Poku builds human-AI collaboration software that helps consumer companies automate operational workflows while keeping people in the loop. The platform enables teams to run live workflows, gradually shift responsibility to AI agents, and use performance feedback to continuously improve automation success rates.
Funding
Funding not disclosed
Founders
Product
Problem
Consumer companies often struggle to automate complex operational workflows because edge cases and quality standards are difficult to define upfront. Fully automated systems fail on unusual situations, while fully manual processes are slow and expensive, creating a need for a balanced approach that combines human judgment with AI efficiency.
Solution
Poku provides a human-AI collaboration platform that lets consumer companies run live workflows with a clear division of responsibility between human operators and AI agents. The platform supports a staged automation approach where teams first run workflows manually, then gradually shift responsibility to AI agents as they demonstrate reliability. Poku includes an evaluation loop that tracks success rates, flags items needing review, and uses every outcome as feedback to correct and improve the system continuously. This allows companies to maintain quality control while scaling automation across their operations.
Target Audience
Consumer companies with operational workflows involving order management, exception handling, and ERP system updates that want to automate processes while maintaining human oversight.
Features
- Live workflow execution with step-by-step tracking for tasks like order review, exception resolution, and ERP updates
- Responsibility shift mechanism that lets teams transition from human-led to agent-led operations in stages
- Evaluation loop with success rate monitoring, completed task tracking, and review queues for items needing human attention
- Feedback-driven improvement system that treats every outcome as a signal to refine agent behavior and decision-making