Government
October 14, 2019
November 18, 2024

A Federal Government Case Study

Castlepoint's AI-powered solution significantly reduced costs and improved accuracy for a Federal agency's records management, demonstrating the value of automation in enhancing compliance and efficiency.

A Federal Government Case Study

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Recently, Castlepoint engaged with a small specialist Federalagency. The agency had been running a manual sentencing process for two years,which involved reviewing content in a legacy shared drive and classifying itagainst AFDA Express and their Records Authority (RA). It wanted to explore anautomation solution as an alternative.

We implemented Castlepoint and ran it across the same drive,registering, classifying and sentencing the content using ArtificialIntelligence (AI).

In parallel, we selected a random sample of files, and undertook a separate manual sentencing activity by a qualified records manager, blind to the results of both the original manual activity and the Castlepoint audit.

Cost savings

We saw a 70% reduction in per-item costs (from 7c per item to 0.004 cents) for sentencing, compared to the manual model. This would continue to reduce as Castlepoint ran across more systems, as the license is for the whole enterprise. Overall, we reduced the cost of processing by 95% per item.

The other huge benefit of automation is extensibility. We ran some other key uses cases with Castlepoint, with the following annualised results:

  • Discovery: $A401,535.82 to $A10,018.40(97.5%) per annum.
  • Disposition: $A1,867.56 to $A27.33(98.5%) per action.
  • Identifying redundant items: $A85.42 to $A2.66(97%) per record.
  • Reporting and auditing: $A1,936.63 to $A4.56(99.8%) per event.

Our projected Return on Investment for Castlepoint was under one month to 100% cost recovery.  

Improved quality

We found that 75% of the manually classified records in the sample size were potentially under-classified, and should be retained 40% longer than currently planned. This under-classification was caused by assessing the records based on their title and a (necessarily) quick scan of their content, which did not allow the sentencer to identify small (but key) portions of text that elevated the item from a 7-year class to a 10-year class, for example.  Castlepoint had a 100% success rate in retention application, compared to the in-depth records manager sentencing action.  

Thesentencer could not open some types of files, meaning they could not besentenced at all. Attachments in emails couldn’t be opened; hidden files,system files, files with overlong names, and zip files were excluded. In thisshare, the most common file types included .properties, .bat, .html and .gz. whichthe sentencer couldn’t read. Castlepoint was able to read all of these.

Castlepoint identified over 500 items with sensitive content, and over 2,500 items subject to a freeze or hold. It also flagged actionable events, including deletions, classification downgrades, unauthorised modifications, or any other action we wanted visibility of. And we also created a taxonomy of ‘high value’ terms, so that the agency can easily see and protect information that is of interest to the executive, key projects, or current regulatory activities.   

Summary

Overall we found a more cost-effective, faster and more accurate outcome when we used Castlepoint to sentence the drive - and we were able to make findings that provided value to the strategy, audit, legal and security teams as well. This made the value proposition much stronger.