The numbers below are scoping targets, stated as assumptions - not observed results. Every engagement starts by measuring your actual baseline. Private Equity firms deploying this system typically target a 25-35% reduction in due diligence timelines by eliminating manual target company data entry and accelerating document flow from Intralinks to investment committee summaries. Deal sourcing is scoped to surface materially more qualified opportunities because relationship managers reclaim 8-10 hours weekly for prospect outreach instead of CRM data entry - hours that convert directly into origination velocity. LP reporting cycles are targeted to compress by 40% as portfolio performance data flows automatically from Carta and proprietary dashboards into investor communication templates, cutting the weeks-long aggregation burden that delays capital calls and performance updates.
The gains compound over 12 months as the system learns from your deal outcomes - the design curve takes extraction accuracy from roughly 85% at launch into the mid-nineties. The working assumption is that by month six, a 10-person sales team is recovering 350+ hours a month at full run-rate - the direct product of the 8-10 hours reclaimed per associate per week stated above - that shift to prospect meetings and add-on acquisition identification. By month twelve, a deployment like this targets a 15-25% improvement in qualified pipeline conversion, and LP reporting automation becomes a talking point in fundraising conversations. The thesis behind the whole model: faster deal cycles reduce dry powder drag, and dry powder drag is the quiet tax on fund performance. Check each assumption against your own pipeline data before you underwrite any of it.