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Question parsing
Every incoming RFP or DDQ is read in full — questions extracted, classified, and mapped to the domains they touch, in minutes rather than hours.
Case study / Asset management
Every RFP answered, at your best.
An AI-native operating system for RFP and DDQ response in asset management — organization-wide digital twins, a governed answer library, and human-in-the-loop review that turn a headcount-limited bottleneck into a scalable operating advantage. Built on actual RFP processes and data, ready to deploy with customization to each customer's teams, strategies, and review rules.
The challenge
A mandate walks away every time you say no.
Capacity constraints force asset managers to decline a third to half of the RFP opportunities they receive — each one a potential nine-figure mandate.
Each response demands 20–40 hours across six or more teams — investment, compliance, operations, legal, risk, and client service. Yet 60–80% of the questions repeat across RFPs, and teams still redraft from scratch, because institutional knowledge lives scattered across documents and individuals.
The result is a growth ceiling set by headcount, inconsistent answers across strategies, and compliance exposure that grows with every submission.
The operating principle
Institutional knowledge, working on every response.
Loresse captures the judgment of each function's best people as persistent digital twins, then wraps the entire RFP and DDQ lifecycle in one governed workflow. Recurring questions are answered from a version-controlled library; novel questions route to the right expert with full context attached. Autonomy grows in phases — from full human validation, to autonomous handling of routine questions, to continuous operation with drift monitoring — always over an immutable audit trail.
The connected workflow
From questionnaire to submission.
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Content retrieval
The governed answer library surfaces the current, approved response for every recurring question — no more redrafting from scratch across scattered documents.
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Digital twin drafting
Seven functional digital twins — investment, compliance, operations, client service, legal, risk, and marketing — draft answers in each team's own voice and discipline.
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SME review
Subject-matter experts inspect and override every draft that needs their judgment, with the reasoning trail attached — their time goes to the novel questions, not the repeated ones.
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Compliance check
Automated checking verifies current disclosures, GIPS standards, and cross-strategy consistency before anything leaves the building.
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Submission & learning
Every AI recommendation, human edit, and final submission is recorded with full provenance — the library improves with each response, regardless of personnel changes.
Organization-wide coverage
Seven functional digital twins.
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Investment team
Portfolio philosophy, performance attribution, market outlook, buy/sell discipline
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Compliance
ADV disclosures, SEC/FINRA requirements, ESG reporting, proxy voting
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Operations
Trading infrastructure, NAV methodology, business continuity, cybersecurity frameworks
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Client service
Reporting capabilities, SLAs, fee schedules, onboarding procedures
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Legal
IMA provisions, side letters, ERISA compliance, GIPS standards
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Risk management
Stress testing, liquidity frameworks, concentration policies, drawdown analysis
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Marketing & IR
Firm narrative, competitive positioning, brand voice, consultant relationships
One governed answer library beneath them all.
Version-controlled, cross-strategy consistent, and audit-ready — knowledge that persists regardless of personnel changes.
The impact
Capacity, growth, and risk — moved together.
Targets grounded in the manual process this workflow replaces: an ~83% reduction in time per RFP — from 20–40 hours to 3–7 — expanding response capacity three to five times with the existing team, and recapturing thousands of analyst hours a year. More responses at higher quality means more mandates pursued and won.
On risk, the same system targets 70–80% fewer response inconsistencies, 60–70% fewer compliance exceptions, and a 50–65% reduction in institutional-knowledge risk — every figure sized against your own baseline during onboarding.
The solution is ready to deploy, customized to your teams, your strategies, and your review rules — proof in weeks, not quarters.