Launching today
WriterzRoom
Governed multi-agent AI content for regulated industries
23 followers
Governed multi-agent AI content for regulated industries
23 followers
Enterprise Content Intelligence platform. A multi-agent pipeline governed by vertical controls, template schema, and brand voice execution. Every generation is structured, validated, and review-ready before delivery. Runs fully serverless on Google Cloud Run.
100% serverless on Google Cloud: 9 Cloud Run services (4 product, 5 internal ops agents), zero VMs to manage.
Hey Product Hunt, I'm Jason, maker of WriterzRoom.
Generic AI writers produce text. Regulated teams need drafts a reviewer can sign off on. WriterzRoom runs each request through an 8-agent LangGraph pipeline, constrained by template schema and vertical controls, and held at a mandatory Quality Gate until it passes. Professional and Enterprise plans add a claim-by-claim evidence record.
Our checks are deterministic rules, and a suite of documents with planted defects runs on every pull request: 23 of 23 seeded defects caught, 0 of 13 clean documents blocked. You can check a draft free, no credits needed.
The video above is an animated walkthrough with illustrative data.
How we use Cloud Run:
writerzroom-backend-api: FastAPI + LangGraph orchestration. Scales with generation and publishing load, and Cloud Run's request timeouts handle long-running agent chains.
writerzroom-frontend-web: Next.js 15 (1 vCPU / 1 GiB, 1→5 instances, health-checked startup probe), serving writerzroom.com.
writerzroom-mcp and writerzroom-corpus-mcp: two MCP servers that expose platform tools and the content corpus to the agents.
Internal ops, same stack: five agents (analytics, competitive intel, prospect research, outreach, content pipeline) that I use to run WriterzRoom itself, deployed the same way as the product.
Wiring: Cloud Build CI/CD (a regression suite gates every deploy) → Artifact Registry images → Cloud Run. Secret Manager for every credential, a Serverless VPC connector to private Cloud SQL Postgres, per-service IAM service accounts, and Cloud Scheduler for auto-publishing.
Why Cloud Run: elastic under load, one deploy path for every service, and no servers to patch.
Happy to dig into any of it: how we run LangGraph chains on Cloud Run, the validation layer, or how the services stay wired together. What would you want to see next?
Jason, the claim-by-claim evidence record is the detail I'd look at first. A reviewer needs something they can check when deciding whether a draft is ready to publish.
@oleksii_sekundant Thank you, and that was a design goal: Each claim in the evidence record is bound to its source with a verdict of Supported, Could not verify, or Unsupported, and anything the check can't decide is shown separately instead of reading as a pass.