Generic AI can summarize documents and answer simple questions. But it fails at complex, specialized work in industries like aerospace, semiconductors, manufacturing, and logistics. The core issue isn't models, it's the context or scaffolding around them When enterprises try to build expert AI, they face a hard tradeoff: Build it yourself: Fully customizable, but requires scarce AI expertise, months of development, and constant optimization. Buy off-the-shelf: Fast to deploy, but inflexible. Hard to customize and doesn't scale across use cases. We took a different approach: a platform approach with a unified context layer specialized for domain-specific tasks. Today, we launched Agent Composer, with orchestration capabilities that enable: Multi-step reasoning (decompose problems, iterat...
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