Sales + CRM Stack

A lightweight CRM you control. Open-source pieces glued with Supabase + Razorpay + a couple of background workers. Cheaper than HubSpot, more honest with your data.

Repos

Layers

Build time

About 2 weeks

Outcome

See below

You will ship

A CRM with lead capture, kanban pipelines, automated email sequences, and INR invoicing.

How to feed this to your AI agent Browse the full directory

Backend

2 repos

supabase

Postgres for the contact graph + Auth for sales team logins.

Postgres + Auth + Storage + Realtime + Edge Functions in one open-source platform. ~73k stars. The fastest way to ship a backend in 2026 for…

drizzle-team

drizzle-orm

Query patterns get complex fast — type safety pays.

TypeScript-first ORM with SQL-like syntax. ~25k stars. Lighter than Prisma, zero codegen step, faster cold starts on serverless. Becoming th…

UI + Pipeline

2 repos

shadcn-ui

Card, dialog, table, command — every CRM component fits in shadcn primitives.

The default for Next.js builders in 2026. Not a dependency — you copy components into your codebase and own them forever. Built on Radix pri…

mui

material-ui

Faster for dense admin tables when you do not care about visual differentiation.

The safe enterprise pick. Massive component library, well-documented, every internal admin tool uses it. Price: your app will look like ever…

Forms + Lead capture

2 repos

react-hook-form

Public lead forms + internal edit forms — same library.

The fastest, smallest form library for React. ~39k stars. Uncontrolled by default so re-renders stay minimal. Pairs naturally with Zod for v…

colinhacks

zod

Shared schema with the public site.

TypeScript-first schema validation. ~35k stars. The de facto choice for input validation in TS apps. Works with every form library, every AP…

7 more layers · 10 more repos · members only

Email sequences1 repo
Billing (India + global)1 repo
Pipeline UI (kanban + drag)2 repos
Voice + telephony1 repo
AI-assisted outreach2 repos
Scheduling1 repo
State + background jobs2 repos

10 more curated repos · unlock full access · members only

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How to build sales + crm stack with AI

The 4-step AI workflow

The AI agents are good at code. They're bad at deciding what stack to use. This bundle does the second part. You bring the agent.

1
Ideate with ChatGPT or Claude.ai (web)
Paste your idea: “I'm building sales + crm stack. Help me sharpen the product spec — features, edge cases, MVP scope.” Iterate for 10-15 minutes until you have a clear one-page brief.
2
Pick your coding agent
For this kind of bundle, we recommend Claude Code — Sonnet 4.6/4.7 handles full-stack multi-file reasoning best. See the install guide → Cursor and Codex are also great; pick the one you already pay for.

Feed this bundle to the agent

Open Claude Code / Cursor / Codex in an empty folder, then paste:

I'm building sales + crm stack. Use this bundle as the source of truth for the stack:
https://stackpicks.dev/build/sales-crm-stack

Brief from my product spec:
[paste your brief from step 1]

Follow the bundle order strictly:
  1. Backend
  2. UI + Pipeline
  3. Forms + Lead capture
  4. Email sequences
  ...

Stop and confirm with me after each layer.

4
Wire one layer at a time, commit between each
Don't let the agent install everything before the first git commit. One layer = one commit. Catches drift early, easy rollback.

Beyond the bundle

1Ship the boring version first. The bundle above is the maximalist list. For an MVP, start with 60% of these and add the rest when real users ask.
2Deploy early. Push to Railway / Vercel after layer 02 (auth) — not after layer 09. Production breaks differently than localhost.
3Read CLAUDE.md / .cursor/rules in this repo for the project conventions your AI agent should follow.
4Iterate on the take. If a repo here doesn't fit your specific use case, tell us — contact — and we'll add a better one within 60 minutes.