Research and product notes for understanding ontology and agents
Explore enterprise ontology, ontology-based agents, the Hopfia platform, and how Finance and Core apply to business work.
From enterprise ontology to agents in operation
Browse practical material by ontology, agents, platform, Core, and Finance.
What Is an Enterprise Ontology, and Why Do Agents Need One?
A practical guide to ontology, knowledge graphs, RAG, and how enterprise agents use shared business context across manufacturing and finance.
Read articleChanging Investment Data and Continuous Risk Review
Why financial agents should carry changing investment data into continuous analysis and risk review.
AI Agents in Specialist Financial Review
How specialized agents can execute research, analysis, and diligence review as a structured sequence of work.
Transcribing Your Investment Thesis into AI
How a firm can translate its investment thesis and decision criteria into a purpose-built agent workflow.
Institutional-Grade Intelligence for LPs
A look at purpose-built agent workflows for institutional-grade LP diligence intelligence.
Open the VDR. Get a Risk Matrix.
How connected VDR data can be structured into a reviewable risk matrix.
The Log: February 2026 Update
A concise log of the major Hopfia product changes from February 2026.
The Log: January 2026 Update
A concise log of the major Hopfia product changes from January 2026.
How to Evaluate AI Agents for Financial Work
A practical framework for evaluating financial agents that support research, analysis, and diligence beyond search and summarization.
Seeking the Irreducible Truth
Separating durable facts from uncertainty when investors face more information than ever.
The 86% Paradox: Why M&A Is Moving Beyond Domain-Specific LLMs
Why complex M&A workflows demand more than a domain-specific language model.
Why Institutions Require Verifiable AI
Why evidence, sources, and analysis traceability must be product features in institutional investing.
M&A Stages, Due Diligence, and AI
Where AI can support screening, diligence, and decision-making across the M&A lifecycle.
LLMs and Document Queries: Overconfidence and Incomplete Retrieval
Why confident answers can still miss relevant evidence in document-based investment research.
How Agentic AI Rewrites the Diligence Workflow
A connected workflow from deal data ingestion to evidence-backed diligence output.
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