Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!

Today we’re announcing ❄️ Snowglobe - the simulation engine for AI chatbots! Snowglobe makes it easy to simulate realistic user conversations at scale so you can reveal the blind spots where your chatbots fail, and generate labeled datasets for finetuning them. We built Snowglobe to solve a problem that we ran into again and again through our journey building Guardrails for the last two years — evaluating AI agents is very challenging. If you spend days and weeks manually creating test scenarios for your chatbots, Snowglobe generates hundreds of realistic user conversations in minutes. How do you even formulate a test plan for evaluating something that can take infinite inputs? How do you deal with the many edge cases that break AI chatbots in prod all the time? Interestingly, self driving cars had the exact same problem. They built high fidelity simulation environments to systematically test cars under a wide range of scenarios. Waymo had 20+ million miles on real roads, but 20+ BILLION miles in sim so they had the confidence needed to ship. Today, we’re excited to bring that same tooling to AI agents with the general availability of Snowglobe!