Every company building AI-powered features today faces a constraint: their AI agent is only as capable as the data it can access. A sales automation tool that can't access a customer's full CRM history will generate incomplete recommendations. A support agent without real-time product usage data will misread the problem it's trying to solve. In both cases, the data exists; it sits within third-party tools the company already uses, but it lives behind separate APIs and systems, managed by separate vendors.
Most companies are still bridging that gap by hand, one integration at a time. It was this inefficiency that drew Anand Chaudhary to Paragon, the integration infrastructure platform for AI and B2B products, where he would go on to lead the engineering effort behind its core systems.
The bottleneck for most AI-powered products is the integration layer that connects the model to the data it needs. This problem predates the AI era. SaaS companies have been absorbing the cost of integration infrastructure for years. When a SaaS product needs to connect with the third-party tools its users rely on, each connection requires dedicated engineering work to build and maintain. A single integration can take weeks, and ten can consume an entire quarter - and that’s not factoring in maintenance and scaling costs over the integration’s lifespan. For a growing SaaS company, integration infrastructure compounds into a significant and ongoing engineering cost.
Paragon, the integration infrastructure platform for AI and B2B products, launched in 2020 as a tool for enterprise workflow automation. The company quickly recognized a more fundamental market need: SaaS companies were spending months building integration infrastructure from scratch, each one solving the same problem independently. The inefficiency represented both a market failure and an opportunity.
With Anand Chaudhary among its core engineers, Paragon pivoted to address that need directly, building an embedded integration platform that SaaS companies could incorporate into their own products. Rather than each company constructing its own connectors, Paragon provided the infrastructure layer, compressing what had previously taken months to weeks. The developer community validated the approach: Paragon was ranked the #1 Product of the Day on Product Hunt.
Anand Chaudhary had been there from the beginning. As one of Paragon’s founding engineers, he was part of the team behind its first Product Hunt launch. By the time the platform had shown clear market fit, Anand Chaudhary was the natural choice for engineering leadership. In April 2023, he stepped into the tech lead role to scale the product and harden the systems behind it.
Anand Chaudhary was promoted to solution architect and then to principal engineer by March 2025, each role expanding his technical ownership of the platform's core systems. As principal engineer, he oversees the architecture and operational reliability of the infrastructure that Paragon's entire customer base depends on.
The central engineering challenge he took on was one that every integration platform has to solve or fail: what happens when the external environment breaks? Third-party APIs impose rate limits. Networks drop connections mid-execution. For most platforms, these failures cascade downstream as broken workflows and lost data.
Paragon's Workflow Engine was built around a principle engineers call durable execution: the ability to process events reliably regardless of what the external environment does. Achieving this at scale requires maintaining execution state across partial failures, ensuring that interrupted processes can resume without duplicating results, and coordinating across systems that were never designed to work together.
Anand Chaudhary contributed to and led the development of that engine, which now powers billions of event executions across Paragon's customer base. Those executions run inside the products of Paragon's enterprise customers, making the Workflow Engine a piece of infrastructure that other companies' applications rely on every day.
"Reliability isn't a phase at the end," Anand Chaudhary has said. "Design it into the system from day one."
The Workflow Engine proved that Anand Chaudhary could build integration infrastructure that held at scale. AI would test whether that same approach could handle an entirely different kind of demand.
Traditional integrations move data between systems when specific events trigger them. AI agents demand something different. They operate autonomously, which means they need the user's full data context to be available the moment the agent reaches for it.
Anand Chaudhary architected Managed Sync to bridge that gap. The product is a data ingestion layer designed specifically for AI products and agents. It handles the pipeline between the third-party tools where user data lives and the AI systems that need to consume it as context. For SaaS companies building AI-powered features, Managed Sync eliminates the same category of engineering burden that Paragon's core platform had already eliminated for traditional integrations: the months spent constructing and maintaining custom data infrastructure.
Paragon also developed ActionKit, a suite of tools and triggers that enables companies to leverage their existing integrations as functional capabilities in AI-powered applications. Where Managed Sync gives AI agents access to data, ActionKit gives them the ability to act on it across connected systems.
Anand Chaudhary's near-term focus is expanding Paragon's connector library to more than 1,000 applications while optimizing the Workflow Engine for the real-time demands of AI-agent operations. The longer-term ambition is to establish Paragon as the universal standard for software connectivity, the infrastructure that makes it possible for any application to work with any other.
The integration problem is as old as enterprise software. What has changed is the cost of leaving it unsolved. As AI reshapes what companies need from their data infrastructure, it is engineers like Anand Chaudhary, those who build the integration layer, who will determine how well any of it performs.
Paragon is building that layer. Anand Chaudhary is the engineer leading the architecture behind it.
