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Current status

Membria operates at a controlled loss. 200KARRfromEnterpriseEdition(35clients,200K ARR from Enterprise Edition (3–5 clients, 40K–80Kcontracts)covers 809080K contracts) covers ~80–90% of the 20K monthly OPEX; the remaining gap is intentionally filled with equity funding to keep the team lean while validation occurs.

Enterprise unit economics (monthly)

CategoryUSD
Revenue~17,000
Infrastructure~6,000
Engineering & support~9,000
Overhead & tools~5,000
Total OPEX~20,000
Net~–3,000
Enterprise revenue is reinvested to subsidize CE development, build reusable knowledge, and lower CE launch risk.

Community Edition (CE) pricing

Membria CE uses two tiers:
  1. Pay‑per‑distill (trial): users pay only when a DoD escalation is required. This tier provides backend knowledge access without full DBB/DS.
  2. Full subscription: $15–20/user/month. Includes Decision Surface + DBB client workflow plus backend escalations.

Revenue logic (examples)

  • Subscription scenario: 10,000 users × 17= 17 = ~170K/month (~$2M ARR).
  • Pay‑per‑distill scenario: revenue scales with DoD request volume; this tier converts heavy users into subscriptions once they need DS/DBB.

Combined trajectory

PhaseEnterpriseCommunityTotal ARR
Current~$200K$0~$200K
CE Beta (Year 1)~$250K~$1.2M~$1.45M
CE Scale (Year 2)~$300K~$4.5M~$4.8M
CE becomes the primary growth engine; enterprise remains a stable, non-dilutive base.

Revenue mix summary

StreamPricingRole
Enterprise Edition40K40K–80K / yearStabilizes cash, validates infrastructure
CE pay‑per‑distillPer DoD request (USD‑pegged → ACTI)Trial tier, usage‑driven
CE full subscription$15–20 / user / monthPredictable scale revenue with DBB/DS
API/Gateway (tokenized)Pay‑per‑use (USD pegged → ACTI)Aligns token demand with usage
Enterprise custom knowledgeOne-off + recurringHigh-margin services for regulated clients
Ecosystem servicesRevenue shareLong-term upside

Profitability outlook

  • Current net: controlled loss (~$3K/month).
  • CE scale (~10K users) expected to generate positive margin, with lower OPEX per user as cache reuse increases.
  • Profitability is tied to cache efficiency, reuse, and hybrid/local inference adoption.