ILLUSTRATIVE CASE STUDY · FOR EDUCATION

The DDQ Agent
a worked example.

Most investment-firm executives have heard the phrase "AI agent", far fewer have seen what one actually does, end-to-end, inside a real workflow. This page walks through a Due Diligence Questionnaire (DDQ) agent the way we would design and deploy it.

// THE SCENARIO

A familiar problem inside a mid-market fund

THE FIRM

A $1.2B mid-market PE manager. Lean IR team of two. Four active funds. Quarterly LP reporting plus a steady stream of inbound DDQs.

THE TRIGGER

A pension allocator sends a 180-question DDQ covering investment process, ESG, cybersecurity, valuations, and operational due diligence.

THE COST TODAY

Roughly 3 weeks of elapsed time. IR drafts, deal partners review, Compliance and IT chase down policies, GC signs off, and the answer library drifts further out of date.

// HOW THE AGENT WORKS

Five stages, one auditable pipeline

This is the same shape we would design for an RFP agent, a deal screening agent, or a research synthesis agent. Only the corpus and the reviewers change.

STAGE 01 / 05

Pull all your documents into one place

The agent reads everything you already have: past investor questionnaires, policies, fund performance, compliance manuals, IT and business continuity docs. It keeps track of where every fact came from and who is allowed to see what.

PPM
ADV
LPA
Prior DDQs
Compliance
IT
BCP
Performance
// WHAT CHANGES

Before vs. after, the realistic picture

Numbers below are illustrative ranges based on the structure of the work, not a published benchmark from a specific client.

TODAY

Manual DDQ workflow

  • 2–3 weeks elapsed per major LP DDQ
  • IR director and analyst absorbed for days
  • Deal partners pulled out of investing time
  • Answers drift; the same question gets two answers across funds
  • Audit trail lives in email threads
WITH A DDQ AGENT

Agent-assisted workflow

  • First reviewable draft in under an hour
  • Human reviewers spend time on judgment, not retrieval
  • Every answer cited to a versioned source document
  • House style and prior approved language enforced by default
  • Each completed DDQ strengthens the firm's answer library
// GUARDRAILS BY DESIGN

What we would not let an agent do

No autonomous send

The agent drafts and routes. A named human approves before anything leaves the firm.

No ungrounded answers

Every claim must trace to a source in the firm's corpus. If the corpus is silent, the agent flags rather than invents.

No cross-firm leakage

Private deployments, customer-managed keys, role-based access, and immutable audit logs aligned to SEC and FCA expectations.

// THE BROADER POINT

The same pattern unlocks a dozen workflows

Once a firm has a clean, governed corpus and a review-first agent pattern, the next workflow is mostly configuration, not a new project from zero.

RFP responses for separately managed accounts
Inbound CIM screening and first-pass deal memos
Earnings call and broker-note synthesis
Quarterly LP letter and portfolio commentary drafting
Side-letter obligation tracking and MFN reviews
Compliance attestation and policy Q&A
// INITIALIZE

See what this would look like inside your firm

We would rather have a 30-minute conversation about your actual DDQ cycle than show you another generic deck. No data, no NDAs needed for the first call.

Celer AI Architect
// SOLUTIONS ADVISORY
Hi, I'm Celer AI. Think of me as the Solutions Architect who actually read the data room. What workflow is eating your week?
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