Using AI to reduce uncertainty of
lead service line replacement

Empowering utilities with the information to accurately inventory service lines and direct replacement efforts where the lead is using predictive analytics and machine learning.

Missing, unreliable, and/or unrepresentative data means that utilities need more than
just existing records to count and locate Lead Service Lines

We use a three-step process to make inventories more accurate and save millions of pounds, targeting replacements to homes with highest probability of lead

  1. Verify accuracy of existing records

  2. Initial representative inspection list

  3. Predictive model and prioritisation

Waste Water

Manage - Normalise data from multiple sources, including SCADA, CMMS, LIMS, & pdf
Visualise - across multiple platforms
Analyse  - predictive insights
Action - Automated and manual actions to optimise your operation

Barriers to effective inventory and replacement

  • No accurate count of total lead service lines

  • Unreliable, outdated and missing data about lead service lines locations


© 2020 by Sypro Ltd, All trademarks, used with permission of the trademark owners

Sypro Ltd trading as Eramosa UK,  - as authorised by Eramosa Engineering - Canada

Sypro Ltd Trading as Eramosa UK  Suite A, 82 James Carter Road
Mildenhall, Suffolk, IP28 7DE, UK
Tel: UK +44 (0)1638 485080
Email: sean@eramosa.co.uk