TACE is TABSAP's Autonomous Content Engine — a live, running pipeline that takes content from source to published LinkedIn post without a human in the loop. It's the most operationally mature product in TABSAP's line, not because it's the largest, but because it's the only one that's actually doing its job unattended in production.
The pipeline is orchestrated in n8n, which sequences the pull from source material through generation and out to publishing. Gemini's API handles the language work — drafting and shaping content against a defined voice and structure rather than producing generic output. Supabase holds state: what's been generated, what's queued, what's already gone out, so the pipeline doesn't duplicate or lose work across runs. Gmail SMTP is wired in for the notification and approval-adjacent messaging the pipeline needs to send. The last hop is Buffer's GraphQL API, which is what actually pushes the finished post live on LinkedIn.
What makes TACE worth building rather than just running content through a chat interface manually is the end-to-end part. Most "AI content" workflows still have a human copying a draft out of a chat window and pasting it into a scheduler. TACE closes that loop — a piece of content enters the pipeline and a published post is the output, with n8n and Supabase handling the orchestration and state in between, and Buffer's API doing the final publish. It has done this for real, live posts, not just in a test workspace.
The next phase of work is less about proving the pipeline works — it does — and more about extending it: more source types feeding in, tighter control over voice and cadence, and eventually more distribution channels beyond LinkedIn. As TACE is core TABSAP infrastructure rather than a customer-facing product in the traditional sense, there's no separate pricing to publish for it; it exists to run TABSAP's own content operation and to prove out an approach that TABSAP's other products and services can build on.