Poku Labs
Poku Labs provides a human-AI collaboration platform that lets consumer companies automate operational workflows in stages, shifting responsibility from human operators to AI agents as they prove reliable. The platform includes an evaluation loop that tracks success rates, flags items for review, and uses outcomes as feedback to continuously improve agent performance. This staged approach helps companies maintain quality control while scaling automation across tasks like order review, exception resolution, and ERP updates.
- AI Agents
- Artificial Intelligence
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
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 (e.g., 20% agent responsibility in Week 01)
- 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