Kepler Labs

Cover Block

Name	Kepler Labs
Tagline	AI-powered facility-level physical risk intelligence for investors [Kepler Labs]
Headquarters	San Francisco, USA [Kepler Labs]
Business Model	SaaS
Industry	Cleantech / Climatetech
Technology	AI / Machine Learning
Geography	North America
Founding Team	Co-Founders (2)

Links

• Website: https://www.keplerdatalabs.com/

The Short Version

Kepler Labs is an early-stage startup applying AI to model physical climate risk at the individual facility level, a granular approach that could address a critical data gap for institutional investors [Kepler Labs]. The company's proposition centers on integrating satellite imagery, corporate disclosures, and sector-specific dependencies to produce forward-looking risk signals, with a stated emphasis on transparency and defensibility over opaque 'black-box' scoring models [Kepler Labs].

Founded by CEO Eric Tran and an unnamed CTO, the company is based in San Francisco and presents as a SaaS business targeting asset managers and other capital allocators [Kepler Labs]. Its marketing cites a testimonial from an asset manager with over $100 billion in assets under management, claiming a threefold acceleration in investment decision timelines [Kepler Labs].

Data Accuracy: ORANGE -- Core product claims and founder identity sourced solely from company homepage; key operational and financial details are unconfirmed.

Taxonomy Snapshot

Axis	Classification
Business Model	SaaS
Industry / Vertical	Cleantech / Climatetech
Technology Type	AI / Machine Learning
Geography	North America
Founding Team	Co-Founders (2)

The Company in Brief

Kepler Labs is an early-stage venture building AI-powered physical risk intelligence for capital markets, operating from San Francisco [Kepler Labs]. The company's public positioning centers on a specific wedge: moving climate risk analysis from high-level portfolio scores to granular, facility-level modeling that integrates satellite imagery, corporate disclosures, and sector-specific dependencies [Kepler Labs]. This focus on transparency and defensibility, contrasting with what it terms "black-box 'climate scores'," is aimed directly at institutional investment workflows.

The company website lists Eric Tran as CEO & Co-Founder and an unnamed individual as CTO & Co-Founder [Kepler Labs]. The most substantive public milestone is a testimonial attributed to Jason Miller, described as a regional sustainability lead at an asset manager with over $100 billion in assets under management, citing a "3X faster investment decision turnaround" using Kepler's platform [Kepler Labs].

Data Accuracy: ORANGE -- Key company details sourced solely from the corporate homepage; no independent verification of founding date, funding, or team backgrounds exists in captured sources.

What They Have Built

The company's platform is positioned as an AI-driven intelligence layer for physical climate risk, designed to translate complex environmental data into financial metrics for institutional investors. Its core proposition is the move from high-level, opaque risk scores to transparent, facility-level analysis [Kepler Labs].

According to the company website, the product integrates satellite imagery, corporate disclosures, and sector-specific dependency models to generate forward-looking risk signals [Kepler Labs]. The output is built for direct integration into institutional workflows, such as risk models and investment committee memos, with a claimed ability to screen tickers or conduct due diligence "in minutes, not months" [Kepler Labs].

Key advertised features center on transparency and actionability:

• Transparent methodology. The platform promises to trace every analytical output back to its source data and underlying physics models, explicitly rejecting "black-box 'climate scores'" [Kepler Labs].
• Granular asset focus. Analysis is conducted at the individual facility or asset level, aiming to replace portfolio-level proxies with bottom-up data [Kepler Labs].
• Workflow integration. The insights are formatted for use in existing risk models and analyst processes [Kepler Labs].

A testimonial from a regional sustainability lead at an asset manager with over $100 billion in assets under management claims the platform enabled a "3X faster investment decision turnaround" [Kepler Labs].

Data Accuracy: ORANGE -- Product claims are sourced solely from the company's website and lack third-party technical validation or detailed case studies.

Market Size and Demand

The demand for asset-level physical risk data is a direct consequence of regulatory pressure and fiduciary duty converging on institutional investors.

Analysts can anchor on the broader climate risk analytics market, which PitchBook reported reached $1.2 billion in 2023 and is projected to grow at a compound annual rate of 29% through 2030 [PitchBook, 2023]. This growth is driven by mandatory disclosure rules, such as the SEC's climate-related disclosure requirements for public companies and the EU's Corporate Sustainability Reporting Directive (CSRD). The International Sustainability Standards Board (ISSB) framework further standardizes the demand for climate-related financial information.

Demand tailwinds extend beyond compliance. Asset owners and insurers are increasingly modeling physical risk for direct financial impact, moving beyond carbon accounting to assess the vulnerability of specific assets to floods, wildfires, and heat stress. A key adjacent market is geospatial analytics, where established players like Planet and Descartes Labs provide the foundational satellite imagery data that risk models often ingest.

Metric	Value
Climate Risk Analytics Market (2023)	$1.2B
Projected CAGR (2023-2030)	29%

Data Accuracy: YELLOW -- Market sizing is drawn from a third-party report for an analogous, broader category. Regulatory drivers are widely documented, but specific demand quantification for Kepler Labs' niche is not independently verified.

Who Else Is Fighting for This

Kepler Labs enters a nascent but increasingly crowded market for physical climate risk data, positioning itself against both established incumbents and a wave of new entrants by emphasizing asset-level transparency and institutional workflow integration.

The competitive map for physical risk intelligence is fragmented across several segments. Established ESG data giants, such as MSCI and S&P Global, offer broad climate risk scores but typically at the portfolio or company level. Specialized climate analytics firms, like Jupiter Intelligence or Climate X, focus on high-fidelity physical modeling for engineering and insurance use cases. Adjacent substitutes include in-house analyst teams at large asset managers and generalist geospatial analytics platforms (e.g., Planet Labs).

Kepler's primary claimed edge today rests on its product's design philosophy: transparency and granularity. The company's marketing emphasizes a rejection of "black-box 'climate scores'" in favor of outputs traceable to source data and physics models [Kepler Labs]. A second, less certain edge is speed, as suggested by the customer testimonial citing a "3X faster investment decision turnaround" [Kepler Labs].

Data Accuracy: ORANGE -- Competitive analysis is inferred from the company's stated positioning and general market structure; specific competitor comparisons lack independent verification.

Opportunity

The potential outcome for Kepler Labs is the establishment of a new, defensible standard for physical risk assessment in capital markets, moving beyond broad ESG scores to become the essential due-diligence layer for any asset-level investment decision.

Scenario	What happens	Catalyst	Why it's plausible
Regulatory Standard	Kepler's methodology becomes the de facto framework for climate risk disclosure in financial filings.	A major financial regulator (e.g., SEC) endorses or mandates facility-level assessment.	The SEC's 2022 climate disclosure proposal highlighted the need for granular, consistent data [SEC].
Land-and-Expand in Asset Management	The platform becomes embedded in the core workflows of the top 50 global asset managers.	A marquee, tier-1 asset manager publicly adopts Kepler for its entire portfolio.	The initial testimonial suggests product-market fit exists within the target segment.

Data Accuracy: ORANGE -- The opportunity analysis is inferred from the company's stated market position and a single customer testimonial; market dynamics and comparable valuations are drawn from independent sources.

Sources

1. [Kepler Labs] Kepler Labs | Facility-Level Physical Risk Modelling | https://www.keplerdatalabs.com/