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Respan

@RespanAI • 2,166 subscribers

The platform for reliable AI agents. One gateway for models, with observability and evals built in. https://t.co/Q2UX2AO8Zf

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Your users never use your product the way you designed it. That’s why we’re launching Prompt Simulations today. Pick a prompt → generate realistic users and scenarios → run full multi-turn conversations → see exactly where your prompt breaks. Test against real behavior before real users find the edge cases.

Your users never use your product the way you designed it. That’s why we’re launching Prompt Simulations today. Pick a prompt → generate realistic users and scenarios → run full multi-turn conversations → see exactly where your prompt breaks. Test against real behavior before real users find the edge cases.

210,543 views • 9 days ago

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.

1,351,710 views • 4 months ago

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.

850,366 views • 3 months ago

Finta uses AI across its accounting platform for startups, with one rule: accuracy over automation. Every day, Finta uses Respan to test prompts across models, manage golden datasets, and run evals before shipping. See how Andy and his team build reliable AI accounting ↓

Finta uses AI across its accounting platform for startups, with one rule: accuracy over automation. Every day, Finta uses Respan to test prompts across models, manage golden datasets, and run evals before shipping. See how Andy and his team build reliable AI accounting ↓

54,459 views • 10 days ago

Introducing Respan P-1, the world’s best privacy model. Every AI application handles sensitive data. Existing approaches to protecting it force a tradeoff between accuracy, latency, and cost. We built P-1 to eliminate that tradeoff. P-1 sets a new state of the art for detecting and redacting sensitive information - outperforming existing models across our benchmark while being fast enough to run on every request. Starting today, P-1 powers PII redaction across Respan.

Introducing Respan P-1, the world’s best privacy model. Every AI application handles sensitive data. Existing approaches to protecting it force a tradeoff between accuracy, latency, and cost. We built P-1 to eliminate that tradeoff. P-1 sets a new state of the art for detecting and redacting sensitive information - outperforming existing models across our benchmark while being fast enough to run on every request. Starting today, P-1 powers PII redaction across Respan.

73,971 views • 23 days ago

We told our agent to hack another agent. It found a way in. Then another. Then another. And we can probably hack your agent too. Today, we’re launching Respan Security.

We told our agent to hack another agent. It found a way in. Then another. Then another. And we can probably hack your agent too. Today, we’re launching Respan Security.

202,650 views • 2 months ago

We deserve better error tracking than a giant table. 3 problems shouldn’t be buried in 10,000 error events. Introducing Respan Error Tracking.

We deserve better error tracking than a giant table. 3 problems shouldn’t be buried in 10,000 error events. Introducing Respan Error Tracking.

127,227 views • 1 month ago

What if you could search your logs by vibe? “The user is pissed” ”The agent is being lazy” “That actually went really well” Introducing Respan Behaviors. 🧵

What if you could search your logs by vibe? “The user is pissed” ”The agent is being lazy” “That actually went really well” Introducing Respan Behaviors. 🧵

140,031 views • 2 months ago

Most AI products don’t fail. They just lose a little performance everywhere. We built Respan for that entire loop, and that’s the idea behind our new film.

Most AI products don’t fail. They just lose a little performance everywhere. We built Respan for that entire loop, and that’s the idea behind our new film.

70,556 views • 1 month ago

Introducing Respan Evals 2.0: Automation. Most AI production issues don’t show up as errors. They show up as answers that look valid but are wrong, incomplete, unsafe, or off-brand. Respan now runs automated online evals on live production logs to catch silent quality failures in real time.

110,832 views • 2 months ago

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.

127,680 views • 5 months ago

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:

58,163 views • 1 year ago

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