Higher-ed admin (registrar, financial aid, R1 grants)
Illustrative scenario

Compressing Six Months to Ten Weeks: AI-Assisted F&A Rate Proposal Preparation

The triennial F&A rate proposal is the single most resource-intensive administrative process in sponsored programs finance — and it lands on top of the team's existing workload every three years without fail. If your team is pulling salary distribution, space utilization, and indirect cost pool data manually from Workday and Cayuse to build the base year package for DHHS or DoD cognizant agency negotiation, you already know the 6-month prep cycle isn't sustainable. An AI agent can cut that to 10 weeks while improving the documentation quality your federal agency reviewers expect.

Up and running in ~8 wkFor: Director of Sponsored Programs Finance or VP for Research Administration
Estimate your payback
~4 mo
Payback period
$195K
Est. savings / year
+$135K
Year-1 net

Rough estimate — change the numbers to match your business. We scope the real figures with you on a call.

Why the F&A Proposal Process Consumes So Much Staff Time

The challenge isn't complexity in any single step — it's the sheer volume of data extraction and reconciliation across systems that weren't built to talk to each other. Pulling salary distribution data from Workday, space utilization records from facilities systems, and indirect cost pool allocations from Cayuse SP and SAP requires iterative manual queries, reconciliation spreadsheets, and documentation that must map cleanly to 2 CFR 200 Subpart E cost pool structures. Sponsored programs finance staff at R1 universities spend $150,000–$300,000 per year in total comp on this work — most of it in the 6-month window before a cognizant agency submission deadline.

Continuous Collection, Automated Assembly

An AI Labor Company agent mines historical F&A rate proposal data packages and established 2 CFR 200 cost pool structures from Workday and Cayuse, then begins operating in continuous collection mode rather than waiting for the triennial crunch. A Gemini-powered agent collects base-year salary distribution, space utilization, and indirect cost data on an ongoing basis, reconciling against the 2 CFR 200 structure as data accumulates. When the proposal window opens, the base year data package is already assembled to cognizant agency specifications. The Director of Sponsored Programs Finance reviews the package and manages federal agency submission — without the preceding 4-5 months of data extraction work.

The Business Case: Staff Capacity and Negotiating Position

Compressing F&A proposal prep from 6 months to 10 weeks produces two distinct returns. The first is capacity: sponsored programs finance staff who previously devoted half a year to proposal assembly can redirect that time to day-to-day research administration. The second is negotiating position — proposals assembled from clean, continuously collected data with consistent cost pool documentation tend to survive federal agency scrutiny better than packages assembled under deadline pressure from manual exports. For a large R1 university where F&A recovery rates affect tens of millions in annual indirect cost recovery, even modest improvements in the negotiated rate represent meaningful budget impact. The agent is typically live and producing results in about 8 weeks.

Works with
Workday FinancialsCayuse SPResearch.govSAP S/4HANAMicrosoft 365Excel
Questions

How does the agent handle the space utilization survey component, which typically requires facilities data outside Workday?

The agent connects to facilities management data sources alongside Workday and Cayuse. If your institution uses SharePoint or SAP for space records, those are integrated into the collection workflow. Gaps in space data are surfaced as specific data requests rather than discovered late in the assembly process.

Can the agent support DHHS, DoD, and other cognizant agency formats in the same institution?

Yes — the agent applies the correct documentation structure based on which federal agency negotiates your rates. For universities with multiple cognizant agencies across different cost pools, it maintains separate documentation tracks and routes each package to the appropriate format requirements.

Related use cases

Illustrative scenario for education & edtech. Figures are example ranges, not guarantees — we scope real numbers with you on a call.

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