One Agentic

Pricing Variables v2

Credit-model config — drives Pricing Assumptions v2
🔒  Internal Use Only  ·  Link the config file once — then “Save & apply” writes directly to pricing_config.json
given (external fact) assumption (internal modelling decision) observed (production data) Grey = derived / calculated
→ View Pricing Assumptions v2

LLM API Pricing

Raw model cost per 1M tokens — everything else derives from these.

ParameterTypeValueUnitNotes
Model name given Displayed in pricing table notes
Input token price given $ / 1M tokens — standard prompt & context
Cached input token price given $ / 1M tokens Prompt caching — reused system prompts & templates
Output token price given $ / 1M tokens — generated response
Revenue markup multiplier assumption × Applied to raw API cost to set customer price
Implied gross margin % Formula: 1 − (1 ÷ markup)

Credit Model & Neo Interactions Session

1 credit = creditUnit tokens (reference unit for billing). creditRaw is derived automatically — it adjusts whenever token prices change so the avg Neo session always costs the target number of credits.

Credit Unit

ParameterTypeValueNotes
Credit unit size assumption tokens Reference token count per credit
Target credit multiplier assumption Stable ratio — creditRaw derives from this
Credit raw cost derived = avgSessionCost ÷ neoTargetCredits — auto-updates with prices
Credit at markup creditRaw × markup

Standard Session — Neo Interactions (avg observed)

Token TypeTypeTokensCost (raw)
Fresh input observed
Cached input observed
Output observed
Avg session cost (raw)
Session price at market

Input tokens account for ~86% of session cost. Cached tokens reduce cost significantly — variance in fresh input is the primary cost driver.

Session Distribution — Planning Scenarios (100 runs)

Token typeTypeMinStd dev (σ)Max
Input tokens observed
Cached input observed
Output tokens observed

Min / Max bound the Minimum and Maximum planning scenarios. Std dev (σ) drives the Conservative (+1σ) scenario for all three token types.

Tier Design

Price = credits × creditMrk × (1 − discount). Set credits and discount — price derives automatically and tracks token price changes.

TierTypeCredits / moDiscount %Price / moMargin @ 100%
Micro assumption
Seed assumption
Mid assumption
Established assumption

Overage rate = creditMrk (/cr) — always above any tier’s implicit credit price, preserving upgrade incentive.

TAM Inputs

All ARR estimates use tier prices as the revenue unit — they update automatically when token prices or discounts change.

Early-Stage VC — Primary Segment

ParameterTypeValueNotes
Base fund count assumption funds Mid-scenario addressable early-stage VC funds
Optimistic fund count assumption funds High-scenario fund count

Late-Stage VC Segment

ParameterTypeValueNotes
Base fund count assumption funds Global late-stage / multi-stage VC funds — base scenario
Optimistic fund count assumption funds Broader global count — optimistic scenario
Base ARR (Established tier) lBase × Established price × 12
Optimistic ARR (Established tier) lOptimistic × Established price × 12

Late-stage funds mapped to Established tier — larger teams, higher deal volume.

Angel Investor Segment

ParameterTypeValueNotes
Conservative angel count assumption US early-adopter active angels
Base angel count assumption ACA active angel estimate (US)
Optimistic angel count assumption Broader active angel universe (US)

Angels are assumed to land on the Micro tier — solo investors with lower session volumes.

Corporate VC Segment

ParameterTypeValueNotes
Conservative count assumption units Global active corporate VC units
Optimistic count assumption units Broader global count
Conservative ARR (Mid tier) cvcConservative × Mid price × 12
Optimistic ARR (Established tier) cvcOptimistic × Established price × 12

Corporate VC mapped to Mid tier (conservative) and Established tier (optimistic) — strategic deal mandates drive moderate-to-high session volume.

Accelerator Segment

ParameterTypeValueNotes
Conservative count assumption programs Active programs — AngelBacked / Golden database counts
Optimistic count assumption programs Pitchbook upper bound — includes inactive / historical programs
Conservative ARR (Seed tier) accConservative × Seed price × 12
Optimistic ARR (Mid tier) accOptimistic × Mid price × 12

Accelerators mapped to Seed tier (conservative) and Mid tier (optimistic) — lower budget than established VC funds but moderate session volume for cohort evaluation.

Excluded Segments — Ballpark Only

SegmentTypeConservativeOptimisticBase ARR (Mid)Opt. ARR (Estab.)
PE / growth assumption
Family offices assumption
Investment banking assumption
Corporate development assumption
Sovereign wealth funds high confidence · high ARPU potential assumption
Event-driven / activist HFs medium confidence · 186 confirmed activists is hard floor assumption
Search funds high confidence · low WTP, likely Micro tier only assumption
Growth equity medium-low confidence · overlaps late-stage VC segment assumption
Total excluded ARR

Base uses Mid tier as ARPU. Optimistic uses Established tier. Not included in the primary VC TAM above.