What problem does it solve?
Deal-desk reviewers waste hours manually cross-referencing proposed non-standard deal terms against internal discount rubrics, comparable deal history, and escalation criteria, leading to slow counteroffers, inconsistent pricing decisions, and risk of unauthorized discounts or approval bypass.
Core Features & Use Cases
- Rubric-backed policy evaluation: Automatically cross-references every line of a proposed deal (discount %, term length, payment terms, ramp structure) against your team's custom discount rubric, citing exact policy sections for in-policy, exception-needed, or out-of-policy verdicts.
- Precedent-backed recommendations: Pulls 5-10 closest historical comparable deals by segment, ACV, term, and competitive context to surface evidence for counteroffers, avoiding rubber-stamp decisions from incomplete data.
- Mandatory human escalation guardrails: Automatically flags asks that exceed DOA limits, have thin analog evidence, touch uncovered policy dimensions, or come from AEs with excessive exception requests to route to the correct named approver, never auto-approving or auto-discounting.
- Use case: For a mid-market AE submitting a 22% discount ask on a 3-year $200k ACV deal, the skill returns a structured recommendation with a cited 18% counter, supporting comparable deal IDs, and an escalation flag if the ask exceeds stacked concession ceilings.
Quick Start
Provide the proposed deal record, file path to your team's discount rubric, and file path to your comparable deal history to the deal-desk-pricing skill to receive a structured, rubric-cited pricing recommendation for human review.
