March 2025 Summaries

Embedded iPaaS platforms promise ease of use for non-technical users to build integrations with prebuilt blocks, but in reality, they rarely work at scale due to several issues. The assumption that non-technical folks can handle integrations 100% is flawed, as real-world integrations require deep knowledge of the product's data model and reasoning about edge cases. Prebuilt blocks often don't align with a product's integration logic, leading to limitations in extending them without writing code. Additionally, embedded iPaaS tools lack primitives that developers need for robust integration infrastructure, such as end-to-end type safety and support for continuous syncs. They also break at scale due to serialization and deserialization issues, data passing limitations, and rate limit handling problems. In contrast, tools built for developers offer full control over integrations, handle OAuth and other complexities out of the box, and are built to scale with the product from day one.

Nango has launched its OpenTelemetry Observability, providing real-time logs and metrics for monitoring integrations. The feature covers 18 log types, including status, integration, connection, scripts, and time window, with filtering capabilities. Real-time metrics are also available, tracking key execution data such as sync executions, action executions, proxy requests, and webhook executions. Additionally, Nango offers OpenTelemetry export for custom observability, enabling the export of integration events as traces to an OpenTelemetry collector. This feature is essential when working with external APIs, allowing users to break down metrics per customer or integration, debug API calls, and track data quality issues. The features are available on both Nango Cloud and Nango Enterprise Self-Hosted, with plans to expand observability capabilities further in the future.

Nango for AI now supports your AI use-cases by providing seamless API access and enabling data ingestion from over 400 APIs, allowing AI applications to thrive on continuous access to fresh external data. Nango also offers agentic API access, managed authentication, and reliability and security features such as logs, metrics, and alerts for full visibility. This is achieved through leveraging AI technologies like parsing API documentation, automating integration testing, and enabling AI-assisted custom integration building. Nango powers the integrations of many AI companies including V7 Labs, Markprompt, Credal, Centralize, Console, Hyperbound, Tennr, Useful, Outer Op, Chatsheet, Laudable, Noan, Ottogrid, Inventive AI, Bloompath, Usenerve, Beam, Lynq.

Nango provides a suite of tools and infrastructure to support real-time syncing, making it easy to reflect changes from external systems into apps instantly without complex infrastructure. Real-time syncing requires webhooks, which can be used in conjunction with fast polling for near real-time syncing. Nango supports both webhooks and fast polling, offering merge strategies to ensure data consistency, and provides high-frequency polling options with optimizations such as 30-second intervals, incremental syncing, and sync partitioning. Setting up real-time syncing with Nango is straightforward, and the company offers documentation and resources for implementation.

AI agents, while becoming increasingly powerful, face significant challenges when interacting with real-world APIs due to complexities like authentication, schema translation, rate limits, and error handling, which can lead to frequent failures. To address these issues, an integrations platform is essential for translating human-like intents into structured API-specific executions, managing authentication securely, providing observability for debugging, and setting constraints to ensure reliable and secure operations. Such a platform introduces clear contracts to validate inputs and handle errors effectively, distinguishing production-ready agents from mere demos. While Model Context Protocols (MCPs) offer a framework for standardizing interactions, they fall short without the robust infrastructure provided by an integrations platform, which is crucial for deploying AI agents that work reliably across various SaaS tools and can be trusted by users.

As a product manager, roadmapping integrations requires careful planning and strategic decision-making to drive growth, increase retention, and create new revenue opportunities. Prioritizing integrations based on customer demand, business impact, feasibility, and strategic fit is crucial. Scoping and planning involve defining the scope of each integration, considering factors such as data sync, configuration options, and field mappings. Realistic timelines and resource planning are essential to ensure successful delivery. Building robust maintenance structures in place is vital to prevent integrations from becoming a maintenance nightmare. The build vs buy decision should be made before investing resources into developing integrations, with the Nango Approach offering a third path that combines control with efficiency. A strategic approach to integration roadmapping can help deliver more value to customers while maximizing team efficiency.

Product integrations, when executed effectively, can significantly boost growth, enhance customer retention, and unlock new revenue streams. Product managers face critical decisions regarding which integrations to prioritize and whether to build them in-house or use third-party platforms. Prioritizing integrations involves assessing customer demand, business impact, feasibility, and strategic alignment, considering both quantitative and qualitative data. Integrations can vary from deep, core-system integrations requiring data synchronization and customization to shallower, API-based integrations for specific use cases. Building integrations internally provides control but can lead to resource strain, maintenance challenges, and slower market delivery, whereas third-party platforms like Nango, Merge, or Paragon offer faster development and reduced overhead but come with their own limitations. Choosing the right partner involves evaluating supported integrations, ease of implementation, and scalability. Ultimately, by making informed decisions, product managers can leverage integrations to achieve strategic goals and enhance customer satisfaction.