For AI products, the bar is even higher: an agent needs to read data from a user's CRM for context, pull documents from Google Drive for retrieval, and write actions back to their tools on their behalf, all through an authorization layer that respects per-user permissions.

Most companies try to build this themselves. It goes fine for the first five or so integrations. By the time a team is maintaining ten, there's a full team doing nothing but integration work. By twenty, they're struggling with inconsistent error handling, fragile authentication flows, and a connector catalog that breaks every time a third-party API ships a change.

Paragon, based in Los Angeles, exists so engineering teams don't have to do any of that. The company provides the integration layer that sits between a product and its customers' tools. Developers drop in Paragon's SDK, and their users get an embedded connect portal where they authenticate their 3rd party integration accounts and configure how data flows. On the backend, Paragon handles the connectivity, authentication, data sync, rate limiting, retries, and error recovery. The platform includes hundreds of native integrations out of the box. For anything custom, a framework makes it straightforward to build, and thousands of custom connectors are now running in production across Paragon's customer base.

Companies like Zendesk, Postman, Pipedrive, Jasper, and CrewAI use Paragon to ship integrations to their own users. The company came out of Y Combinator and is backed by Inspired Capital, Global Founders Capital, and Village Global.

But the interesting question isn't what Paragon does. It's how a startup-sized engineering team keeps all of it running reliably while still shipping new product.

The part that doesn't get easier

Coding agents can generate a connector or integration. That part of the problem is increasingly commoditized. What doesn't get automated is everything around it: understanding how customers actually use each integration in production, deciding which edge cases to handle and which to surface, knowing when a third-party API change calls for a patch versus a new abstraction, and keeping all of those connectors consistent in how they behave across every customer's environment.

A connector to Salesforce isn't a file anyone writes once. Salesforce ships API changes, deprecates endpoints, adjusts rate limits, and modifies OAuth flows on its own schedule. Multiply that across hundreds of platforms and the maintenance surface area compounds. It takes monitoring, incident response, cross-service dependency awareness, and product judgment about what matters to the customer using the integration downstream.

Paragon decided early to treat this as an infrastructure and product problem rather than a staffing problem. The company invested in engineering process that most startups defer until they're five times the size.

Thirty-eight domains, each with a stability contract

The foundation is a technical ownership model covering thirty-eight domains across six engineering teams. Every domain, from the workflow engine to the data sync pipeline to individual frontend surfaces, has a named owner responsible for P0 incidents, architectural decisions, and a defined set of service-level indicators (SLI).

The SLIs are granular. Backend domains track endpoint latency at P50, P90, and P99. Teams measure error-free session rates through an APM tool, monitor CPU and memory utilization per service, and track logging costs quarter over quarter. Frontend owners carry web vitals: Largest Contentful Paint, Time to First Byte, Interaction to Next Paint, bundle size, and deployment time. All of it gets reviewed in twice-weekly stability meetings.

"The anti-pattern at most companies is treating stability as a side effect of feature work," said Anand Chaudhary, a principal engineer who began contracting with Paragon in 2019 when the company was five people and has since built much of its engineering process. "We made it a first-class function. Every domain has an owner, every owner has SLIs, and those SLIs show up in a standing review cadence."

The payoff is what Paragon's customers experience: integrations that just work. An AI company using Paragon to pull data from a user's Google Drive doesn't think about whether the connector handles token refresh correctly under concurrent load. Paragon's ownership model is why they don't have to.

Shipping HIPAA in ten weeks

Many of Paragon's customers sell into healthcare, and their buyers require HIPAA-compliant infrastructure all the way down the stack. An AI company building clinical workflow tools can't use an integration platform without its own HIPAA certification. Procurement and Security won't sign off.

Paragon shipped HIPAA in ten weeks, in parallel with ongoing feature development. Anand Chaudhary served as principal architect of the effort, coordinating three parallel workstreams, each with its own engineering spec and team lead.

They first introduced project-scoped access controls so that work on one customer's integration is fully isolated from another customer's protected health information. The second modernized the session architecture: short-lived access tokens on a tight window, refresh tokens on a few days rotation, and a cache layer that validates every request and supports immediate invalidation on logout, password change, or two-factor authentication events. The design also solved a concurrency problem where multiple browser tabs racing to refresh an expired token could create conflicts, using backend locking, frontend request coalescing, and cross-tab coordination via the BroadcastChannel API. The third track was audit logging for all PHI access.

"We designed compliance as native infrastructure," Chaudhary said. "The access controls, the session model, the audit layer. They're part of the platform, not a checkbox sitting next to it."

Paragon announced HIPAA certification on February 3, 2026, alongside a renewed SOC 2 Type II. For customers, it means any SaaS product or AI application running on Paragon can now offer HIPAA-compliant integrations without standing up its own compliance engineering team.

"HIPAA changes what our customers can bring to market. It gives healthcare AI and SaaS companies a path to offer integrations inside environments where compliance is non-negotiable, without having to build that infrastructure from scratch. More broadly, it helps move the industry toward a model where secure, compliant interoperability is expected, not exceptional."

- Ishmael Samuel, CTO, Paragon

What comes next

Paragon is now building AI development tooling into its own engineering workflow, wired into its codebase, product specs, and design files. In a recent internal demo, an engineer picked up a spec they hadn't seen, ran it through the system, and shipped a working feature (endpoints, migrations, UI, pull request) in under an hour. Features that previously took a full sprint are compressed when the AI has enough context about the codebase.

It's the same philosophy the company applies to its product: invest in infrastructure that compounds. Build the hard thing once so the next thing ships faster.

"Anand builds things that make the next problem easier," said CTO Ishmael Samuel. "The HIPAA sprint worked because of choices he made years ago. That's the kind of compounding you can't hire for."

Learn more at useparagon.com.