World First: Henon Launches Zero-Error RAG System for Financial Workflows
TORONTO, Jan. 8, 2026 /CNW/ - Henon today announced the release of the world's first Zero-Error Retrieval-Augmented Generation (RAG) system built specifically for unstructured data within financial workflows. The launch represents a breakthrough in AI-assisted infrastructure for private equity and credit firms, where even minor inconsistencies in generated output can carry major financial or operational risk.
Most advanced RAG systems operate within the 75% to 92% accuracy range, which may be acceptable for consumer applications but remains unacceptable for institutional finance. Henon's zero-error RAG has been tested across structured reporting, valuation workflows, audit trails, and scenario modeling. It delivers consistent, explainable, and correct output across every query.
Henon's architecture integrates a controlled retrieval layer with structured data governance. This eliminates ambiguity at the source. The result: no hallucinations, no approximations. Just grounded, auditable answers drawn from the right information every time.
"For most RAG systems, 88% accuracy is considered a win," said Peter Zwicker, CEO of Henon. "But when you're generating portfolio statements, regulatory summaries, or valuation commentary, 88% isn't even close. Zero-error isn't our slogan, it's our threshold."
The zero-error RAG engine is now available across Henon's monitoring, reporting, and modeling modules. It operates across both historical and live portfolio data and includes embedded reasoning checks and source traceability. This gives teams confidence in every output and a clear path to verification when needed.
"AI-assisted workflows are only useful if the output is correct," said Jeff Batchelor, Global Head of Client Experience at Henon.ai. "With Henon, firms can rely on real answers from their real data. Not a guess. That's the standard we've built toward."
The release is part of Henon's M1 architecture. It removes friction from every stage of financial data management, from ingestion to insight, and ensures CFOs, sponsors, and operators can move from data to decision with confidence, without switching tools, retracing steps, or second-guessing data.
About Henon
Henon is an AI-native platform for private equity and credit firms. Built to reduce friction from data to decision, Henon combines data warehousing, monitoring, reporting, modeling, and valuation tools in a single, secure system of action. Henon supports a global network of clients from offices in Toronto, Chicago and London.
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Forward-Looking Statements
These statements may relate to, but are not limited to, Henon's expectations regarding the amount and the terms of a contract and the expected benefits of Henon's software platforms. Forward-looking statements are inherently subject to risks and uncertainties, some of which cannot be predicted or quantified. Forward-looking statements are based on information available at the time those statements are made and were based on current expectations as well as the beliefs and assumptions of management as of that time with respect to future events. These statements are subject to risks and uncertainties, many of which involve factors or circumstances that are beyond Henon's control. These risks and uncertainties include the ability to meet the unique needs of customers; the failure of Henon's platforms to satisfy customers or perform as desired; the frequency or severity of any software and implementation errors; Henon's platforms' reliability; and customers' ability to modify or terminate the contract.
SOURCE Henon Financial Technologies
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