Private Equity Suite
Nine productized services across the PE deal cycle — pre-deal diligence, hold-period intelligence, exit and LP reporting. The flagship is technical diligence the way an engineering shop does it.
The PE deal cycle is the most legible structural narrative in capital allocation — source, diligence, close, hold, exit, report. Most PE-services firms cover one phase well and the others adequately. We build across the cycle because the data infrastructure each phase needs reuses what the prior phase produced.
The flagship is the one most firms can't credibly offer: technical due diligence on the code itself, the way an engineering shop would do it. Other DD shops can read financial statements; few can read a codebase and tell you what shipping that codebase on day 30 of ownership actually looks like.
Across the three tiers, the bar is what production work always demands — point-in-time correctness, idempotent ingestion, observability at every boundary. None of these are differentiators; they're the ante.
Pre-deal
Sourcing and diligence. Where speed and signal-quality compound — the deal team finds more targets and de-risks each one faster.
- I·01Flagship
Technical Due Diligence Engine
A code- and architecture-level diligence report — red/yellow/green risk heatmap across modules, dependency analysis, test-coverage and CI/CD posture, security vulnerability surface, and the operating-partner-readable summary of what the next twelve months of platform work will cost.
1–3 week sprint per target · packaged report - I·02
Deal-Sourcing Engine
A scoring pipeline that ingests structured (PitchBook-class) and unstructured (news, hiring, patents, alt-data) sources, applies your fund's thesis-specific filters, and ranks candidate targets — feeding your CRM with the top tier weekly.
6–10 week build · ongoing data ops - I·03
Diligence Red-Flag Engine
An AI-extraction-and-review layer that ingests the data room, surfaces the anomalies and the off-market clauses, benchmarks against comparable transactions, and screens beneficial ownership against sanctions and PEP lists — delivered as a risk heatmap the deal team works against.
1–2 week sprint per target · risk heatmap report
Hold
Portfolio intelligence and value creation. Operating partners see across the book, forecast each portco, and act on the pricing and margin levers that move the next print.
- II·01
Portfolio Intelligence Platform
A unified portfolio platform: ETL pipelines from each portco system (Excel, QuickBooks, NetSuite, Sage, Stripe) plus third-party data (Preqin, Bloomberg), normalized to a single schema, exposed through cross-portco dashboards with covenant tracking and liquidity alerts.
12–20 week build · ongoing data ops - II·02
Portfolio Forecasting Engine
Predictive forecasting models per portco — quarterly cash-flow and EBITDA projections trained on the portco's internal financials and sector-comparable data, with structured scenario planning (cost-cut sensitivity, price-elasticity scenarios, demand-shock testing) that feeds straight into the fund's valuation model.
8–12 week build · quarterly model refresh - II·03
Post-Acquisition Integration Tracker
An NLP and ML layer that reads the recurring integration artifacts — board decks, weekly status reports, ops dashboards, strategy memos — extracts integration-milestone status, predicts timeline slippage, and surfaces missed synergies before board prep makes them visible.
6–10 week build · ongoing per integration - II·04
Pricing & Margin Optimizer
An ML layer on the portco's product, customer, and channel data — estimates price-elasticity per segment, identifies the margin levers worth pulling, simulates the impact of pricing and packaging changes before they ship.
8–14 week build per portco · ongoing iteration
Exit + LP
Exit-prep automation and LP-facing reporting. The unglamorous half of the cycle, automated.
- III·01
Exit-Prep Automation
An exit-prep package — automated data room construction from the portco's existing systems, investor-deck assembly with portco metrics auto-populated, comparable-transaction analysis against current-market multiples, buyer-pool intelligence for the strategic and financial pools.
4–8 week sprint per exit · ongoing data room maintenance - III·02
LP Reporting Engine
An automated reporting pipeline — calculates IRR / MOIC / DPI / TVPI per vehicle, generates per-LP report PDFs in each LP's preferred format, populates LP portals via API where available, produces ILPA-template-compliant ESG reports, and exports K-1 / 1099 XML for the year-end tax cycle.
10–16 week build · ongoing reporting cycle
How a private equity suite engagement runs.
Each product has its own engagement shape — typical length, what you get, who staffs it. Across the suite, the constants are the same.
- Lead
- Bogdan
- Cadence
- Async-first
- Engagement
- Per product
- Bar
- Production
Principal engineer. Most architecture and most code ships through one keyboard.
Weekly check-ins, written updates between, calls when the decision needs the room.
Shapes listed on each product page — typically multi-week builds with ongoing operation.
Async correctness, capacity under burst, observability at every boundary.
If this fits the operation, the next step is one call.
We'll talk scope and fit. If we're not the right fit, you'll know fast.
Bogdan and team · async-first · OP—2026