Ridgeline is now a due diligence engine

If you acquire wind assets, you know the drill. LOI signed, exclusivity clock ticking, your team scrambling to assess dozens of turbines before time runs out. Component histories, risk scores, O&M projections, the IC deck. All under pressure.

Ridgeline has handled this workflow since day one. But it required a human at a keyboard, clicking through each step. Over the last several weeks, we shipped the infrastructure to remove that bottleneck. Ridgeline is now an engine you integrate with, not a platform you log into.

Here's what changed and why it matters if you're screening wind deals at volume.

API layer

Seven REST endpoints now expose the full DD workflow. Partners create campaigns, submit assessment data, trigger scoring, generate reports, and promote results to operational data. No UI required.

Auth via API keys. Rate limiting. Webhook callbacks for async scoring. OpenAPI 3.1.0 spec for integration docs, versioned at v1.

What does that look like in practice? A partner like K2 Management calls our API from their deal pipeline tool. No browser tabs, no re-keying data from one system to another.

Scoring that you can defend in committee

A single risk number doesn't cut it for an investment committee. They want the reasoning.

The scoring waterfall now breaks out each component's contribution to the overall risk score. Gearbox, blades, generator, main bearing. Sensitivity analysis is built in: "If gearbox condition improves by one point, the overall score moves by X." Weights are configurable per customer.

We've watched too many deals stall because the IC couldn't see behind the number. This fixes that.

Batch screening

Repeat acquirers screen dozens of targets before committing evaluator time. That volume is now handled programmatically.

Submit 30 wind assets in one pass via CSV or JSON. The pipeline dashboard ranks them by risk score with comparative views against fleet averages and prior deals. Your evaluators spend time on the top five, not all thirty.

Partner workspaces

Partners aren't going to send their clients through our login page. They need their own front door, and now they have one.

Each partner gets an isolated workspace with role-based access. Evaluators run the full DD workflow, reviewers read and comment, clients see results. Partner branding on reports. API keys scoped per workspace. This is the piece that lets DD partners like DNV white-label Ridgeline inside their own client engagements.

Reports

Three output formats, all generated from structured data:

• Executive one-pager: risk score, GO/NO-GO, key findings, capex reserve estimate. One page for the IC.
• Full DD summary: component-level assessments, scoring waterfall, risk register, data quality scores.
• Detailed component export: raw assessment data in Excel/CSV for technical teams.

How a deal actually flows through

The whole sequence runs without a browser:

1. Partner calls the API with deal parameters. The engine creates a campaign and selects a turbine template from our library of 29 OEM types covering roughly 80% of the US operating fleet.
2. Partner submits component-level assessment data.
3. Partner triggers scoring. The engine runs the waterfall, returns a GO/NO-GO with a full risk breakdown, and fires a webhook when done.
4. Partner pulls a formatted report. PDF, HTML, or Excel.
5. If the deal closes, campaign data promotes to master operational data, cutting the re-keying cost that typically runs $15K–$40K per year.

Who should care

PE firms, infrastructure funds, IPPs, and DD partners who evaluate 20 to 50 wind targets per year. If your team spends more time assembling spreadsheets than analyzing risk, this was built for your workflow.

What we're doing next

We're running our first partner pilot right now: one real deal, through the API, end to end. Once we have 20 or more completed campaigns flowing through the engine, we turn on the historical benchmarking pipeline. Actual vs. predicted remaining useful life, regional failure rate patterns, vintage-specific risk profiles. The data compounds. Every deal that runs through Ridgeline makes the next assessment sharper.