IIT Delhi · Rezo.ai
685 — Student Enrollments
Vendor-reportedEducation · Sales & marketing · AI agents · In production
Sales & marketing
Perk · AutoRFP.ai
Vendor-reportedTechnology & softwareIn productionLLM
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by autorfp.ai (vendor self-report). Checked against the source page on 2026-09-05. 4 of 4 figures below appear on that page word for word.
The problem
Response content lived across Google Drive, where keyword search and manual assembly broke as RFP volume grew and Perk added bid headcount across Word, PDF, and Excel formats.
What was deployed
- Vendor
- AutoRFP.ai
- Products
- AutoRFP.ai, Project Agent
- Technique
- LLM
- Build or buy
- Bought off the shelf
- Deployment
- SaaS
- Data used
- library content, past answers, Word, PDF, and Excel source material
- Scale
- global
What changed
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
more than doubleRFPs responded tothe year before
“Perk has responded to more than double the number of RFPs than it had the year before.”
Quoted word for word from the source
949hours saved
“The team saved 949 hours”
Quoted word for word from the source
20 to 30% moreRFPs responded toquarter on quarter
“The team reported 20 to 30% more RFPs quarter on quarter”
Quoted word for word from the source
time savedfrom old process
“saving 45% of the time compared with the old process.”
Quoted word for word from the source
strongershortlist and closing rates
“Stronger AI-assisted responses helped Perk improve shortlist and closing rates while increasing capacity and reducing the time it takes to complete bids.”
Quoted word for word from the source
“AutoRFP.ai is like a team member that never sleeps, keeps getting smarter, and allows my team to focus on the stuff that they’re really good at.”
Difficulties and limits
- Response content lived across Google Drive, where keyword search and manual assembly broke as RFP volume grew and Perk added bid headcount across Word, PDF, and Excel formats.
- Each time a new RFP came in, the team spent hours manually searching for past answers. When a keyword was missing, the team could not surface a response even when related content existed elsewhere in the library.
- RFP volumes were growing, and Perk, a rapidly expanding technology company, continually added headcount. That was when the old process started to break.
Sources
- autorfp.ai — vendor self-report, 2026-08-18
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