Qasim Hassan.
Work

2026/AI/In Development

Dealflow AI

AI-native CRM for freelancers — deals, tasks, and follow-ups in one place.

Dealflow AI
Problem
Freelancer CRM tools are either too generic or too heavy — deals, tasks, and follow-ups scatter across notes and inboxes.
Action
Building Next.js + Expo on one Supabase backend: pipeline, timeline, and AI summarize → approve → tasks.
Result
In development as a personal Jafrix product with a shared typed monorepo.
  • Web + mobile, one backend
  • AI summary → approve → tasks
  • Shared typed monorepo
Architecture
Next.js appAuth + DBLLM / agentsDeal pipelineScore · brief · CRM hooks

Next.js product surface over a deal pipeline — intake, scoring, and AI-assisted review sitting on shared auth and data, with clear separation between UI workflows and model calls.

The Problem

Freelancers juggle leads, proposals, and deals across spreadsheets, email threads, and half-adopted CRMs — none of which are built around how a solo operator actually works, or use AI to cut the manual tracking overhead.

What I Built

Dealflow AI is a personal AI-native CRM: a Next.js web app and Expo mobile app sharing one Supabase backend.

  • Clients, deals (kanban + list), tasks, activity timeline, and dashboard KPIs.
  • Deal workspace with notes, reminders, and file uploads (Supabase Storage).
  • AI that summarizes a deal, extracts next actions, drafts follow-ups, and can transcribe audio — with an approve → create tasks path so suggestions don’t silently mutate the pipeline.
  • Server-only /api/ai/* routes so model calls stay off the client.

Major Features

  • Dual clients, one data model — web and mobile stay in sync through Supabase + shared packages.
  • Pipeline that matches freelance work — clients → deals → tasks → activity, not enterprise CRM bloat.
  • AI in the workflow — summarize, extract actions, draft follow-ups; human approval before tasks land.
  • Typed monorepo — @dealflow/shared + @dealflow/ui keep web and mobile consistent.

Key Challenges

Sharing a clean data model between Next.js and Expo without a custom API layer, while keeping AI calls fast enough to feel like part of the deal workspace — not a separate chatbot tab.

Results

Dealflow AI is in development as a mobile + web AI CRM: core pipeline screens and AI action flow are in place. Roadmap items (email/calendar sync, push, offline write queue) are still open.

Stack Decisions

Supabase was chosen so both clients get typed access to the same Postgres data without maintaining a separate API. Server-only AI routes keep keys off the client; OpenRouter / OpenAI / Groq give flexibility for text and transcription without rewriting the product surface.

Building something in this space?

I ship mobile, web, and AI product surfaces end-to-end — from product UI to payments and store releases.

Get in touch →