Agents
Many AI agents in finance rely on extremely high quality context engineering from documents š They can be roughly divided into two categoriā¦
Many AI agents in finance rely on extremely high quality context engineering from documents š They can be roughly divided into two categories: 1ļøā£ Repetitive, operational work common in back-office us
Many AI agents in finance rely on extremely high quality context engineering from documents š They can be roughly divided into two categories: 1ļøā£ Repetitive, operational work common in back-office use cases - invoice processing, loan origination, KYC 2ļøā£ Assistive agents for open-ended research and generation of reports/presentations - e.g. diligence, equity research We gave a workshop last week in NYC on how to build a high-quality document context layer to enable these AI agent use cases. At this stage, you need a rigorous OCR layer, evaluation checks, and good UI/UX for HITL review/audit - even a slight mistake in number can have catastrophic consequences downstream. Check out the resources below: ā My slides: talk a lot about document processing and the general landscape of knowledge work: https://www.figma.com/slides/QUUMQqhCsmV6tz8s5Iq9Iu ā Loganās repo on building an agentic document parsing pipeline over financial documents, with full HITL review: https://github.com/logan-markewich/finparse-pipeline Our core mission is extracting the highest-quality document context for AI agents in finance and more. Come talk to us if youāre facing relevant challenges: https://www.llamaindex.ai/contact
Source: Jerry Liu (X) | 2026-05-17