See what you save at the coverage you choose.
Set your agents, your volume, and how much of it you want QEval® to score. You get your annual savings across agent efficiency, QA capacity, and handle time. No gate, no login.
How many compliance violations are you missing right now?
Most QA programs sample 2 to 5% of conversations. The math on what falls through is not complicated. It is just uncomfortable.
Your numbers. Your model. Your savings.
Six industry presets, three scenarios, and an ingestion dial. The output is your year-one value across the levers QEval® actually moves: agent efficiency, QA workforce capacity, and handle time. Most customers run 50% ingestion and capture the majority of the value; you do not need 100%. We size the QEval® investment to your plan and net it out with you, so this page shows the value, not our price.
Your numbers in, your savings out.
Your savings, in one place. Yours to keep.
One click gives you a portable summary with all three scenarios, your inputs, and the math behind every number. Copy it, keep it, and come back to it whenever you want.
Financial Services operation with 1,000 human agents and 0 AI agents generating 440,000 conversations per month at a 3% QA sampling rate.
Of 5,280,000 annual conversations, 5,121,600 go unreviewed. At the industry-average violation rate of 2.3%, an estimated 117,797 compliance violations per year pass undetected.
Compliance risk avoidance: $1.1M. QA labor capacity: $280K. Operational efficiency: $700K. Sales/revenue lift: $700K.
Total recoverable value (base): $2.8M/yr across compliance, QA capacity, operational efficiency, and revenue lift. This is the gross value QEval® puts back on the P&L; the QEval® investment is sized to the deployment plan and netted out in the commercial conversation.
Your numbers versus industry leaders.
Three dimensions where the gap between current-state and QEval-state drives every dollar in the model above.
Companies your size in your industry typically see this.
Anonymized outcomes from QEval® deployments across five verticals. These are measured results, not projections.
The math behind the model.
Why does the model default to 50% ingestion, not 100%?
Because that is how QEval® is actually deployed. You do not need to score every conversation to capture most of the value; 50% ingestion is plenty for the majority of programs, and many run effectively at 30%. The model scales the efficiency, handle-time, compliance, and sales levers directly by your ingestion rate, so you can see exactly what 30%, 50%, or 100% is worth and choose the coverage that fits your budget. QA workforce savings come from automating the review function itself, so they hold up even at lower ingestion.
Where does the 2.3% violation rate come from?
Industry research across financial services, healthcare, and telecom contact centers consistently finds that 2 to 3% of customer interactions contain a compliance violation (disclosure miss, identity verification skip, regulatory language failure). 2.3% is the midpoint of published ranges. Your actual rate may be higher or lower depending on industry, agent tenure, and call complexity. Adjust the cost-per-violation slider to model your specific risk.
How are the value levers calculated?
Agent efficiency value (the primary lever): efficiency gain (5 to 10% by scenario) multiplied by total agents multiplied by annual agent cost (hourly rate multiplied by 2,080 hours) multiplied by ingestion rate. This mirrors the deck's efficiency model, where the ingestion factor is applied directly. QA workforce savings: your QA team is estimated from agent count (about one auditor per 85 agents), multiplied by a loaded QA cost and the share of that team QEval® lets you redeploy (50 to 80% by scenario). Handle-time value: ingested annual volume multiplied by average handle time multiplied by AHT reduction (8 to 15% by scenario) multiplied by hourly cost. Compliance risk (optional, off by default) and sales/revenue lift (sales-focused operations only) are additive when enabled.
What do the three scenarios mean?
Each scenario sets the efficiency, handle-time, and QA-redeploy rates together. Conservative uses a 5% efficiency gain, 8% AHT reduction, and 50% QA redeploy: minimal process change. Base uses 7.5% / 12% / 65%: standard deployment with coaching integration. Upside uses 10% / 15% / 80%: full Six Layers operationalization with executive sponsorship. The efficiency ramp mirrors the deck's documented 5% to 10% climb across the first year.
Why does the model not include revenue from Layers 2 through 6 directly?
It does, indirectly. The Sales/Revenue Lift lever maps to Layers 2 and 3 (Customer and Revenue Intelligence). Operational Efficiency maps to Layer 4. The model deliberately underestimates Layer 5 (Training Intelligence) and Layer 6 (Strategic Intelligence) because those outcomes compound over time and are harder to project for Year 1. The 3-Year TCO view captures more of that compounding.
Can I trust these savings numbers?
Yes, and you can check every one. Every number traces to an input you provided or an assumption documented in the ledger, so nothing is hidden. QEval® does not pad the model; if anything, the conservative scenario deliberately understates the savings. Click "Copy to clipboard" on the savings summary to keep the full breakdown, adjust the wording to your own format, and revisit it whenever you want.
Run the model on your real numbers.
Bring your scorecards, your call volume, your compliance requirements. We will score real interactions in 30 minutes and validate the business case with your data.