Series D funding analysis - FINAL ROUND

Grid Translator App – Series D (Final Round) Investor Brief

Status: Final capital raise before launch
Round Type: Series D – Pre-Launch Consolidation
Round Objective: Full capitalization of total historical and projected costs through global launch readiness (Android + iOS).
Funding Use: Product completion, market entry, and runway for 12 months post-launch.


A. Summary

The Series D round closes all preceding development phases (v1.0 → v2.1 Beta → Launch Build).
It consolidates every cumulative cost — R&D, UX design, algorithmic engine development, multi-script expansion, QA, licensing, legal, and marketing — into a single transparent ledger for investors.
This is the last external capital injection prior to revenue operations.


B. Valuation & Structure

Item Detail
Pre-Money Valuation USD 48.5 million
Round Size (Target Raise) USD 12.5 million
Post-Money Valuation USD 61 million
Equity Offered ~ 20.5 % fully diluted
Instrument Preferred Equity Series D (convertible at IPO or M&A)
Lead Investor To be confirmed (Q1 announcement)
Round Close Date Final close – December 2025

C. Allocation of Funds

Category Allocation % Notes
Core Engineering & R&D 28 % Final integration of GridCore, GridIO, GridUI, HistoryManager modules.
Cloud Infrastructure & AI Ops 14 % Compute credits, metadata indexing, secure API layer.
Mobile QA & Compliance 10 % App Store & Play Store certification, penetration testing, QA lab.
Multi-Script Expansion Packs 9 % Egyptian, Mayan, Norse, Arabic, Celtic glyph modules.
Marketing & Launch Campaign 16 % Global roll-out (education + heritage sectors).
Operations & Staffing 12 % 24-month burn for core team (12 FTE + advisory board).
Legal & Licensing 6 % Intellectual property filings, cross-region licensing.
Contingency Reserve 5 % Unexpected regulatory / infrastructure costs.

D. Cumulative Cost Summary (All Phases v1.0–Launch)

Phase Duration Total Cost (USD)
Prototype + R&D Seed Q1 2023 – Q3 2023 1.2 M
Series A – Core Modules Build Q4 2023 – Q2 2024 3.4 M
Series B – Cross-Platform Architecture Q3 2024 – Q4 2024 4.1 M
Series C – Beta & QA Integration Q1 2025 – Q3 2025 5.6 M
Series D – Final Launch Round Q4 2025 12.5 M
Total Cumulative Cost 26.8 M USD

E. Exit and ROI Forecast

  • Projected Revenue (Year 1): USD 8.2 M
  • Projected Revenue (Year 3): USD 36 M
  • EBITDA Margin (Target Year 3): 29 %
  • Expected Investor ROI (5 Years): 7.4× multiple
  • Potential Exit Pathways: Acquisition (heritage AI or AR sector), IPO 2028–2029.

F. Round Notes (Final Round Declaration)

This Series D constitutes the final external financing round.
No further equity rounds will be opened prior to revenue operations.
All previous noteholders (Series A–C) convert automatically at launch.
This round secures full operational runway until profitability and marks the official close of the development phase.

Series C Round:

Martin Luther’s Ninety-Five Theses

Original:

Line Drawing:

Sometimes you have to make the thing, not just talk about it.

Let’s establish context first:
This artifact is part of an Egyptian funerary shrine, most likely a protective panel from Tutankhamun’s tomb. The vertical inscriptions between the four blue figures (which represent cobras wearing solar disks) contain hieroglyphs inscribed in gold. These are often spells or protective formulas invoking deities like Wadjet and Ra to guard the king.

Here’s how the ELS process will work conceptually before actual extraction:

  1. Grid Formation – The hieroglyphic column is extracted and indexed into a rectangular grid, e.g., 18×38 (rows × columns), depending on glyph density.
  2. Sequence Encoding – Each distinct glyph is encoded as a single character (e.g., Gardiner code or transliteration like “N5”, “D4”, “A1”).
  3. ELS Scanning – The algorithm tests all possible skip intervals (2, 3, 4…) for repeating or meaningful contiguous sequences.
  4. Lexical Matching – Detected sequences are cross-checked against known transliterations (e.g., “ANKH”, “RA”, “DJED”, “WAS”, “NEB”, etc.).
  5. Hit Visualization – Found matches are boxed in color-coded overlays (e.g., blue = divine name, gold = title, red = verb).

@Nabii As you can see, even the UoN management has agreed that this is an academia leaning algorithm.