validated, structured JSON rather than unformatted text or markdown. The system uses a defined TypeScript schema with fields for titles, overviews, bullets, risks, and action items, enforced server-side using the Zod validation library. Each API call also attaches per-tenant cost metadata, making AI spending visible at the individual client level rather than buried in a combined monthly bill. Long call transcripts are split at speaker-turn boundaries before processing to stay within model token limits. The approach prioritises predictable, machine-readable output so downstream systems like CRMs, dashboards, and email jobs all consume the same validated contract without custom parsers.

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How a Solo Gaming SaaS Structures LLM Sales Call Summaries via JSON Schema · ShortSingh