How I'd build Investor AI
I'd reach for Next.js on the frontend with TypeScript and shadcn/ui for the form components, connect it to a FastAPI backend in Python where the Claude API lives, Postgres for the database with a careful multi-tenant schema, Stripe for billing, and Resend for transactional email. I'm estimating 480-520 hours to get to a production launch, about 12 weeks at 40 hours per week, because the compliance piece adds real weight.
Day-by-day plan
Week 1:
- Day 1-2: Auth schema with Auth0, multi-tenant organization model in Postgres, role-based access control for compliance officers vs. advisors
- Day 3: Stripe integration for the three tiers; customer creation webhook that provisions tenant and sets feature gates
- Day 4: Customer onboarding flow - org setup, team member invites, compliance officer approval step
- Day 5: Basic document template system; schema for letter types, placeholder variables, firm-specific customization fields
Week 2:
- Day 1-2: Claude API integration with multi-shot prompt caching to avoid re-running compliance checks on the same template rules; test generation of suitability letters against mock client profiles
- Day 3: Document preview UI with Monaco editor so users can tweak generated output before sending
- Day 4: Email distribution via Resend; attachment handling for PDFs
- Day 5: Compliance audit logging - every generated document, every edit, every send logged immutably to Postgres
Week 3:
- Day 1-2: Integration tests against the full pipeline; edge case enumeration for letter types
- Day 3-4: Deployment setup with Caddy reverse proxy, database migrations, monitoring with error tracking
- Day 5: Internal hardening and security review
What's hard about this build
The core risk is liability. If an RIA uses Investor AI to draft a suitability letter and FINRA later flags it as non-compliant (even if the RIA edited it afterward), they'll cancel and warn every other RIA they know. That's a small, tight-knit community. I need to be ruthlessly honest in the prompts about what the AI can and cannot guarantee. The second hard piece is firm-specific compliance mandates. Each RIA's compliance officer has their own format requirements, some demand specific language around concentration risk, others don't. Scope creep here is real; I'll build a template system that's customizable but bounded. Third, the incumbents - Orion, Redtail, Wealthbox - are already shipping AI features inside the platforms where RIAs live all day. Standalone tools have integration friction. I'd accept that and focus on nailing the three use cases instead of trying to be everything.
What's fast because of AI
Claude accelerates the scaffolding. Generating Next.js form components, FastAPI endpoints, and Postgres migrations from a specification saves me 2-3 days of boilerplate. Test generation - writing comprehensive edge cases for letter generation, client scenario handling, and error paths - that'd normally take a week, Claude enumerates the cases and drafts the tests in a day. Writing clear, compliance-conscious prompts is an iteration process, but Claude helps me reason through what guardrails matter and what's theater. UI copywriting - the microcopy on buttons, tooltips, and error messages - Claude drafts that in an afternoon instead of it living half-finished for weeks. Debugging multi-tenant issues is tedious; Claude helps me trace the request path and spot where the tenant context got dropped faster than manual inspection would.
How I'd hand it off
I'd record a Loom walkthrough of the admin panel, the customer onboarding, and the full document generation flow. I'd leave a runbook in Markdown covering database schema, environment variables, Stripe webhook handling, and how to onboard a new customer. I'd do a 30-day pager rotation with you; first two weeks you shadow me on any production issues, second two weeks I shadow you, so the operational knowledge sticks. I'd transfer Stripe secrets, the Postgres database access, and Claude API credentials into whatever secret manager you use.