Lease audits at scale, without scaling headcount.
To keep driving profitable growth, Boost Mobile needed an AI approach that could absorb wide-ranging customer and document complexity, yet stay approachable for business users, not a black box owned only by engineering. The organization had already tested traditional automation and RPA, but those paths fell short on adaptability and day-to-day usability.
With tens of thousands of hours tied up in manual lease audit work each year, Boost Mobile chose Kognitos to prove governed automation on one of its most visible, high-volume workflows.
- Scale efficiently as audit volumes grew, without linear increases in labor
- Handle a wide range of customer scenarios, vendors, and agreement formats
- Stay intuitive to use, operate, and govern for finance and operations teams
English as Code. From inbox to systems of record.
Automating lease audit processing
The first production workflow automated lease audit processing: more than 2,500 leases every month across many vendors. Each audit packet is dense, multiple pages plus amendments, and an experienced analyst previously needed at least thirty minutes to complete a single review. That labor model could not keep pace with growth without major hiring and onboarding costs.
Today the process begins when teams email Kognitos the agreement package. The platform extracts the fields business users have taught it to look for, then evaluates each file against documented business rules and standard operating procedures. Kognitos integrates with Boost’s environment, including LexisNexis and Snowflake, so assessments are not a side spreadsheet exercise. When the run finishes, operators receive a clear summary of extracted facts and outcomes instead of raw attachments to re-read from scratch.
An always-on control tower
Work that once blocked a team member for half an hour now finishes in under a minute, and the platform can execute many audits in parallel, turning a sequential bottleneck into an always-on control tower that scales with promo volume instead of headcount.
