Runner
Runner is an AI/ML tool described as an AI Chief of Staff for you and your team. According to its homepage, users show Runner how their team handles a process, train agents against a simulation of past cases until they pass, and then deploy one agent for every customer. The product is listed as free and is positioned around creating customer-specific AI agents rather than a single generic assistant. Runner's workflow centers on learning from historical or past cases. Teams demonstrate their process, and the system simulates prior cases to evaluate whether a trained agent behaves correctly. Once an agent passes the simulation, it can be deployed per customer. This approach targets repeatable, process-oriented work where consistency and customer context matter. The tool appears intended for teams that want to scale customer-facing or internal operations with AI agents. The homepage emphasizes an agent for every customer, suggesting a multi-tenant or per-customer deployment model. No public GitHub repository, language, license, or release details were available in the provided sources.
- Category
- AI/ML
- Pricing
- Free
Problem solved
Teams often handle similar processes repeatedly for different customers, and creating a reliable AI agent for each customer is difficult without examples of past cases. Runner addresses this by letting teams demonstrate their process, training agents on simulations of historical cases, and deploying an agent per customer once it passes. This reduces the need to manually configure or prompt a separate assistant for every customer.
Use cases
- Train an AI agent on past customer support cases
- Simulate team processes to validate agent behavior before deployment
- Deploy a dedicated AI agent for each customer
- Automate internal chief-of-staff style workflows
- Onboard team members by demonstrating processes to agents
- Evaluate agent readiness against historical case simulations
- Create customer-specific assistants for recurring operations
Audience
- Business Users
- Enterprise
- Startups
- Product Managers
Pros
- Focuses on customer-specific AI agents rather than a single generic assistant
- Uses past cases and simulation to train and validate agents
- Deploy one agent for every customer
- Listed as free
Cons
- Limited public technical documentation
- No GitHub repository available in the provided sources
- Unknown language, license, and release details
- Agent quality depends on the quality and volume of past cases
Official website: https://runner.now/
Canonical LambdaBase page: https://www.lambdabase.com/tools/runner