CoveraText the agent
Methodology & benchmarks

How accurate is Covera, really?

Two honest scorecards. First, how the Monte-Carlo simulation holds up against the published MEPS aggregates it claims to reproduce and the ACA subsidy formula. Second, how candidate models compare when driving the real agent: on whether they cite real numbers, call the right tools, and what they cost.

Simulation accuracy

16/16 checks within tolerance · 80,000 simulated people

Mean spend by age band (vs MEPS)

Age 0-17 mean spend
$2,438 vs $2,300
Age 18-44 mean spend
$4,237 vs $3,700
Age 45-64 mean spend
$8,799 vs $8,400
Age 65+ mean spend
$15,498 vs $13,800

Spend concentration (vs MEPS)

Top 1% share of spend
23% vs 22%
Top 5% share of spend
53% vs 50%
Top 10% share of spend
68% vs 66%
Bottom 50% share of spend
4% vs 3%
Population mean annual spend
$6,885 vs $6,700
Population median annual spend
$1,814 vs $1,300

ACA subsidy formula

FPL, household of 1
$15,650 vs $15,650
FPL, household of 4
$32,150 vs $32,150
Applicable % at 150% FPL
0% vs 0%
Applicable % at 250% FPL
4% vs 4%
Applicable % at 400% FPL
8.5% vs 8.5%
Applicable % above 400% FPL (capped)
8.5% vs 8.5%

Read honestly: the engine reproduces adult age-band means, the ACA subsidy math, and (after adding a person-year frailty termthat correlates a year's care across service lines) the real spend concentration the top few percent of people who drive most healthcare cost. That heavy tail is the hard part to get right, and it is what the bad-year risk you rank on depends on. Source: Calibrated to the AHRQ Medical Expenditure Panel Survey (MEPS), Household Component.

Explore the distribution

5,000 simulated years, run live in your browser.

$5,599
Simulated mean
MEPS target $8,400
$675
Median year
half spend less
58%
Top 5% share
of this group's spend
Simulated annual spend distributionmean$0$53,955+

The long right tail is the whole point: a few people drive most spending, which is why the cheapest plan often is not the safest. Add a condition to watch the mean and tail move.

What real care costs, plan by plan

Each row is a fixed episode of care run through the real adjudication engine on the cheapest plan in each metal tier. Click any number to see the exact math.

Episodes are fixed reference bundles (round allowed amounts), so the math is checkable; the plans and cost-sharing are real CMS PY2026 data. Deductible + coinsurance + copays, capped at the out-of-pocket max, equals the number shown.

LLM model benchmark

The model benchmark (needs ANTHROPIC_API_KEY) hasn't been generated yet. Run npm run benchmark to populate this section.

Faithfulness = share of dollar figures in the reply that match a real simulated number (not hallucinated). Tool accuracy = share of questions where the model called the expected tool. Quality = LLM-as-judge rubric. Cost uses real token usage × published per-model pricing. The harness lives in scripts/benchmark/.