The primitives that enterprise AI
runs on haven't been built yet.

Ridgepoint backs Seed and Series A founders building the workflow, data, and AI infrastructure that enterprise software teams will depend on for the next decade.

Portfolio

The thesis in practice

Inngest
Event-Driven Workflow Orchestration
2022 Seed
Tiptap
Headless Rich-Text Editor Framework
2022 Seed
Nimbus Analytics
Embedded Analytics for B2B SaaS
2022 Seed
Goody-2
Enterprise AI Compliance Layer
2023 Seed
Sequin
Database Change-Data-Capture Platform
2023 Pre-Seed
Codemod.com
Automated Code Migration Tooling
2023 Seed
Meridian AI
AI Workflow Automation for Finance Teams
2024 Series A
Portkey.ai
AI Gateway and LLM Observability
2024 Seed

Investment Thesis

Operator conviction, not market consensus

Enterprise AI adoption is running years ahead of the infrastructure layer that supports it. Most teams deploying LLMs today are doing so on primitives that were never designed to run at enterprise scale — fragile orchestration, opaque data pipelines, compliance gaps that only surface in production.

We invest at the point where a primitive is becoming clear but the market hasn't yet validated it. That's the moment where founders with operational depth — who have felt the absence of the tool they're building — have the highest conviction and the lowest competition.

Ridgepoint's check is not a bet on the market. It's a bet on the founder's specific understanding of a specific missing layer.

Read our thesis

Investment principles

  1. Primitive not feature

    The best infrastructure companies are building the substrate, not the product that sits on top of it. If the thing you're building would make five other categories possible, that's the right level of the stack.

  2. Enterprise obsession from day one

    Enterprise requirements — audit trails, SSO, RBAC, observability — aren't something you retrofit at Series B. The founders who internalize them early build better products and win longer-cycle deals.

  3. Conviction before clarity

    We invest when the founding team's conviction is highest and the market signal is weakest. By the time the market is obvious, the check size required to lead is beyond our mandate.

The Team

Operators who became investors

Katherine Reeves
Managing Partner

Previously VP Product at a Series-C enterprise automation company. Left to angel-invest across developer-tooling and enterprise SaaS. Founded Ridgepoint in 2019.

Jordan Solis
General Partner

Six years growth equity covering software and applied AI. Former product engineer at a B2B analytics startup. Joined Ridgepoint in 2020; leads Series A and portfolio operations.

Priscilla Tran
Principal

Former engineer at a developer-tools open-source company. Transitioned to venture in 2022 via fellowship. Covers early diligence and founder engagement for Fund II.

Meet the team

Building something in enterprise AI infrastructure?  [email protected]

We typically respond within 5 business days.