Haystack™
Asset Inventory Verification
93%
Typical model accuracy
By Identifying High Risk Assets and Correcting Records Haystack™ is Creating Safer, More Reliable and Resilient Networks
Asset Verification
Maintaining an accurate and up-to-date inventory of assets, including components and equipment, is crucial for running a network efficiently and safely.
Occasionally, particular types of component or asset configuration can catastrophically fail either on the Operator’s own network or one with similar assets. In these cases it is essential similar cases are identified quickly and action taken. As asset records are usually insufficiently detailed or flexible to find these cases an Operator has to resort to time-consuming manual inspections. This is expensive and introduces unquantified risk to the system whilst it’s completed.
More routinely, as assets or fittings are replaced or repaired some discrepancies arise between what is actually installed and what’s recorded in a company’s asset management system. This mismatch increases system risk and unplanned maintenance expenses.
Haystack’s™ Models and Pipeline Rapidly and Reliably Identifies High Risk Assets and Potential Errors in Asset Inventory Records
700M
Images processed since 2018
Increased network safety and reliability
Pinpoint the location of old or problematic components across your network.
Reduce procurement costs
Ensure the correct data is supplied to contractors reducing unforeseen costs increases.
Thousands of assets and millions of images
Our systems are able to identify components attached to thousands of assets and millions of images.
Talk to us about Haystack™
Today many operators collect images and video during regular asset inspections, Keen AI’s Asset Search and Verification service processes this data, identifying high risk components, correcting asset records and enriching asset records with data that hasn’t been recorded before.
Since 2018, Keen AI has processed over 700M images for our electricity transmission and distribution customers. This enables us to rapidly fine tune our foundational model pipeline to address the specific challenge a customer is facing.
