Holiday Cars · Inspektlabs
95% Reduction — Turnaround Time
Vendor-reportedTravel & hospitality · Quality inspection · Computer vision · In production
Quality inspection
Root Insurance · Observe.AI
Vendor-reportedInsuranceUnited StatesIn productionEnterpriseNLP
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 exato.ai (vendor self-report). Checked against the source page on 2026-09-06. 3 of 4 figures below appear on that page word for word; the rest are marked.
The problem
Manual quality review process with low call coverage (0.003% of 102,000 monthly interactions), one-size-fits-all training, and lack of insights into AHT and CSAT.
What was deployed
- Vendor
- Observe.AI
- Products
- Contact Center AI
- Technique
- NLP
- Build or buy
- Bought off the shelf
- Deployment
- SaaS
- Data used
- recorded calls
- Scale
- 102K monthly interactions, 120 agents
- Timeline
- 7 months
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.
15% improvementcompliance
“Leading auto insurance company improves compliance by 15%, mitigating risk with conversation intelligence”
Quoted word for word from the source · round percentage, no baseline given
15% greater adoptionadoption of mandatory call disclosuresin the first month
“15% greater adoption of mandatory call disclosures in the first month.”
Quoted word for word from the source · round percentage, no baseline given
100%call coveragefrom 0.003%
“increased call coverage from .003% to 100%”
Quoted word for word from the source
100%percentage of voice calls quality checked
“With Contact Center AI, the company quality checks 100% of voice calls”
Not found on the source page in these words
“Before implementing Contact Center AI just seven months ago, our quality review process was extremely manual. Our CSR to Quality Analyst ratio is about 50 to 1. In an average month, an analyst evaluates two calls per associate. During any given month, our CSRs take hundreds of calls. By only evaluating 2 calls, our QA’s were touching a very small sample of the total interactions.”
Difficulties and limits
- Manual Quality Review Process and Low Call Coverage
- One-size Fits All Training Program
- Lack of Vision Into Crucial Insights (AHT and CSAT)
Sources
- exato.ai — vendor self-report
Similar deployments
MSM (MyMind Joint Stock Company) · CloudThinker
98.4% — Bug detection rate on AI-assisted pull requests
Vendor-reportedTechnology & software · Quality inspection · AI agents · Scaled
Ancera · Voxel51
improved by over 7% — model performance
Vendor-reportedAgriculture · Quality inspection · Computer vision · In production
Mint Group Solutions · GuardSync AI
98% — Completion & Compliance Rate
Vendor-reportedOther · Quality inspection · Computer vision · In production
Prohan · DAC.digital
Vendor-reportedManufacturing · Quality inspection · Computer vision · In production
icare · SAS
increased by 15% — accuracy
Independently reportedInsurance · Process automation · Classical ML · Scaled · 2019