Agent Development alternatives
The most-used agent development tools compared with Semantic Kernel — pricing, strengths, and who each one is best for.
Each tool below is a same-category competitor. Click Compare for a side-by-side breakdown against Semantic Kernel.
A low-level orchestration framework for building stateful, multi-step agent workflows with explicit control over state, branching, and human-in-the-loop steps.
A framework for orchestrating role-based multi-agent teams, where specialized agents collaborate on a task under a defined process.
A data framework for connecting LLMs to private and enterprise data — ingestion, indexing, retrieval, and agent workflows over your own content.
An open-source framework from Microsoft Research for building multi-agent applications, where agents converse to solve tasks together.
OpenAI first-party agent toolkit — a visual Agent Builder, embeddable ChatKit UI, a connector registry, and evals, billed at plain API rates.
An open-source framework from deepset for building production LLM applications — RAG, search, and agents — built around composable pipelines.
One AI workflow a week, with the Agent Development that actually ship it — real stacks, real costs, and where each option falls down.
Browse our workflow library to see how each of these tools fits into real SMB automation stacks.