Early Alpha — Building in public

AI-native apps
that adapt to you

Crawfish Labs is building a suite of apps where AI isn't a feature — it's the foundation. Each app learns your patterns, adapts its behavior, and gets smarter with every interaction.

See the apps

Our Apps

Three vertical apps, one shared AI platform. All in early alpha preview.

Crawfish Fit icon

Crawfish Fit

Alpha

AI-powered fitness and nutrition tracking. Built on BLS methodology with an adaptive coach that learns your schedule, recovery patterns, and goals — then adjusts your program automatically.

  • Adaptive workout programming
  • AI nutrition logging
  • Per-user coaching memory
Crawfish Budget icon

Crawfish Budget

Alpha

Financial coaching that understands your real spending life. Snap receipts, track transactions, and get proactive guidance from an AI that knows your patterns — not generic advice.

  • Receipt scanning & OCR
  • Smart categorization
  • Proactive spending insights
Crawfish Meetings icon

Crawfish Meetings

Alpha

Real-time meeting intelligence. Transcription, automatic action item extraction, and a post-meeting AI summary that actually captures what matters — not everything that was said.

  • Real-time transcription
  • Action item extraction
  • Smart meeting summaries

The Approach

We call it the Adaptive Application Paradigm — apps as LLM-native systems, not LLM-bolted-on features.

AI at the core, not the edge

Most apps add AI as a chatbot bolted onto existing workflows. We build apps where the AI layer is load-bearing — memory, coaching, and adaptation are first-class, not an afterthought. Every app shares the same per-user AI memory platform with hot/warm/cold memory tiers and a weekly refresh agent.

Users as co-developers

Every interaction is a signal. Chat, reviews, and usage patterns flow directly into prioritization and ship within hours — not quarters. The feedback loop isn't a product process, it's the product.

Composable by design

Features are Swift packages. Adding a capability to any app is one line. The shared backend handles auth, rate limiting, agent memory, and feedback analysis across all apps — so each new vertical gets the full platform on day one.