Load a wholesale rate sheet
The analytical tools below all read from a Redis-cached rate sheet session. Load one once — every question in the catalogue reuses it for instant answers (no re-fetch).
These questions require cross-lender curve data, par rate comparison, and real-time session context. No LOS, PPE, or rate aggregator answers all of them simultaneously for a live scenario.
get_wholesale_rate_sheetStep 1Loads the full rate ladder for a location/scenario into Redis and returns a session_id. Run this first — every other LO tool reads from the cached session.
get_rate_session_statusInventory of every scenario loaded in a session — slugs, lender counts, available term types, TTL. Useful for confirming what's available before running an analysis.
query_rate_lender_rankingReturns lenders ranked by par rate for a given loan type + term (e.g. conforming_30yr). Powered by a pre-built Redis sorted set — O(log n) read.
query_rate_buydown_breakevenCalculates the breakeven months/years between two rates on a specific lender × product. Two O(1) HGET calls + app-layer amortization math.
query_rate_curveFull buydown/buyup pricing grid for a lender's product — every rate/points/payment combination. Use to inspect curve shape and find par for a lender.
compare_rate_scenariosSide-by-side comparison of 2–5 rate sheet scenarios loaded in the same session. Picks the best-overall scenario across multiple metrics.
query_rate_pricing_anomaliesInspect pre-computed anomaly flags for one lender × product — curve inversions, flat zones, APR spikes, dominance, par displacement. Zero-latency read.
query_rate_dominated_lendersSession-wide anomaly index ranked by severity. The right starting point for a rate-sheet quality audit — drill into any flagged lender with the anomalies tool.
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The AI chat will route to the right tool, call it on your loaded session, and explain the result in plain English. No tool name memorization required.