AI, data & intelligence

An AI content engine that drafts, schedules, and ships social, on voice.

Generates posts, member stories, replies, and video scripts with an LLM, then publishes to X on a schedule with analytics and a voice-QA gate.

AI social engine

Brief + sourcestopics, RSS

LLM generationsix content types

Voice-QA gateon-brand check

Scheduled publishto X, analytics synced

Sector: AI content platform
Engagement: Product build
Stack: Next.js · Prisma · LLM · X API
Status: Working platform

Context

An organization producing constant social content needed volume without losing its voice, and without a person hand-writing, scheduling, and posting every item across a busy calendar.

What we built

We built an AI social-content platform. It generates six kinds of output (posts, member stories, replies, video scripts, image design briefs, and translations) via a frontier LLM, runs them through a voice-QA check so they sound like the organization, then publishes to X through OAuth. A scheduler (queue, calendar, cron) handles timing and an analytics sync closes the loop, with full OAuth auth, callback, and publish, plus cron publish and analytics jobs on a Prisma-backed store.

The value

Turns a person-bound bottleneck into a pipeline: generate, QA for voice, schedule, and publish without hand-touching every post.
The voice-QA gate keeps AI volume from sounding like AI. Content scales without going generic.
Scheduling and analytics close the loop, so posting is a managed calendar rather than a daily scramble.
Six content types from one engine (posts, stories, replies, scripts, image briefs, translations) feeding the whole social operation.

6 content types

one generation engine

Voice-QA

on-brand gate before publish

Auto-publish

scheduled posting to X

Hands-off

generate, QA, schedule, publish

Client name and identifying details withheld by design. Every figure here is drawn from the system we actually delivered.