SaaS Factory is an autonomous platform that builds your product, studies your competitors, ships features every night, and obsessively serves your customers with enterprise-grade infrastructure — from day one.

[ CYCLE / 30 MIN — HOW IT WORKS ]
Write a one-paragraph mission. The factory provisions a Neon database, a Vercel project, a GitHub repo, and a production codebase — fully configured.
Research agents continuously scrape competitors, find feature gaps, and write prioritised specs — filling the queue without you lifting a finger.
Implementation agents write production code. Testing agents run CI. Release agents merge and deploy — every 30 minutes, around the clock.
The same stack powers every product on the platform. Each capability the factory gains flows to every product, including yours.
[ PLATFORM PROOF / LIVE METRICS ]
SaaS Factory is built and maintained by its own agent team. Every feature on this page was discovered, written, tested, and shipped by the platform — on the platform.
[ PRODUCT PORTFOLIO / MULTI-PRODUCT ]
Product suites, agency portfolios, venture studios — manage every product from a single command centre. Coordinate releases, spot drift between products, and track cross-product pipeline health from one dashboard.

Ship your first feature tonight. The agents are ready.
Questions? Email us at sf-core-org-support-saas-factory@saas-factory.ai
[ AI-FIRST PRODUCTS / AI-FIRST INFRASTRUCTURE ]
SaaS Factory doesn't just use AI to build your product — it generates AI-first products on AI-first infrastructure. Every product gets a built-in MCP server and AI Worker out of the box. Your users get AI capabilities on day one.
Every product ships with a Model Context Protocol server. Connect Cursor, Claude Desktop, or any MCP-compatible tool directly to your product's data and capabilities — no integration work required.
[ AGENT TEAM / ALWAYS ON ]
Research agents find opportunities. Design agents write specs. Implementation agents write production code. Testing agents verify it. Release agents ship it. Marketing agents promote it. Compliance agents audit it. Each has a defined role. Each runs in coordinated cycles. No bottlenecks — the factory never waits for a human approval to keep shipping.
Research Competitor scraping, gap analysis, feature discovery
Implementation Production code, PRs, CI runs, merges
Revenue Churn scoring, upsell detection, billing health
[ PLATFORM CAPABILITIES / PRODUCTION-GRADE ]
Every product the factory builds runs on the same enterprise stack that powers the platform itself. You don't configure it. You don't maintain it. It ships.
Automated SOC2, GDPR data deletion, audit logs, OWASP sweeps, dependency scanning — compliance agents run continuously.

[ SHIPPING VELOCITY / EVERY NIGHT ]
The release agent generates versioned release notes, blog posts, and social copy on every deploy. The changelog grows. The product gets better. You watch it happen. Every release is tracked, tagged, and auditable — with one-click rollback
[ MCP + AI WORKER / PLATFORM SUPERPOWERS ]
The factory doesn't build ordinary SaaS. It generates products wired for the AI era — with MCP and AI Worker built in at the infrastructure level, not bolted on later.
Every product gets a Model Context Protocol server with OAuth 2.0 token management, SSE streaming, and tool usage analytics. Connect from Cursor, Claude Desktop, or any MCP client and interact with your product's data through natural language — zero integration work.
OAuth token management with org-scoped access control
[ FAQ / COMMON QUESTIONS ]
A dedicated AI Worker runs inside your product handling background intelligence — classifying support tickets, scoring leads, computing churn risk — without writing a single line of AI code.
Your product's agents can consume external MCP tools — GitHub, Linear, and beyond. The factory connects your product to the growing MCP ecosystem automatically.
Support AI ticket routing, resolution, KB generation
Compliance SOC2, GDPR sweeps, dependency audits

MRR time series, ARR summary, cohort retention, churn prediction with automated win-back campaigns — wired in from day one.
Inbound tickets classified and resolved by Claude, with KB auto-generation from resolved tickets and CSAT follow-up.
Customer health scoring, engagement tracking, proactive outreach, NPS collection — your product ships with a full CRM out of the box.
Lead scoring across firmographic, BANT, and ICP dimensions. Kanban board, stage automation, and Inngest-driven nurture sequences.
Agent job metrics, pipeline health, error capture, token spend tracking, and fleet-wide observability across every product you run.
Features shipped from competitor gap analysis, user feedback, and quality audits
Every deploy goes through CI — testing agents verify before merge
Public changelog published automatically with each release
Approval gates available for features you want to review before merge
Built-in tool usage analytics dashboard
CORS-configured for external MCP client connections
The AI Worker runs inside your product as a background process — classifying support tickets with Claude, computing customer health scores, detecting churn risk, scoring leads, and generating KB articles from resolved tickets. Your product ships smarter than products built by hand.
Support ticket classification and AI resolution via Anthropic
Customer health scoring across engagement, payment, and NPS signals
Lead scoring with 100-point deterministic model
Churn prediction with automated win-back campaign generation