One workspace holding 33+ AI tools for writing, research and chat, with the accounts, subscriptions and infrastructure needed to keep them all running.
Product design, full-stack build and deployment
AI tools sharing one account, quota and interface
Running in production at montlify.com
Authentication, subscription tiers and usage metering
A single AI tool is a weekend project. Thirty-three of them behind one login is a platform problem: every tool needs the same account, the same quota, the same billing state and the same interface, or the product stops feeling like one product and starts feeling like thirty-three stapled together.
A shared application frame so each tool inherits authentication, quota, history and layout rather than reimplementing them. Adding a tool became a configuration change instead of a release.
Prompt management, streaming responses and per-tool routing, so the model behind any given tool can change without the front end knowing about it.
Authentication, subscription tiers and per-user usage limits. The metering had to exist before anything could be priced, so it was built first rather than retrofitted.
Cloud deployment with caching on repeated work. In an AI product the cost line and the architecture are the same conversation, so both were designed together.
AI compliance platform
A self-hosted platform that audits contracts against GDPR, HIPAA and SOC 2 and returns cited, severity-ranked risk reports — with inference running on the customer's own GPUs, so no document leaves their network.
Real-time voice compliance agent
A voice agent built for three people in the room rather than two on a call. It tracks who is speaking, warns the professional privately in their earpiece when a rule is crossed, and stays silent the rest of the time.
A short call, then a written scope with a fixed price and a date. Scoping costs nothing and the document is yours either way.