[ PLATFORM / CAPABILITIES ]
It never stops improving.
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.
Describe your product. SaaS Factory provisions infrastructure, generates a production codebase, and deploys it.
Research agents discover what to build. Design agents write specs. Implementation agents write and test the code. All in one 30-minute loop.
Testing agents verify. Release agents package and deploy. Marketing agents generate the changelog and social posts.
Every improvement to the platform compounds across every product. Every improvement to one product is a data point for the whole fleet.
[ GET STARTED ]
Give it an idea. SaaS Factory handles the rest — infrastructure, code, releases, customers. Questions? Email us at sf-core-org-support-saas-factory@saas-factory.ai
[ AI-FIRST / INFRA-01 ]
Every product SaaS Factory generates is built for the AI era from the ground up — with a native MCP server and a built-in AI Worker baked into every deployment, not bolted on as an afterthought.
Every product generated by SaaS Factory ships with a live Model Context Protocol server
[ AGENT-TEAM / CYCLE-30MIN ]
The factory operates 24/7 through a team of specialist agents — each with a defined role. Research agents find gaps. Design agents write specs. Implementation agents write production code. Testing agents verify it. Release agents ship it. Compliance agents audit it. All coordinated, every 30 minutes, without a single human bottleneck.
Research Competitor analysis, feature gap discovery, opportunity scoring
Implementation
[ BUILD / SHIP / VERIFY ]
From discovery to deployment, every step of the software development lifecycle runs in the factory — with live observability at every stage.
Research agents continuously scan competitors, identify feature gaps, and feed the highest-value opportunities directly into the feature queue.
[ PRODUCT-OWNER / INTELLIGENCE ]
The Product Owner agent manages your feature queue, roadmap, and release plan. Ask it a question — it reads your error logs, checks pipeline health, and answers in plain English. When a feature is stuck, it offers to build it for you.
Natural language Q&A on your product's status and roadmap
[ REVENUE / CUSTOMERS / GROWTH ]
Every generated product ships with a fully wired revenue engine, CRM, support system, and deal pipeline — not as add-ons, but as core platform infrastructure that agents actively use.
The revenue dashboard surfaces MRR time series, ARR summary, revenue movement (new/expansion/churned), subscriber lifecycle funnel, and top-product breakdowns — all from real billing data, not estimates. An automated alert fires when month-over-month growth drops below -10%.
[ ENTERPRISE / INFRA-GRADE ]
The same stack that powers SaaS Factory powers every product it builds. Every improvement to the platform compounds across the entire portfolio.
SOC2, HIPAA, ISO27001 controls audited every cycle. Row-level security, encrypted secrets, and audit trails across all sensitive data paths.
[ FLEET / MULTI-PRODUCT ]
SaaS Factory is designed for builders running multiple products. The fleet dashboard gives you a cross-product command centre — pipeline health, pending approvals, release status, and agent jobs across every product, in one view.
Product suites — coordinate multi-product releases with dependency tracking
Cross-product observability — token usage, cost, and health across the fleet
[ FAQ / FEATURES ]
MCP SSE endpoint live at /api/mcp/[projectId]/sse on every product
OAuth token management with full tool usage telemetry
Expose any product capability as an MCP tool — readable by any AI agent
Alongside the MCP server, each generated product includes an AI Worker — a persistent background process that scores customers, runs churn models, triggers nurture sequences, and executes any async AI task your product needs. It runs in the same infra. No separate queue setup.
Cron-driven and event-triggered job scheduling via Inngest
Churn scoring, health scoring, and lead nurture sequences ship automatically
Every job is observable — token usage, run duration, and failure logs tracked
Release Changelog, social posts, blog drafts — shipped every cycle
Compliance SOC2, HIPAA, ISO27001 controls audited on every run
Implementation agents write production-quality code, open PRs, pass CI, and merge — with approval gates whenever you want a human in the loop.
Every night, release agents package a new version, generate a changelog, write blog posts and social content, then deploy to production automatically.
Compliance agents run SOC2, HIPAA, and ISO27001 control checks on every pipeline cycle — surfacing gaps before they become liabilities.
Every agent run is fully observable — live SSE streaming, token usage, duration, and failure logs surfaced in the dashboard for every product.
Define exactly where humans review — approval gates pause the pipeline at any stage so you can inspect before any PR is merged or release deployed.
Reads error monitoring to decide if a fix is needed
PO agent rewrites technical failures into plain-English explanations
Mission, team, suite chat, and release planning — all in one view
Stripe billing fully integrated — real money movement
Dunning sequences run automatically on past-due invoices
Subscription renewal, trial expiry, and win-back campaigns automated
A churn engine runs a weighted 6-dimension model across every customer — payment history, inactivity, usage trend, subscription lifecycle. Upsell opportunities are detected and surfaced automatically. Win-back campaigns trigger on cancellation.
0–100 churn risk score per customer
Upsell opportunity detection on high-growth signals
NPS response tracking and analysis
Proactive outreach log per customer
Inbound tickets are classified by Claude, matched against a knowledge base, and resolved with a real email reply — without a human. Tickets that need escalation are flagged. High-CSAT resolutions automatically draft knowledge base articles.
Full ticket lifecycle — ingest, classify, resolve, follow-up
Real reply emails sent via Resend API on every resolved ticket
Knowledge base articles suggested from resolved tickets automatically
A real scoring model across firmographic, BANT, ICP match, and engagement dimensions. Deals move through Kanban stages with AI-suggested next actions. Stale deals get automatic escalation with a recommended outreach.
Firmographic scoring (company, title, industry)
BANT signal weighting
Lead auto-nurture sequences (T+0, T+3d, T+7d)
Deal staleness escalation with AI next-action
Dedicated database per product, regionally placed. Migrations, schema drift detection, and index recommendations all run automatically.
Every release triggers a Vercel deployment. Environment variables pushed automatically. Deployment URL tracked per pipeline run.
Resend integration ships in every product — dunning emails, support ticket replies, CSAT follow-ups, and notification webhooks pre-wired.
Every unhandled exception is captured and surfaced in the dashboard. The PO agent reads the error log and decides whether to queue a fix.
Built-in REST API, outbound webhook delivery, rate limiting, and API key management — available to every product in the fleet.
ROI dashboard — value delivered per product, per agent cycle
25 live products running on the platform today
