Emissions & climate risk, quantified

Every portfolio has a tail. We find it.

SkewRisk builds AI agents that measure greenhouse gas emissions and physical climate risk — wildfire, flood, heat — property by property, then recommend what to do about both.

the asset carrying the risk

Most assets sit in the body. The exposure hides in the tail.

What it does

Three agents, one report.

You hand SkewRisk your portfolio data. A pipeline of specialized AI agents cleans it, measures it, and tells you where the risk actually lives.

Agent 01

Validate

Before anything is calculated, a data agent flags what it doesn't trust — missing units, anomalies, undocumented assumptions. A confident wrong number is worse than no number.

Agent 02

Quantify emissions

Scope 1 and 2 emissions computed with localized grid factors, by property, with every assumption documented for disclosure and third-party verification.

Agent 03

Score the risk

Property-level wildfire, flood, and heat exposure from public hazard data — ranked across the portfolio to surface the assets quietly carrying the most risk.

How it works

From a messy spreadsheet to a decision.

An agentic pipeline, not an LLM bolted onto a dashboard. Each step hands clean, checked work to the next.

Step 1

Ingest

Upload property data in whatever shape it arrives — utility figures, addresses, fuel use.

Step 2

Clean & check

The validation agent resolves gaps and flags what needs a human eye.

Step 3

Compute

Emissions and address-level climate risk scored against authoritative public data.

Step 4

Report

A structured, citable report — emissions, tail-risk ranking, and recommended actions.

Under the hood. A multi-agent system orchestrated with LangGraph and Claude, drawing on public emissions and hazard datasets. Built to make expert judgment about where data breaks down repeatable — and the output reliable enough to act on.
Multi-agent / LangGraph Claude eGRID factors FEMA & NOAA hazard data GHG Protocol · TCFD-aligned
The output

A report, not a dashboard to manage.

Something you can hand to a board, an auditor, or an investment committee.

Portfolio emissions summary
Portfolio emissions, broken down by scope and property.
Portfolio Risk Table
Address-level wildfire, flood, and heat scores with a tail-risk ranking.
Portfolio Recommendation
Prioritized actions to cut emissions and reduce exposure.
Who it's for

Built for the people who own the answer.

Real estate & REIT portfolios facing emissions disclosure and rising physical risk across many properties.

Sustainability & ESG teams who need forward-looking numbers, not just last year's report.

Asset & risk managers who need to know which holdings carry concentrated climate exposure.

Teams preparing for disclosure under frameworks like SB‑253, TCFD, and similar regimes.

Behind SkewRisk

Domain depth meets hands-on AI.

SkewRisk is built by Vahid Shabro, PhD — a product leader with fifteen years across energy, emissions, and climate. He built ComboCarbon at ComboCurve from inception, led GHG and climate-risk strategy at bp, and has spent his recent work hands-on in agentic AI.

The conviction behind SkewRisk is simple: in emissions and risk work, the calculation was never the hard part. The hard part is knowing when the data is wrong, and turning that judgment into something a team can trust at scale. That's what the agents are for.

Get in touch

See it on your portfolio.

Walk through a sample analysis, or talk through whether SkewRisk fits your data.

vahid@skewrisk.com