Decision logic for enterprise agents: what Saphenia does
Saphenia builds decision logic for enterprise agents, capturing a company's rules for one recurring decision and checking every agent's answer against them.
Articles
Decision logic for enterprise agents, portfolio reviews, and the decisions that are expensive to get wrong.
Saphenia builds decision logic for enterprise agents, capturing a company's rules for one recurring decision and checking every agent's answer against them.
Compare 11 portfolio monitoring and AI review tools for private equity, from platforms that store portfolio data to tools that work on the quarterly review.
A step-by-step method for private equity firms to build a recurring portfolio performance review from scattered company reports and spreadsheets.
How private equity teams handle two portfolio company reports that disagree on a figure: find the cause, apply source rules, show both, record the decision.
How private equity teams keep one KPI definition across companies, carry the period with every figure, handle redefinitions, and record missing facts.
Who should approve a corrected portfolio-company KPI, what the correction record holds, and how the correction carries into the firm's next review.
Private equity firms should set pass criteria first, test an AI portfolio review pilot on their own hardest files, trace every figure, and time the review.
A deterministic agent resolves every output into one of four outcomes and differs from retrieval in one step: each claim is checked against business rules.
A COO's guide to build or buy for AI agents: when RAG is enough, the full cost of building, and how to compare outputs on your own documents.
How heads of lending keep loan product matching current: version lender criteria by effective date, tie each match to its source, and name every refusal.
Where Saphenia runs, whether customer data trains any model, who owns what Saphenia builds from your data, and where Saphenia's ISO 27001 and SOC 2 certifications stand.
Saphenia prices a deployment on three levers: the size and complexity of your data, the number of decisions, and bespoke agent or integration work.
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