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Respan

@RespanAI • 1,716 subscribers

Self-driving observability and evals for agents. Formerly Keywords AI (YC W24). Community: https://t.co/JAZ9auu0hr

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Introducing Respan AI Gateway. The world’s first AI gateway with built-in observability, evals, and prompt optimization. Access 1,000+ models through one endpoint, with the production layer teams need beyond routing.

Introducing Respan AI Gateway. The world’s first AI gateway with built-in observability, evals, and prompt optimization. Access 1,000+ models through one endpoint, with the production layer teams need beyond routing.

847,798 просмотров • 15 дней назад

AI observability platforms raised $1B+ to reinvent print debugging for the agent era. Reading traces manually is not a scalable production workflow. We think the stack should catch issues itself. Meet Respan.

AI observability platforms raised $1B+ to reinvent print debugging for the agent era. Reading traces manually is not a scalable production workflow. We think the stack should catch issues itself. Meet Respan.

1,350,804 просмотров • 1 месяц назад

Respan Launch Week, Day 2: Evals Evals are one of the hardest parts of building AI applications. It is not because teams cannot run them. It is because they are hard to structure, hard to compare, and even harder to improve over time. So teams end up guessing. Did this prompt actually get better? Is this model really an improvement? We built Evals in Respan to make this systematic. You define: - what you want to test, such as prompts, models, or configs - the dataset, from production logs or test cases - the evaluators, whether LLM, code, human, or a mix Then you run experiments and compare results side by side. Same inputs. Same evaluation. Clear answers. No more guessing. Start running your first eval.

Respan Launch Week, Day 2: Evals Evals are one of the hardest parts of building AI applications. It is not because teams cannot run them. It is because they are hard to structure, hard to compare, and even harder to improve over time. So teams end up guessing. Did this prompt actually get better? Is this model really an improvement? We built Evals in Respan to make this systematic. You define: - what you want to test, such as prompts, models, or configs - the dataset, from production logs or test cases - the evaluators, whether LLM, code, human, or a mix Then you run experiments and compare results side by side. Same inputs. Same evaluation. Clear answers. No more guessing. Start running your first eval.

127,602 просмотров • 2 месяцев назад

We worked with OpenAI to build a native integration for the OpenAI Agents SDK. Today, we are very excited to launch as a tracing processor. With just a few lines of code, you can trace all your agent workflows and debug them much faster. Check out this quick demo to get started:

We worked with OpenAI to build a native integration for the OpenAI Agents SDK. Today, we are very excited to launch as a tracing processor. With just a few lines of code, you can trace all your agent workflows and debug them much faster. Check out this quick demo to get started:

58,055 просмотров • 1 год назад

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