Return on investment
Give your experts more time to do expert work
Qevatrix is built on a simple operating principle: skilled quality, regulatory, clinical and evidence professionals should spend less time on repetitive administration and more time on work that requires their judgment. Published research supports that mechanism — with an important qualification.
AI and automation can make suitable tasks materially faster, but effects vary by task, and human review remains essential when correctness and regulated judgment matter. Qevatrix uses AI to draft, summarise, flag, retrieve and recommend. Qualified people remain responsible for approvals, regulatory conclusions, reportability decisions, CAPA closure and clinical conclusions.
Qevatrix is designed to reduce repetitive administrative work and release professional capacity for higher-value quality, regulatory, clinical and growth activities.
ROI calculator
Estimate the return for any Qevatrix application
Pick the applications and plans you are considering, describe the team doing the administrative work, and choose one of the three disclosed reduction scenarios. Every result is an estimate, and you can export it or email it to the people who approve the budget.
1. Choose your Qevatrix applications
Each application addresses a disclosed share of the administrative week. Overlapping applications never recover the same hour twice.
2. Your team
3. Reduction scenario
Published research
What the evidence actually shows
These studies evaluated generative AI, process automation and electronic data workflows. None of them evaluated Qevatrix — they establish that the mechanisms Qevatrix relies on have a credible evidence base.
40% faster professional writing, 18% higher quality
Randomised study of 453 college-educated professionals using generative AI on professional writing tasks.
Noy S, Zhang W. Science. 2023;381(6654):187-192. doi:10.1126/science.adh2586
15% average productivity increase
Real-world deployment across 5,172 support professionals using an AI assistant, with the largest gains among less experienced staff.
Brynjolfsson E, Li D, Raymond L. Quarterly Journal of Economics. 2025;140(2):889-942. doi:10.1093/qje/qjae044
25.1% faster, 12.2% more tasks completed
Randomised field experiment with 758 consultants. The same study found AI users performed worse on a task outside the model's capability frontier — which is why Qevatrix keeps a human review point on every regulated decision.
Dell'Acqua F, et al. Organization Science. 2026. doi:10.1287/orsc.2025.21838
Electronic case report forms beat paper
Randomised clinical-trial comparison: electronic capture was faster and showed better data integrity than paper forms.
Fleischmann R, et al. BMC Medical Research Methodology. 2017;17:153. doi:10.1186/s12874-017-0429-y
22% faster than spreadsheets
Registry crossover study comparing electronic data capture with Excel-based capture.
Staziaki PV, et al. Journal of Medical Internet Research. 2016;18(6):e141. doi:10.2196/jmir.5576
51 minutes saved per participant
Multicentre evaluation of automated EHR-to-CRF transfer, which would also have prevented hundreds of manual entry errors that survived monitoring.
Cheng AC, et al. Journal of Biomedical Informatics. 2026;180:105060. doi:10.1016/j.jbi.2026.105060
Assumptions
A conservative, disclosed model
There is not yet a large Qevatrix customer outcomes dataset, so Qevatrix does not publish a universal “X% faster” claim. Every estimate applies one of three transparent reduction scenarios to repetitive work the software actually addresses.
15% — Conservative
Below every published AI productivity result cited here.
25% — Base case
Close to the 25.1% speed gain observed in the 2026 consulting experiment.
35% — High utilisation
Mature adoption across several connected Qevatrix applications.
The core calculation is deliberately narrow: eligible repetitive hours × modelled time reduction × loaded labour rate = capacity value. The annual subscription is then deducted to produce a modelled ROI. Consulting cost avoidance and projected revenue are set to zero so the same recovered hour is never counted twice.
Recovered time is valued as productive capacity, not as a payroll reduction. A positive modelled ROI means the estimated value of released capacity exceeds the subscription cost under the stated assumptions — it does not mean a cash refund or an accounting expense reduction.
Illustrative base case
Modelled scenarios at a 25% reduction
These are modelled scenarios, not observed customer outcomes.
| Organisation | Configuration | Hours released / year | Estimated capacity value | Modelled ROI |
|---|---|---|---|---|
| Small device company | QualityOS Essentials | 240 | $14,400 | 21% |
| Growth-stage manufacturer | DeviceOS Professional | 720 | $54,000 | 50% |
| Established manufacturer | DeviceOS Professional* | 2,160 | $183,600 | 411% |
*Enterprise pricing may apply depending on site count, SSO, data residency, support and other requirements.
Break-even test
How much capacity has to be released to equal the price
At an illustrative loaded labour rate of $75 per hour, current published annual prices correspond to these thresholds. They are decision thresholds, not promises of savings.
| Qevatrix product | Annual price used | Capacity needed to equal price |
|---|---|---|
| QualityOS Essentials | $11,940 | 159 hours/year |
| QualityOS Professional | $23,940 | 319 hours/year |
| RegulatoryOS Essentials | $10,740 | 143 hours/year |
| RegulatoryOS Professional | $21,540 | 287 hours/year |
| DeviceOS Professional | $35,940 | 479 hours/year |
| ClinicalOS Single Study | $33,000 | 440 hours/year |
| EvidenceOS Registry | $29,940 | 399 hours/year |
Methodology
Disclosure
External studies cited here evaluated generative AI, process automation or electronic data workflows; they did not evaluate Qevatrix. Qevatrix figures are scenario models using the disclosed assumptions above and current published Qevatrix pricing. Actual results vary by organisation size, workflow mix, configuration, adoption and user practices.