Economics

The same answer. One-eighth to one-thirty-eighth of the price.

Everyone is overpaying for AI — not from carelessness, but because nobody knows which model is enough for the task. We do. The failure library decides, exhaustive pre-ship validation proves it, and the receipt shows the number before you commit. On agentic coding benchmarks, frontier models sit at 90–97%; our validated band is 93–97% — inside it, at a fraction of the cost.

Faultmap makes this possible — the same accuracy band, proven pre-build.

Per 1K requestsFrontier reflexWith Pavamana
Run cost, per 1K requests

$150–600+ on the frontier reflex

$2.10–6.50, right-sized

Accuracy band

90–97%

93–97%

Cheapest possible model

near zero

accuracy falls to ~70–93%

When the proof happens

after you ship

before you build

Modelled on real workloads, not marketing. The failure library (5M+ patterns) decides when a leaner model and architecture are sufficient; exhaustive pre-ship validation proves it, path by path, before the agent exists. Bands vary by task — every agent ships with its own cost justification.

Run the numbers on your workload
Your numbers

Run the arithmetic on your workload.

Frontier burn is easy to model — it is the biggest model on every call. The band below is what right-sizing plus validation looks like at your volume.

Frontier reflex, today

$600K/mo

unvalidated paths, biggest model every call

With Pavamana

$4K–$13K/mo

right-sized architecture, every path tested first

You save

$587K–$596K/mo

at 93–97% accuracy — the band, not the cliff

Modelled, not measured. Based on the failure library deciding when a leaner model and architecture are sufficient, and exhaustive pre-ship validation proving it. Bands vary by task; your agent ships with its own cost justification. Figures are approximate; actual costs vary by workload, model, region, and provider terms.

Why it holds

Cheap is a cliff. Right-sized is a strategy.

The cheapest model alone falls to ~70–93% on hard tasks — the cliff. The frontier reflex costs roughly 20–200×+ more than necessary. Between them sits the architecture most agents never get: the failure library tells us which paths a leaner model can carry, and every valid path is tested before the agent exists.

01

The library decides

5M+ failure patterns from real agent behaviour say where a leaner model is enough — and where it is not.

02

The check runs first

Every valid path (17,568 on one recent build) is tested before code exists. The expensive reasoning model is reserved for what needs it.

03

The receipt ships with it

Cost is quoted before commitment and baselined from day one. Renewal is a report, not a pitch.

Modelled on real workloads, not marketing. The failure library (5M+ patterns) decides when a leaner model and architecture are sufficient; exhaustive pre-ship validation proves it, path by path, before the agent exists. Bands vary by task — every agent ships with its own cost justification.

All cost figures are approximate estimates for comparison, based on public model pricing and typical production workloads at the time of writing. Actual costs vary with model choice, token usage, caching, region, volume discounts, and your specific use case and fine print of each provider’s terms. They are not a quote, guarantee, or promise of savings.

How it stays affordable

Discovery is autonomous. The cost stays flat.

Nothing in the discovery is done manually. Faultmap reads the goal, personas, data, and tools and maps the failures automatically — 5M+ patterns, no consultants in the loop. The same engine that maps one agent maps the hundredth at near-zero marginal cost, which is what makes exhaustive validation affordable at $10K a year.

Production plan$10K per year

Three production agents, built and kept cost-efficient.

  • Three production agents built to pass their own Faultmap
  • Kept cost-efficient continuously, savings baselined from day one
  • Exhaustive pre-ship validation on every path
  • Renewal is a report, not a pitch
  • $3K per additional agent

Anchored against

vs $55–110K of build labour for one agent

vs $150–600+ per 1K requests on unvalidated frontier paths

vs $20–100K a year fixing what breaks in production

Faultmap your agent, free
Sources & verification

Where these numbers come from.

Every cost figure on this page was checked against public pricing pages and production-agent cost analyses, accessed August 4–5, 2026. Pricing changes often — the disclaimer above applies to everything.

Verification method: figures cross-checked across at least two independent sources (official vendor pricing pages + at least one aggregator), converted to per-1K-request cost using typical production agent workloads (3–8 model calls, 20k–80k+ tokens per request, with and without caching).