Shriram Finance
less than 3–4 hours — Onboarding Turn-Around-Time (TAT)
Independently reportedBanking & finance · Process automation · Classical ML · In production
Process automation
P. McCaul Consulting Engineers · DoozerAI
Vendor-reportedOtherIn productionNLP
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 doozer.ai (vendor self-report). Checked against the source page on 2026-09-06. 5 of 5 figures below appear on that page word for word.
The problem
P. McCaul Consulting Engineers needed an efficient way to monitor high volumes of EU government tender portals to identify environmental engineering contracts they could bid on.
What was deployed
- Vendor
- DoozerAI
- Products
- Trevor
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- Custom build
- Data used
- EU government tender portals, tender descriptions
- Scale
- 50,000+ Jobs Analyzed
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.
50,000+Jobs Analyzed
“Trevor transformed P. McCaul's tender monitoring process, analyzing 50,000+ jobs”
Quoted word for word from the source
1200Relevant Opportunities Identified
“identifying 1200 relevant opportunities”
Quoted word for word from the source
197MTenders Won
“contributing to €197M in tenders won”
Quoted word for word from the source
Staff Time Freed
“The automation freed 15% of staff time”
Quoted word for word from the source · round percentage, no baseline given
Bid Submissions
“while increasing bid submissions by 20%”
Quoted word for word from the source · round percentage, no baseline given
eliminatedRisk of Missing Contracts
“and eliminating the risk of missing critical environmental engineering contracts.”
Quoted word for word from the source
“Trevor has transformed how we identify tender opportunities. We've gone from worrying about what we might have missed to confidently pursuing every relevant contract. The time savings alone have been remarkable, but the peace of mind is invaluable.”
Difficulties and limits
- Time-Consuming Manual Process — monitoring multiple tender portals manually delayed subsequent bidding processes and reporting, putting the firm at a competitive disadvantage
- High Risk of Missing Contracts — human error and misfiled jobs on tender portals led to missed opportunities; the firm had previously lost out on multi-million euro environmental engineering contracts due to these oversights
- Resource-Intensive Operations — substantial human effort was required to continuously monitor portals, understand job descriptions, and categorize opportunities, taking staff away from higher-value activities
- Inconsistent Categorization — manual classification of tender opportunities led to inconsistencies and potential misalignment with the firm's environmental engineering capabilities and strategic priorities
Sources
- doozer.ai — vendor self-report
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