Our portcos already do their own forecasts. What's the value-add?

Portco finance teams are great at the operating-detail layer; the platform sits on top with consistency. Same forecasting methodology applied across the portfolio means the valuation team isn't reconciling five different sets of assumptions when they roll up. And the scenario layer (cost-cut sensitivity, price-elasticity, demand shock) is what most portcos can't staff for.

What data does the model need?

Three years of monthly portco financials (P&L line-item depth, balance sheet, cash flow), the portco's customer-cohort or revenue-segment breakdown if relevant, and access to sector-comparable benchmarks (we provide the comparables layer). Where the portco has thinner history, we use sector-anchored priors with documented uncertainty.

How accurate are the forecasts?

On stable mid-market portcos with three-plus years of history, the model's 90-day forecast typically tracks within 5–8% on EBITDA. On earlier-stage or post-acquisition-integration portcos, the band widens; we surface the uncertainty rather than hiding it. The valuation team consumes the forecast WITH the uncertainty band.

Does this replace the portco CFO's planning process?

No. It runs in parallel — the portco CFO has the operating context, the engine has the cross-portfolio consistency and the scenario layer. Where they disagree, the disagreement itself is the useful artifact.

Per-portco for build, ongoing for quarterly refresh. Discovery call covers the portco set.

§ Product

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.

Engagement: 8–12 week build · quarterly model refresh
Built for: Operating partners · Portco CFOs · Valuation teams

Book a 30-minute call →See the suite

§ Problem

Portco forecasts are spreadsheet-built, partner-adjusted, and rolled up to fund valuation through inconsistent assumptions. The result is a fund valuation that everyone trusts at a one-line summary level and no one trusts under the hood.

What this is

A forecasting layer for the fund's portfolio — replacing five inconsistent spreadsheet methodologies with one consistent model methodology applied per portco. Three components:

Forecast models. Time-series + driver-tree hybrid per portco, trained on internal financials and sector-comparable data. Quarterly cadence; monthly-grain output where the underlying data supports it.
Scenario layer. Structured what-ifs: cost-cut sensitivity, price-elasticity scenarios, demand-shock testing, FX scenarios for portcos with material non-domestic exposure. Feeds fund-level valuation models without manual re-modeling.
Uncertainty surfacing. Forecasts come with documented confidence bands. The valuation team consumes the forecast with the uncertainty, not as a point estimate.

How it's built

Statsmodels and PyMC for the time-series + Bayesian layers, LightGBM for non-linear driver modeling. Sector-comparable data sourced from your existing data infrastructure plus the public-comparables layer we maintain. Output served through the Portfolio Intelligence Platform if that's already in place, or as a standalone deliverable.

What you get

Forecast models per portco, with documented assumptions and uncertainty bands.
The scenario library, configured to the fund's standard sensitivity set.
Quarterly refresh — the model retrained, the scenario library updated, the valuation hand-off packaged.
A methodology document the valuation team can stand behind when LPs ask how forecasts are built.

§ How we engage

Engagement is shape, not list.

Length and price are functions of the data and the destination. The shape below is the typical engagement.

Length: 8–12 week build · quarterly model refresh
Lead: Bogdan
Cadence: Async, weekly
Bar: Production

§ Related

Products this composes with.

Same suite, or vertical-specialized versions in another.

§ Questions

What buyers ask about this one.

Our portcos already do their own forecasts. What's the value-add?
Portco finance teams are great at the operating-detail layer; the platform sits on top with consistency. Same forecasting methodology applied across the portfolio means the valuation team isn't reconciling five different sets of assumptions when they roll up. And the scenario layer (cost-cut sensitivity, price-elasticity, demand shock) is what most portcos can't staff for.
What data does the model need?
Three years of monthly portco financials (P&L line-item depth, balance sheet, cash flow), the portco's customer-cohort or revenue-segment breakdown if relevant, and access to sector-comparable benchmarks (we provide the comparables layer). Where the portco has thinner history, we use sector-anchored priors with documented uncertainty.
How accurate are the forecasts?
On stable mid-market portcos with three-plus years of history, the model's 90-day forecast typically tracks within 5–8% on EBITDA. On earlier-stage or post-acquisition-integration portcos, the band widens; we surface the uncertainty rather than hiding it. The valuation team consumes the forecast WITH the uncertainty band.
Does this replace the portco CFO's planning process?
No. It runs in parallel — the portco CFO has the operating context, the engine has the cross-portfolio consistency and the scenario layer. Where they disagree, the disagreement itself is the useful artifact.
Pricing?
Per-portco for build, ongoing for quarterly refresh. Discovery call covers the portco set.

§ The next step

If the deliverable matches the gap, the next step is one call.

We'll scope length and price against your data and the operation it integrates with. No retainer, no fishing.

Book a 30-minute call →← Back to Private Equity Suite

Bogdan and team · async-first · OP—2026