Agenta

Agenta is an open-source, end-to-end LLMOps platform designed to help engineering and product teams build, evaluate, and ship production-grade LLM applications faster. It consolidates the three most common pain points of LLM development — prompt engineering, evaluation, and observability — into a single collaborative workspace, eliminating the need to stitch together separate tools for each stage of the lifecycle. Instead of juggling prompt files in Git, spreadsheets for evaluations, and a separate tracing stack, teams can iterate on prompts, run structured experiments, compare model outputs side-by-side, and monitor live traffic from one interface.

The platform centers on a prompt playground and prompt management system that supports versioning, environments (dev, staging, prod), and deployments, so that changes to prompts and model configurations can be rolled out and rolled back without redeploying application code. Non-technical collaborators — product managers, domain experts, and QA — can tweak prompts, test variants, and annotate outputs directly in the UI, while engineers retain control over the underlying application logic through Agenta's SDK and API. This collaborative loop is one of Agenta's core value propositions: it unblocks the prompt-engineering bottleneck that typically sits entirely on engineering teams.

On the evaluation side, Agenta supports both automated and human-in-the-loop evaluation. Teams can define test sets, run batch evaluations across multiple prompt variants and models, and use built-in evaluators such as exact match, similarity, regex, JSON validation, RAG faithfulness, and LLM-as-a-judge. Results are visualized in dashboards that make regression detection and model comparison straightforward, which is critical when choosing between providers like OpenAI, Anthropic, Google, Mistral, or self-hosted open models.

Observability is built on OpenTelemetry, giving Agenta native compatibility with standard tracing ecosystems. It captures full LLM traces — including nested spans for retrieval, tool calls, and agent steps — along with latency, cost, and token metrics. Engineers can jump from a production trace directly into the playground to reproduce and fix an issue, closing the loop between monitoring and iteration.

Agenta is available as a fully managed cloud offering and as a self-hosted open-source deployment, which appeals to regulated industries and teams with strict data-residency requirements. It is SOC 2 compliant, supports SSO, RBAC, and private deployments on the higher tiers, and integrates with popular frameworks such as LangChain, LlamaIndex, and LiteLLM. The combination of open-source foundations, enterprise controls, and a unified LLMOps workflow positions Agenta as a practical alternative to fragmented stacks built from Langfuse, Helicone, and standalone prompt tools.