Inspiration: Casual chats are full of half-baked sparks. We keep branching those sparks into clearer paths, push them farther with specific next steps, and let you choose (or auto-finish) the ending that actually ships.h.
What it does: Turns any message into unlimited, linkable branches and automates execution. Scrapes, LLM pipelines, and email sequences (templates, follow-ups, A/B). Branches can merge across chats so isolated ideas form a single, actionable pipeline.
How we built it: VS Code–driven dev + backend, a lovable interface, and pluggable API extraction from Anthropic, Apify, and Bright Data power a chat-first, graph-native platform that dispatches work through a scalable worker pool to execute validated micro-prompt pipelines and push results to SMTP/CRMs — with per-branch cost estimates, dry-run modes, and full observability to keep automation safe, auditable, and revenue-driving.
Challenges we ran into: Combinatorial state growth, LLM hallucination, flaky scrapes, and runaway API costs. We solved these with depth/cost caps, dry-run gating, hybrid scraping fallbacks, embedding-based merge suggestions, and human-in-the-loop approval for high-impact sends.
Accomplishments that we're proud of: Working end-to-end prototype: reliable scrapers pull structured data, deterministic prompt pipelines synthesize richer insights, embedding-driven merge UX links formerly unconnected branches, and automated outreach engines generate and send personalized email sequences .
What we learned: Branching is only valuable when paired with controls: auditability, mergeability, and cost predictability. Connecting unlinked ideas often unlocks more ROI than digging deeper in a single thread. Prompt design is product design.
What's next for Brunch: Scale multi-agent orchestration, ship advanced email automation (sequences, analytics, delivery optimization), release vertical templates (PR, influencer outreach, research), add CRM/GitHub/Calendar connectors, and build enterprise privacy/VPC options to unlock larger deals.
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