Loopr
Solo founders running high-touch outbound workflows get overwhelmed by bloated CRMs designed for teams. They need one focused place to track leads, analyze replies, and know exactly who to follow up with next.
1. The Founder's Problem
Solo founders running high-touch outbound workflows get overwhelmed by bloated CRMs designed for teams. They need one focused place to track leads, analyze replies, and know exactly who to follow up with next.
2. Why Traditional Solutions Failed
- ✗Traditional CRMs are built for enterprise pipelines, not solo founder workflows
- ✗Lead context is scattered across sheets, notes, and inboxes
- ✗No tool combines CRM tracking with daily AI guidance in one calm workflow
- ✗Most products add noisy notifications and gamification instead of clear next actions
3. What We Built
- ✓Dual pipeline modes: sheet view for fast edits + Kanban view for stage-based movement
- ✓AI daily briefing surfacing who to follow up with and why
- ✓Signal Score system rating each lead from 0-100 based on engagement signals
- ✓Reply analyzer for sentiment + AI-suggested next steps
- ✓Single-tenant data model with Supabase RLS and CSV export
- ✓Pipeline analytics with stage conversion trends and performance charts
- ✓Calm, distraction-free interface with no notification spam or streak mechanics
4. The Process
WEEK 1
Pipeline schema + auth + RLS foundation (4 days), sheet/kanban UI architecture (3 days)
WEEK 2
AI briefing + reply analyzer integration (4 days), signal scoring logic + lead workflows (3 days)
WEEK 3
Analytics layer + polish + deployment hardening (3 days)
5. Results & Metrics
Users
31 signups
Revenue
$0 (early beta)
GitHub
9 stars
Performance
Sub-second pipeline interactions, real-time analytics
Code
TypeScript-first React 19 + Vite build
6. Tech Stack & Why
7. What We Cut to Ship Fast
- –Team collaboration features (kept solo-founder-first)
- –Mobile app (prioritized desktop outbound workflows)
- –Email provider integrations (deferred to post-MVP)
- Solo founders value clarity over feature quantity. Removing noise improves daily usage.
- Daily AI briefings drive action only when tied to pipeline context and specific next steps.
- Signal scoring needs transparent logic. Black-box scoring reduces trust.
- Dual views (sheet + kanban) cover both speed editing and strategic pipeline movement.
8. Lessons Learned
- Solo founders value clarity over feature quantity. Removing noise improves daily usage.
- Daily AI briefings drive action only when tied to pipeline context and specific next steps.
- Signal scoring needs transparent logic. Black-box scoring reduces trust.
- Dual views (sheet + kanban) cover both speed editing and strategic pipeline movement.
Screenshots
What This Actually Proves
- ✓I ship fast: 7 MVPs in 14-21 days each. Not prototypes - actual working products with auth, payments, databases.
- ✓I'm honest about metrics: 10-50 users, $0 revenue (test mode), 7-10 GitHub stars. No fake numbers.
- ✓I know what to cut: Real-time features, team collaboration, mobile apps. Ship core value first.
- ✓I learn from mistakes: RLS policies are hard. Prompt engineering takes 15+ iterations. Financial calculations need edge case testing.
- ✓I justify tech choices: Supabase over Firebase (cheaper, better for relational data). Groq over OpenAI (10x cheaper, 800 tokens/s).
