A California-based debt-relief program ran two of the most painful processes in tax: pulling client data from the IRS portal and filing returns through Intuit. Each took ~45 minutes manually, the IRS only allowed a single credential, and COVID-era backlogs piled on. We built two interlocking RPA robots that ran sequentially and in parallel.
Two resource-intensive operations: IRS data retrieval per client, and return filings via Intuit. Each took ~45 minutes manually. The IRS portal restricted access to a single credential set, blocking concurrent processing. Two-factor authentication added another technical hurdle, and COVID-era operational disruptions caused IRS backlogs and intermittent staff lockdowns.
Manual scaling was simply not possible — not by hiring, not by overtime — so the queue was building up while clients waited.
We deployed two interlocking RPA robots. Robot one handled IRS authentication, document retrieval, data extraction, and handoff. To deal with 2FA, the robot accessed a designated mobile device through a VPN and read the rotating 30-second authentication codes — a clean, auditable workaround that respected the security model rather than circumventing it.
Robot two automated tax-return filings through Intuit using the data extracted by robot one. The two ran in a coordinated pipeline, with structured handoffs and exception queues for cases needing human review.
In just over a week, the first robot processed 1,657 IRS cases at an average of 6 minutes 28 seconds each — saving roughly 38.5 minutes per case and 1,060 hours overall. The second robot handled 2,600 filings at an average of 4 minutes 25 seconds each, saving an additional 1,755 hours.
Combined: 2,818 hours saved — over 70 weeks of FTE-equivalent — and $100,000+ in labour costs based on California medians. Operational continuity, velocity, and precision were maintained at a moment when traditional methods simply weren't available.
All of these started with a 30-minute call. Yours can too.
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