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@llama_index

See how @intelligenceco built Cofounder, an AI chief of staff that turns business documents into agent-ready context at scale. 📄 LlamaParse handles continuous ingestion from @gmail, @SlackHQ, @linear, @notionhq, and @github every 30 minutes - processing PDFs, images, and attachments with agentic OCR 🤖 Two-stage retrieval system combines vector similarity with agent reasoning to filter by time, source, and ownership across multiple business tools 💰 Achieved lower costs and latency compared to managed RAG solutions while avoiding weeks of custom parser development ⚡ Freed engineering time to focus on core differentiator - building agents that can act - instead of document infrastructure "It probably would've taken us a month or more to build a worse document parser ourselves. LlamaParse let us focus on the agents instead of reinventing infrastructure." Read the full case study: https://t.co/1C2qyOAKaz

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