Tasq intelligently automates work identification, work assignment, and work management for production operations. Tasq learns from user feedback to continue to refine its models and recommendations.

How Tasq jumps ahead of Pump by Exception: Moving to a pump by exception system comes with its problems. Tasq has designed its system to alleviate these problems to reduce frustration while getting the intended value out of intelligent workflows.

Pump by exception systems are still reactive and create lot of noise. Tasq is proactive and filters out the noise while continuing to learn from users.

Tasq believes that the pairing of machine learning to workflow (assigning & prioritizing each individuals day) is critical to ensure an optimized operation. One without the other continues to frustrate users and will stop short of realizing true value. Tasq is agnostic to artificial lift type and currently have models working across all lift types to flag issues before they cause deferred production.

SaaS - per well fee model

• Connecting operational processes together: Synthesizing multiple systems together (XSPOC, Production data, SCADA, field form entry, data labeling, scheduling, live assigning/reassignment of wells/jobs)

• Machine learning: Tasq learns from each job to enhance the model & refine the future outputs

• User recommendations: Field technician will receive a recommendation on how to fix each issue that Tasq assigns to him/her

• Procedures: Open environment to build & manage your own procedures and link them to certain issue types. Procedures are created and edited by team leads. Procedures also show the best step to resolve the issue.

Problems Tasq addresses: Fragmented systems, silo'd knowledge, "dumb" systems

Solution: Deploy models that learn to flag the right work & make recommendations to increase production and enhance decision making

• Intelligent models: Well target model, setpoint optimization, anomaly detection, liquid loading, equipment change recommendations.
• User recommendations
• Field data capture is utilized to label ML models for enhance predictions
• Built in troubleshooting procedures for all type of operational issues
• All work in one platform. Scheduled work, PM, field data capture, reassignment, handoffs all included as a part of Tasq.
• Full scheduling functionality for all type of scheduled work