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Artificial Intelligence·B2B

Inlet is Transforming API Chaos into Clarity

Nabarun ChakrabortyDivya Thakkar
Nabarun Chakraborty & Divya Thakkar·Aug 14, 2026·1 min read
Inlet, an AI-powered dev tool founded by Sean Adler and Adam Miller, automates software integration workflows.

Developers spend 30-40% of their time on integrations, connecting software systems, working through API documentation, and mapping data manually.

Inlet is an AI-powered development tool that automates several steps involved in building software integrations and makes the process 10x faster than tools like Copilot or Cursor.

The Minds Behind Inlet

Inlet was founded in 2023 by Sean Adler and Adam Miller, engineers with experience in AI and machine learning.

Sean previously worked at ASAPP and Akasa, where he worked on automating enterprise workflows with large language models (LLMs). Adam led teams at Gridspace and built AI-driven voice bots for complex workflows.

The founders based Inlet on their experience working with enterprise-level workflows and the integration problems involved in connecting software systems.

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Why Inlet?

Inlet is a B2B development tool that automates tasks involved in building integrations.

Engineers can upload API documentation to Inlet. Its AI indexes the documentation and identifies the relevant endpoints and data models.

Inlet also automates data mapping between schemas. A process that usually takes days can be reduced to minutes.

After the mappings are created, developers can use Inlet’s AI to generate code tailored to their infrastructure. The tool supports code generation in any language and for any platform, including legacy systems.

How Inlet Automates Integrations

Inlet’s workflow focuses on three parts of integration development:

  1. Indexing API documentation: The AI processes uploaded documentation and identifies endpoints and data models.
  2. Mapping data between schemas: The tool maps data between different schemas, reducing a process that can take days to minutes.
  3. Generating code: Developers can use the resulting mappings to generate code for their infrastructure, language, or platform.

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