
Infrastructure to make your product AI native
Build agents, workflows and networks with auth, memory and orchestration built in. Access any LLM worldwide (605 models, 60+ providers). Connect your APIs or MCP servers in a few clicks, or use 1,000+ integrations. Drill into traces, test against datasets before you ship, get outputs scored by LLM judges. Track cost per model, agent, task or customer, and monetise. Embed an AI workspace inside your app with a few lines of code where users can ask, schedule, automate anything.
Sidenet AI provides a SaaS platform for building AI-native products, enabling users to create agents and workflows with integrated authentication and orchestration. It offers access to over 605 LLM models, supports extensive API integrations, and includes tools for testing and cost tracking.
Scored deterministically. Only candidates that fire a story trigger are sent to a model, so this one has no written angle.
Gaps in our data, not findings about the product. Their weight is redistributed across the 5 we did measure.
A source that found nothing is a measurement. A source that has not run is a gap. Neither means the launch lacks the thing.