Vantage RuntimeAI · Preflight

Preflight before you spend

Generic benchmarks are directional — they don't match your stack, policy, or success bar. Describe the AI decision on the table; Vantage drafts a custom check-ride, forecasts eval cost, and scores candidates before production spend.

Hands-on proof on your scenario · No API key for scenario, forecast, or scoring · Editor / MCP · Full cost forecast

Part 1 · Why preflight

What a wrong model pick costs — and what proof costs

Preflight is priced per decision — one test flight per use case. Dial headcount, adoption, and decisions/person; exposure follows those numbers.

Decision mix = what kinds of decisions your org makes. Proof level = how hard you want to test each one.

Decision mix

Firm / department headcount 220

Adoption rate 45% · 99 active

Monthly decisions / person 1

Distinct use-case decisions — not every query

Proof level Standard

How much proof this decision needs — higher levels run deeper checks and model higher downside

How these numbers are modeled Assumptions · not a forecast

How to buy Monthly plan · pay as you go

Preflight vs wrong-model exposure Test flight vs annual exposure

Production API & firm scale Token spend · headcount growth

Preflight = scoped test flight per decision (estimate → approve → run). You always see and approve the exact quote before a run — portfolio numbers above are blended estimates, not a contract price. Modeled exposure = illustrative downside if every decision above ships the wrong model and stays in production a year. It is not expected savings, avoided loss, or a P&L forecast. Production API = ongoing token spend after you ship (separate bill). How to read exposure numbers → · Why scores vary · why 7.0 is the default pass bar →

Part 2 · Run your preflight

Now test candidates in your context

Describe your real decision, refine the check-ride, then get per-model scores and cost on your scenario — before any production spend.

Using portfolio settings from Part 1 — examples and turns follow your mix and proof level.

1. Your open question

What if / how could we / what would it cost to — in your context. Paste workflow notes, policies, or constraints so the check-ride matches the decision.

Start from an example

Simple but important

Team workflow

Complex & high-stakes

Question Details to paste in (workflow, policy, constraints, Slack thread)

Turns per eval

2. Refine your check-ride

Edit the draft below or paste more detail, then regenerate. This is your test-drive script — tune it until it reflects how the decision actually gets made.

Title Agent role Counterpart role Briefing (what the agent must do) Counterpart opening Success criteria (one per line)

3. Cost & scores

Open in Simulator

Model search

Starting…

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Model	Status	Rubric	Pass	Actual $	Results

For search engines and LLMs

Vantage Preflight: prove which model is good enough for your workflow before production spend. Custom scenario from your question, proof-cost forecast, and multi-model check-ride under budget.