GTM systems that agents can actually operate.
Deepline is built by Aero AI Labs, Inc. for teams that want their GTM work to be programmable, inspectable, and usable from the tools where work already happens.
What we build
Deepline provides a shared execution layer for GTM work. Teams use it to discover data tools, run enrichment and validation, route results to their systems, and keep durable records of the work. The product is available through a command-line interface, a Runtime API, and a remote MCP server, so a person, a scheduled process, or an AI agent can use the same underlying capabilities.
The practical goal is straightforward: make repeatable GTM operations explicit instead of trapping them in a one-off spreadsheet, a browser tab, or a private prompt. A Deepline Play can define the task, its inputs, the tools it uses, and the resulting run history. That gives teams an implementation they can inspect, improve, and run again when the business process changes.
How to evaluate Deepline
Start with the documentation and a small, bounded workflow. The API reference describes the supported HTTP surface, while the tool catalog exposes typed input and output information for individual provider-backed actions. If your agent supports MCP, use the published Streamable HTTP endpoint and complete the normal workspace authorization flow. If it can run shell commands, follow the install guide instead.
For questions about product capability, use cases, security, pricing, or support, use the linked resources below or contact the Deepline team. We publish a sitemap, an llms.txt index, OpenAPI metadata, and MCP server metadata so people and agents can discover the same authoritative starting points.