Durable workflow orchestration for modern applications — step functions, background jobs, and event-driven pipelines that are observable and recoverable by default. Built for the AI-native application era.
Companies we've backed
Eight investments from 2022 through 2024 across the enterprise AI infrastructure stack.
All Portfolio Companies
Fund I & Fund II
A headless, framework-agnostic rich-text editor built on ProseMirror. Powers collaborative editing and AI-generated content surfaces in B2B SaaS products. Developer primitive, not an app.
Embedded analytics and reporting infrastructure for B2B SaaS teams. Lets product teams ship data-dense dashboards directly into their product without maintaining a separate BI stack.
A compliance and policy enforcement layer for enterprise AI deployments. Intercepts LLM inputs and outputs to enforce data-handling rules, prevent leakage, and produce audit trails for regulated industries.
Change-data-capture and streaming infrastructure for Postgres. Captures every database mutation and routes it to downstream consumers — queues, search indexes, AI pipelines — without polling or custom triggers.
A platform for authoring, sharing, and running codemods at scale. Automates framework upgrades, API migrations, and large-scale refactors across enterprise codebases — saving engineering weeks per migration cycle.
AI-native workflow automation purpose-built for finance operations teams — AP/AR, close processes, variance analysis. Replaces spreadsheet-and-email workflows with durable, auditable, AI-assisted execution pipelines.
An AI gateway and observability platform sitting between application code and LLM providers. Routes requests, enforces policies, logs every call with semantic context, and provides cost and quality analytics across models and providers.
This list represents investments made through Ridgepoint Fund I and Fund II. Past performance is not indicative of future results.
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