Tayler Ramsay.Designs and ships financing flows at $16B scale.

A consumer applies for financing once. The merchant wants that one application to reach 35+ lenders without 35 forms, 35 redirects, or 35 different compliance gauntlets. Every lender has its own gateway, fields, and regulatory language. The platform absorbs all of it with one application contract that themes per merchant and per lender. Compliance text becomes a design-system token, not content.

Apply is the surface a consumer sees once. Transact is the surface the merchant lives in. Three jobs on one console: Launch sends an application to a customer's device by QR, email, or Snap Sign; Track exposes the lender cascade per application with full audit log; Analytics surfaces 40+ metrics across 20 facets (approvals by age, by income band, by location, by lender). Same product themed across every merchant on the platform. Multi-tenant is not a CSS layer here. Each merchant's brand color is a token, each merchant's enabled lenders are a config, each location's role permissions scope what staff can see and do. Theming is a design system, not a stylesheet.

Merchant onboarding ate a full cross-functional team. Five days of meetings per partner to gather configurations from sales, ops, risk, and the partner themselves. Six entity types, each with about ten metadata fields, arrived through email and Slack threads. Tickets dropped, configs drifted, and stakeholders had no visibility into program status without booking a meeting. I designed OnboardIQ from a blank canvas: a flexible workflow product that codified the entire process into configurable, partner-aware steps. Audits and automation went directly into the workflow, so validation, status, and handoffs were surfaced inline instead of chased over Slack.

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Lab technicians couldn't trust AI answers without seeing the source documents. Existing tools gave answers but no verification. I built a split-screen verification interface with citation deep-linking to exact PDF coordinates so users could validate every response. The gap-detection UX uses an 85% confidence threshold: if the model isn't sure, it asks for the missing documents instead of guessing. The pattern was later extracted into Document Domain Agents, a domain-agnostic framework for high-stakes RAG.

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Most RAG systems guess when they don't have enough information, which creates dangerous false confidence in safety-critical contexts. Document Domain Agents is the framework I extracted from Rayni for any domain where AI accuracy is non-negotiable. The gap-detection UX turns AI limitations into collaborative moments. When the system needs more, users upload the missing documents instead of losing trust in it. Verification is split-screen, BLUF formatting handles scannability, and confidence indicators are calibrated to domain risk.

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Qualified is a Chrome extension that lives in the browser side panel while you shop. Tell it what you want (say, "a laptop under $1,000") and it searches products, compares them side-by-side, and surfaces real financing options from five lenders the moment intent shows, not at checkout. Architecture: React side panel → Express server on Fly.io → Claude (sonnet-4-6) with eight tool definitions → tool execution → streamed back. The wedge is MCP Apps, an extension of Anthropic's Model Context Protocol where tools return interactive HTML UIs instead of just text. Sandboxed iframes hydrate via postMessage to render comparison tables, payment calculators, product grids, and pre-filled application forms directly inside the conversation. Same multi-lender waterfall pattern as Versatile / Synchrony, reimagined as an agentic sidecar with generative UI.

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MindPattern is two systems wired together. The backend is a deterministic 12-phase Python pipeline that operates as a one-person media company on autopilot: preflight data collection across eight sources (RSS, Hacker News, arXiv, GitHub, Reddit, Twitter, YouTube, LinkedIn), parallel dispatch of thirteen specialist research agents, synthesis of 150+ findings, newsletter publishing, and platform-native social posting. A self-improving harness finds bugs in the pipeline, writes fixes using TDD, reviews its own PRs, and merges them. The public site is a chat interface built around generative UI. When the AI invokes MCP tools that return structured data, React components render directly inside the conversation instead of plain text: finding cards, source tables, health dashboards, pattern lists, skill cards. Wrapped in a Wire Room intelligence-dossier aesthetic: JetBrains Mono everywhere, manila palette, stamp badges, grid-paper textures.