The Problem

Regenerative agriculture is growing faster than the infrastructure around it. New certifying bodies, investment vehicles, technology platforms, and consumer brands are entering the space each year, but the ecosystem remains deeply fragmented, poorly indexed, and difficult to navigate even for organizations working inside it. There is no authoritative directory. There is no shared map.

For organizations trying to build partnerships, deploy capital, or develop supply chains in this space, that opacity has real costs. Outreach is duplicative. Relationships are formed by proximity and chance rather than strategic fit. Opportunities for collaboration go unrealized because the relevant actors simply don’t know each other exists.

This project began with a straightforward premise: before you can build the ecosystem, you have to be able to see it.

What I Built

Over the course of my work at Why Regenerative, I developed a structured landscape database of more than 3,000 organizations operating in or adjacent to the regenerative agriculture ecosystem in the United States. The database spans four sectors: farms and producers (2,459), investors and funders (151), brands and buyers (231), and technology companies (75).

Each record was researched and enriched manually, with organization descriptions, web links, geographic data, product categories, certification status, fundraising stage, and fund type where applicable. The goal was not just a list, but a usable intelligence asset: something that could support outreach prioritization, partnership identification, event programming, and strategic planning.

Methodology

This landscape map was built using two primary sourcing approaches, each suited to a different segment of the ecosystem.

For farms and brands, I drew directly from the registries of active certifying organizations, including Regenerative Organic Certified (ROC), Regenified, the American Grassfed Association, Savory’s Ecological Outcome Verification program, and the Real Organic Project. Registry-based sourcing produces high-confidence records within a defined scope. This method captures the certified universe comprehensively, but says nothing about the much larger population of farms operating regeneratively without formal verification.

To reach that broader population, as well as investors and technology companies, I used LinkedIn keyword search filtered by organization type. Searching “regenerative agriculture” and restricting results to farms, financial institutions, and technology companies respectively produced a large initial universe that I then reviewed and enriched manually.

This approach has real coverage limitations worth naming. LinkedIn search systematically underrepresents smaller operations, rural producers, and organizations that don’t maintain an active digital presence. It captures self-identification with the regenerative label, not verified practice, meaning some organizations in the database use the language without the underlying methodology, and others doing substantive work may not use the term at all. Investor coverage is similarly incomplete: family offices, foundations, and funds active in the space but not self-describing as “regenerative agriculture” investors are likely underrepresented.

These limitations don’t undermine the map. They define its scope. What this database captures well is the organized, visible layer of the regenerative agriculture ecosystem. What it does not yet capture are the informal relationships between these actors, the uncredentialed farms that may represent the majority of regenerative production in practice, and the conventional capital beginning to move toward this space without yet adopting its language.

One methodological choice is worth making explicit. The database intentionally includes organizations that use “regenerative” language without holding a formal certification because restricting the map to certified actors only would produce a cleaner but less honest picture of the ecosystem. The self-identified regenerative universe is the relevant one for understanding how the term is actually functioning in the market, including at its contested edges. That inclusivity is not an endorsement of every claim in the database. It is a recognition that mapping the full landscape, certified and uncertified alike, is a prerequisite for understanding where the definitional boundaries are, how they are being drawn, and by whom.

What the Data Shows

Five findings stand out from the landscape data.

The ecosystem is vast but largely uncredentialed. Only 11.5% of mapped farms hold a recognized certification. The remaining 88.5% operate without third-party verification, a structural gap that limits access to premium markets, carbon programs, and mission-aligned capital. This figure likely understates the true scale of the uncredentialed universe, given that certified farms are better represented in the sourcing methodology.

Regenerative agriculture, in practice, is predominantly livestock. Beef appears in over 61% of farm product listings. When combined with chicken, pork, eggs, lamb, and dairy, animal products dominate the landscape. This reflects the historical alignment between holistic grazing and the regenerative label, and points to a relative underrepresentation of row crops, perennial systems, and plant-based production.

Production is distributed; capital is not. Farm activity is spread across the country, led by Texas, California, Pennsylvania, and New York. Investor headquarters cluster tightly in Colorado, New York, and California, a geographic mismatch between where regenerative production happens and where the capital to support it is based.

The capital stack has meaningful gaps. Venture and impact funds dominate the investor landscape at 47 and 37 organizations respectively. Credit and lending vehicles number just 11, a significant gap given that most farm-level transitions require patient debt, not equity. The infrastructure for financing the actual practice change on the ground remains thin.

Brand certification reflects a contested definition. ROC accounts for 61% of brand certifications, followed by Rainforest Alliance (20%) and Regenified (17%). These are philosophically distinct standards with different verification requirements and different theories of what regenerative agriculture demands. ROC integrates soil health, animal welfare, and worker equity as a unified standard; Rainforest Alliance emphasizes supply chain sustainability and biodiversity; Regenified focuses on measurable soil outcomes. Their co-presence under the same label is not incidental. As industry veteran Alan Lewis has documented, this is precisely the mechanism through which meaningful claims get diluted: when one term is used to mean many different things, the connection between claim and practice becomes harder for buyers, retailers, and consumers to verify. A landscape map that shows three distinct certification frameworks operating under a single marketing category is not just a taxonomic observation. It is a picture of a definitional contest that has real consequences for producers who have invested in rigorous standards and for consumers who are paying a premium on the assumption that those standards mean something.

The charts below are the same interactive views as the standalone data page: certification mix, geography, products, investors, brand standards, and technology stage.

Charts built from the landscape database. Scroll inside the frame to see all sections, or open full screen →

From Landscape to Network

What this database establishes is a roster, a structured, sourced account of who is operating in the regenerative agriculture ecosystem and in what capacity. That is not a small thing. In a space this fragmented, knowing who exists and how to categorize them is a prerequisite for almost everything else: partnership development, capital deployment, market building, policy advocacy. A landscape map is where serious ecosystem work begins.

But it is not where it ends.

The more valuable and more difficult layer of analysis is the network underneath the landscape, not just who the actors are, but how they are connected. Which certified farms have established buyer relationships, and which are producing into a market vacuum? Which investors are co-investing, and which are operating in isolation from the rest of the capital stack? Which technology companies have achieved integration with farm operations at scale, and which remain disconnected from the producers they’re designed to serve?

The map below illustrates what that network layer could look like: 30 illustrative organizations across six sectors, connected by the kinds of relationships the landscape database does not yet capture. Click any node to explore its connections.

Illustrative network map. Organization names and relationships are fictional representations of ecosystem actor types. Open full screen →

Network mapping in a fragmented ecosystem like this one is methodologically harder than landscape mapping. Relationships are not always public, not always stable, and not always legible from the outside. But the methods exist: co-appearance at industry events is a reliable proxy for professional proximity; co-investment data surfaces financial relationships between funds and companies; structured surveys of ecosystem participants can capture the informal referral and collaboration networks that don’t show up in any registry.

The reason this matters goes beyond academic interest. In a transition-stage ecosystem, network position determines outcomes. A farm that is well-connected to a certifying body, a mission-aligned buyer, and a patient lender is on a fundamentally different trajectory than an equally committed farm that has none of those relationships. Identifying which organizations sit at structural bridges, connecting otherwise isolated clusters, and which are doing important work in isolation is the kind of analysis that can actually direct resources, partnerships, and attention more effectively.

A network map would also make visible something that a landscape map cannot: the difference between certification and market integration. One of the structural concerns Lewis and others have raised about the proliferation of regenerative claims is that certification alone does not guarantee that a farm’s practices are actually connected to a market willing to reward them. A certified farm with no buyer relationship, no access to mission-aligned capital, and no connection to a retailer enforcing claim integrity is in a fundamentally different position than the label alone suggests. Network mapping is where that distinction becomes legible. Identifying which certified producers have downstream relationships with brands, retailers, and investors, and which are doing rigorous work in effective isolation, is the kind of analysis that could help direct resources, partnerships, and shelf space toward the claims that are most defensible, and away from the ones that are not.

This project is designed to evolve in that direction. The landscape database is the foundation. The network is the next layer. Continue to Part 2: What the Connections Reveal →