Every major shift in how software is built creates an opening for a new infrastructure layer. Cloud reshaped compute. Mobile reshaped the application backend. We believe AI will do the same. 

As AI agents become first-class participants in software development, we are seeing a new generation of infrastructure emerging to support both developers and the agents writing code alongside them. At Insight Partners, we’ve been closely tracking this shift for several years, investing in companies like E2B*, CrewAI*, Runware*, Fastino*, and Databricks*.

Databases and backends are an area we have followed closely since the early days of large language models. We have been looking for a platform that is easy enough for developers building AI applications today but designed for a future in which agents write more of the software, manage state, and run workflows autonomously. 

Traditional backends assume an experienced engineer will assemble the stack and know where to add transactions, retries, cache invalidation, and synchronization. That assumption can become a liability when agents are writing more of the code. 

Convex was built for what comes next. 

A backend built for developers and agents

Convex brings the core components of a modern backend platform like database, server functions, real-time synchronization, workflows, search, and file storage into a single, unified TypeScript-native platform. 

Instead of stitching together separate databases, APIs, queues, and synchronization services, developers and agents can express application logic directly in TypeScript. That means less glue code, fewer architectural decisions, and fewer places to make a plausible but costly mistake. 

We view Convex’s reactive architecture as a good example of this. In a traditional stack, developers decide what data to fetch, when to refresh it, and how to keep every client in sync. Convex handles that automatically by tracking which queries depend on which data and pushing updates if and when that data changes. Mutations also run transactionally, helping applications remain consistent when multiple users or agents act at the same time. 

These properties matter in two ways: first, they make Convex a strong platform for coding agents. One language, strong types, automatic feedback, and fewer moving parts help agents produce applications that work beyond the initial demo. Convex extends that advantage with integrations for major coding agents that allow them to inspect real deployments, surface errors, and verify their work as they build. 

Second, Convex is well-suited to running agentic applications. Agents can read and write shared state, execute work concurrently, and use durable workflows that retry and resume after failures. 

What’s ahead

After following and using Convex for some time, including for a fair number of weekend projects, we had the opportunity to meet the team last year. 

Jamie Turner and James Cowling both came from Dropbox, where Jamie led storage and database engineering and James helped build its multi-exabyte, geo-distributed storage infrastructure. They brought that experience to a problem that is easy to underestimate: removing backend complexity without giving up correctness. 

We came away convinced that the depth of the team matched the ambition of the product. 

Convex has spent years building the underlying database and sync engine while fostering a passionate developer community. That work is now showing up in adoption, with more than 21,000 GitHub stars, nearly 500,000 developers, 2 million applications built, and over 1.2 million weekly npm downloads. 

We believe Convex can become a foundational backend layer for a world in which software is increasingly built by developers and agents working together. 

We are thrilled to lead Convex’s Series B and to partner with Jamie, James, and the entire Convex team as they make reliable backend architecture the default for developers and agents alike. 

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*Editor’s note: Insight Partners has invested in Convex, E2B, CrewAI, Runware, Fastino, and Databricks.