DeVaris Brown
Cofounder
Cofounder and CEO of Meroxa, the real-time data infrastructure company. Previously a product leader at Twitter, Heroku, VSCO, and Zendesk. Angel investor and advisor to dozens of startups.
Venture studio · Multi-strategy fund
A venture studio and multi-strategy fund from DeVaris Brown and Van Jones. We start companies, back founders, and buy businesses where AI permanently changes the economics.
01 / Partners
Why Third Letter. DeVaris and LaVandez. The third letter of each name is a capital V.
Cofounder
Cofounder and CEO of Meroxa, the real-time data infrastructure company. Previously a product leader at Twitter, Heroku, VSCO, and Zendesk. Angel investor and advisor to dozens of startups.
Cofounder
Venture investor. Deal Lead at Wellington Access Ventures, the early-stage platform of Wellington Management, and previously a Partner at Drive Capital focused on enterprise SaaS and data infrastructure. Cofounded Hello Tractor, an agricultural equipment platform operating across Africa. Chicago Booth MBA.
02 / Thesis
Origination
Both partners build in public. Deal flow comes from founders, operators, and communities we already work alongside.
Structure
Studio, venture, control buyout, or public equity. Whichever fits the company.
Duration
We underwrite to decades, hold through cycles, and measure ourselves on what survives.
03 / Model
The studio builds the tooling. Venture backs the companies using it. Private equity applies it to businesses that already make money. Public markets capture the re-rating.
We build from problems we have lived as operators, supply the first team, and hold founding equity. Kno is the first.
We back founders where a technical wedge can compound into a durable moat, and bring operating experience to the table.
Services and software companies whose operating core can be rebuilt with the studio’s tooling. Value comes from margin, not multiple.
Incumbents where AI adoption changes unit economics before it changes the multiple.
Know which data actually makes your AI better.
Open-source agent data evaluation. Kno measures which documents, examples, policies, and conversations improve an AI agent, and by how much, then ranks each by impact and cost.
| Asset | Impact | Decision |
|---|---|---|
| new_refund_policy.md | +18% | keep → knowledge_base |
| example_42.json | +7% | keep → context |
| example_91.json | +1% | reject |
| old_refund_policy.md | −9% | reject → harmful |