A fully transparent AI venture powered by measured, real-time data. Autonomous software engineering ecosystem — 80 headings, ~372K lines of code measured from the repository. Pre-revenue, 0 customers, single founder + AI co-pilot. Raising $250K via SAFE to reach first pilot customers.
Valuation Clarification: T1/T2/T3 are outputs of the internal FIPR v6.1 VE.5 model: T1 = real replacement cost of measured LOC (÷ 3,000 production LOC per dev-year × $120K × complexity), plus risk-weighted systemic premiums, the AEGIS master-heading governance premium, and the capitalized AI Factory asset (continuous autonomous production without payroll). They are an internal assessment, not a market valuation. The $25M SAFE Cap is the fixed deal term you invest at. The model ceiling ($47.9M) landing above the cap supports the deal; model values and the cap are deliberately shown separately for honesty.
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Services, code progress, and ecosystem metrics update every 30 seconds.
371,773 lines — 2,667 files — 85 services. Built by a single founder with AI. Database backups, dumps, and machine-generated exports are NOT counted. Only application source files are counted. Updated in real-time.
Explore how each parameter affects valuation. Click any heading row above to see its full formula breakdown.
Every HEADING/SERVICE in the Amezay AI Ecosystem, valued using FIPR v6.1 Value Engine (VE.5), calibrated to real replacement cost. 3-tier display: T1 Asset Floor (replacement cost of measured LOC), T2 Module Value (replacement cost + risk-weighted premiums + AI Factory asset), T3 Ecosystem Ceiling (+10% synergy). AEGIS, the master heading, receives a 10% governance premium for orchestrating the whole ecosystem. The AI Factory asset capitalizes the autonomous workforce (20-engineer equivalent, no payroll). LOC measured from real source code. MMIMM scores from quality audits.
Complete venture infrastructure built on interconnected AI modules.
Traditional software companies face the same fracture: teams that don't scale, bloated budgets, repetitive toil, fragile infrastructure, and opaque management. Most ventures fail before finding product-market fit or crumble under unsustainable cost structures. The answer lies in rethinking software development itself.
Amezay AI's goal is an era where software development is largely AI-assisted: while humans focus on strategy, creativity, and business development, AI handles much of the coding, testing, deployment, and operations. The ecosystem runs on MasterMind AI, H13R (13-gate quality protocol), VOKA, VELA, and DARK-ROOM. The fully-autonomous factory is the long-term vision; today the founder + AI co-pilot operate the codebase.
Amezay occupies a category of its own. Competitors are either single-purpose tools (coding assistants) or closed-source enterprise platforms. None offer a self-hosted, full-stack AI operating system + complete enterprise application suite built at this scale by a single founder.
| Area | Amezay | Competitors |
|---|---|---|
| Architecture | 30-layer OS, 60+ APIs | Single-agent tools |
| Memory | 5-tier + LMD evolution | Chat history only |
| Deployment | Self-hosted, ~$150/mo | Cloud, $5K+/mo |
| Governance | Constitution + FIPR protocol | None |
| Autonomy | Founder + AI co-pilot (not measured) | Human-in-loop required |
| Source Access | Private repo (investor DD) | Mostly closed source |
Amezay operates in its own category. Competitors fall into three groups:
No competitor offers: a self-hosted, full-stack AI operating system + complete enterprise application suite at this scale.
Amezay vs global competitors for every DEV heading. 30+ headings, 700+ lines of detailed analysis.
Scores are a founder self-assessment against global competitors — not independently verified.
Redefining software production with the MMIMM loop (MasterMind Idea → Market) and the DARK-FACTORY concept. Technologies in the ecosystem: H13R (13-gate quality protocol), VOKA (AI Telephony + ACCSP + Omnichannel), VELA (Security), DARK-ROOM (sandbox), LUMINA (education), CRM. The 'no-humans-required factory' is the long-term vision; today the founder + AI co-pilot operate it.
Idea → Research → Develop → Test → Deploy → Market. In the designed model, each cycle is AI-conducted with human input for strategic direction only. Every step is logged, measured, and optimized. Today the loop is driven by the founder with an AI co-pilot.
The long-term vision: a lights-out software factory where AI agents generate code, run tests, and deploy with minimal human oversight. This is the goal this raise funds toward — it is not claimed as current operation. Today a single founder plus AI co-pilot produces the code.
The MMIMM development model: features are described in natural language and produced autonomously by the AI software factory (MasterMind AI → DARK-ROOM deploy). Currently operated by the founder with an AI co-pilot. No paid users and no international deployment yet — reaching first pilot customers is what this raise funds.
Measured from repository structure
Non-blank lines, code files only
No traditional engineering team
The workflow: the founder describes a feature in natural language. MasterMind SAI forms transform the request into a structured task. MasterMind AI evaluates and approves, then DARK-ROOM codes, tests, and deploys. The model is designed so domain experts (accountants, logisticians, municipal staff, exporters) can eventually drive it directly — this is the vision, not current practice.
MMIMM is the engine that turns natural language ideas into production code. The loop (idea → research → develop → test → deploy → market) is orchestrated by Hive Queen, recorded in LMD, and secured by VELA — the DARK-FACTORY, a software factory run by a single founder with an AI co-pilot. 'Minutes' is the development goal; no independent benchmark is claimed.
Latest AI tasks, code changes, and system events. Every update reflects here automatically.
Code metrics, LMD entries, and system events.
Every number on this page falls into one of three categories: Measured (from the live repository or system), Estimated (clearly-labeled assumptions), or Vision (aspiration, never presented as fact). Nothing else is shown.
LOC is computed by measure-loc.mjs, which walks the repository and maps each directory to a heading. The heading list itself is exported from the live amezay_hive database (hive_heading_manifest on ServerB) into heading-registry.json, so the page always reflects the current registry. Rules: only code file extensions count; blank lines and comments are excluded; node_modules, dist, build, backups, and archive are excluded. The result is stored in heading-loc.measured.json and is the single source of truth for the valuation model. LOC is a proxy for complexity and effort — it is not a measure of business value or revenue.
T1 (asset floor), T2 (module value), and T3 (ecosystem ceiling) are outputs of the internal FIPR v6.1 VE.5 model. T1 = realistic replacement cost of the measured LOC (LOC ÷ 3,000 production LOC per dev-year × $120K × complexity); only the systemic premium above rebuild cost carries risk. AEGIS (master heading) earns a 10% governance premium. A capitalized AI Factory asset (20-engineer-equivalent workforce × $120K × 8×) adds the value of continuous autonomous production without payroll. These are an internal, self-assessed reference range — not an independent valuation and not the price you invest at. The price is the $25M SAFE valuation cap, a fixed deal term.
Financial figures are estimates and labeled as such. Security posture shows "pending" until a real scan completes — no vulnerability count is claimed. Customer and user numbers are zero until there are customers. Global deployment is a vision, not a claim. Where a number cannot be verified, the page says so instead of inventing a value.
Chronological flow of key events, commits, and FI tasks.
A unique governance structure where founder and AI co-lead work together.
Full transparency with real costs and targets.
This is a long-term commitment. Your money is spent on infrastructure, tools, and assets — it is non-refundable.
IMPORTANT: Funds are spent immediately on non-recoverable assets. Physical servers, domain registrations, API credits, and software licenses cannot be refunded. There is no "money back" option.
This is NOT a liquid investment. You cannot sell your position on demand. The earliest realistic exit is acquisition or Series A funding — estimated 3-5 years. Do not invest money you may need within this timeframe.
Answers to every question an investor should ask.
All spending is fully transparent to investors. Every dollar is accounted for in real-time. These are non-recoverable asset expenditures — once spent, funds cannot be returned.
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Detailed feature-by-feature comparison with 6 competitors.
Key terms and definitions for the Amezay AI ecosystem.