Ermos AI for lender policy lookups.
Every brokerage runs on policy knowledge: which lender takes this income type, how that one treats casual employment, who will look at this postcode. The knowledge lives in policy documents, BDM emails and the heads of senior brokers. An Ermos unit makes it a library the whole team can query.
How it works on the unit
Lender policy documents, credit updates and your own scenario notes are indexed on the unit as they arrive.
Which lenders fit self-employed under two years, how does this lender treat rental income, what were we told about this niche last quarter.
Responses point to the policy document and section they came from, so the broker confirms against the current source.
Policies move constantly. The unit finds the position fast; the broker confirms currency with the lender or BDM before lodgement, as always.
What it changes in the brokerage
Scenario research drops from an afternoon of PDFs to a question, juniors stop interrupting seniors for policy memory, and the knowledge from every BDM conversation compounds instead of evaporating, because ErmosIQ keeps tuning retrieval to how your team asks.
Why on-premise matters here
Your scenario notes encode client situations and your competitive knowledge of the lender market. Both stay in the brokerage.
Common questions
Are policy answers current?
Can it hold our own scenario history?
Is this a lender comparison tool?
See Dominion answering from your own documents.
A demonstration takes 30 minutes, uses no client data, and comes with no obligation.
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