Sovereign Defence AI Brief

What Ukraine Needs
But Doesn't Have Yet

Six specific AI tools Ukraine can't buy from Palantir, can't build alone, and doesn't currently have — each buildable in weeks, each a genuine force multiplier.

6Critical gaps identified
3–10 weeksBuild time per tool
$19M–$51MTotal package cost
0 satellitesRequired

Section 01

Priority Order — Impact vs. Build Time

Ranked by lives saved per week of deployment. Start with #1, ship it, then build the rest in parallel.

1

🗺️ Unified Frontline Picture

Every unit, every fire, every enemy sighting — one shared live map. The single biggest gap. Solves friendly fire, coordination failure, and information blindness simultaneously.

4–6 weeks
$3M–$8M
2

📦 Predictive Ammo & Resupply AI

Units running out of ammunition mid-battle because resupply is reactive. AI predicts depletion before it happens and auto-generates resupply orders. Currently done on spreadsheets.

3–4 weeks
$2M–$5M
3

🚁 Drone Video Auto-Detection AI

Operators manually watch footage and call targets by voice. AI that identifies and classifies Russian equipment in real time — operator confirms. Saves critical seconds per engagement.

6–8 weeks
$5M–$12M
4

🔮 Russian Attack Prediction Model

Russia follows patterns before every attack — artillery surges, EW activation, supply convoy movements. AI trained on 3 years of Ukraine conflict data that predicts attacks 24–72 hours ahead.

6–10 weeks
$3M–$8M
5

📡 Electronic Warfare / GPS Jam AI

Russia jams GPS constantly over the front. Drones crash, artillery GPS rounds go dumb. AI that detects jamming in real time, maps the zone, and reroutes automatically.

8–12 weeks
$4M–$10M
6

🔎 Captured Intelligence Fusion

When Russian soldiers are captured or equipment seized, intelligence is processed slowly and manually. AI that cross-references captured data against intercepts, builds unit maps, finds patterns in hours not weeks.

4–5 weeks
$2M–$8M

Priority 1 — Highest Impact

🗺️ Unified Frontline Picture

The single most valuable thing you can build. Every other product plugs into this. It is literally what Palantir was invented to do.

One Map. Every Unit. Live.

Right now a Ukrainian company commander has one app. Artillery has a different system. Intelligence has a third. Drone operators have a fourth. None of them talk to each other. Friendly fire happens. Artillery fires into positions friendlies just moved into. Reinforcements go to the wrong grid. This fixes all of it.

🔴 Critical Gap — Build First
Ukraine Today — Without This
  • Company commander uses one app, artillery uses another — they never sync
  • Enemy position reported by phone call, written on paper map
  • Drone operator spots a tank, calls it in by radio, delays 3–10 minutes
  • Friendly positions unknown to adjacent units — friendly fire risk
  • No shared picture above company level — battalion commanders are blind
  • Resupply trucks get lost because nobody shared current route safety
Ukraine With This System
  • Every unit's position auto-reported via GPS tracker on vehicles + phones
  • Enemy sighting entered once — visible to every unit in the theatre instantly
  • Drone detection appears on the map in under 5 seconds
  • Artillery fire requests auto-deconflicted against friendly positions
  • Battalion commander sees every company in real time on one screen
  • Resupply routing shows live threats along every possible road
📍 GPS Unit Trackers
+
🚁 Drone Detections
+
📡 SIGINT Alerts
+
👤 Soldier Reports (App)
+
🎯 Artillery Fire Requests
+
🚛 Logistics Positions
🗺️ One Live Map — Every Level
What Gets Displayed
  • All friendly unit positions — updated every 30 seconds
  • All confirmed enemy contacts — timestamped, confidence-scored
  • Active fire missions — deconfliction zones shown automatically
  • Logistics routes — green/amber/red based on threat level
  • Drone coverage areas — who can see what right now
AI Layer on Top
  • Auto-deconfliction: blocks artillery request if friendlies in danger zone
  • Anomaly alert: unit hasn't reported in 20 min — flag for command
  • Pattern detection: enemy positions forming a line = likely assault
  • Route AI: calculates safest resupply route in real time
  • Prediction overlay: where contact is most likely in next 2 hours
How Soldiers Use It
  • Rugged tablet or phone app — works offline, syncs when connected
  • One button to report enemy contact — fills in their location automatically
  • Voice input — soldier speaks, AI transcribes and places on map
  • Works in GPS-jammed environments via dead reckoning fallback
  • No internet required — peer-to-peer mesh network between units
Tech Stack
  • Map: Mapbox GL offline tiles + custom military symbology (NATO APP-6)
  • Backend: PostGIS spatial database + WebSocket real-time push
  • Mobile: React Native app — Android (rugged Kyocera/Samsung)
  • Sync: Peer mesh via LoRa radio when no internet available
  • AI: Python microservices for deconfliction + pattern detection
$3M–$8M
Build Cost
4–6 weeks
To First Deploy
All units
Every level plugs in
~0ms
Contact-to-map delay
Why this is #1: Every other product on this list feeds data INTO this map. Build the map first, and every subsequent product becomes an additional layer on top rather than a separate system. This is the foundation of the entire sovereign stack.

Priority 3 — Tactical Edge

🚁 Drone Video Auto-Detection AI

Ukraine has thousands of drone operators. Every one of them manually watches footage and calls out targets by voice. AI changes this entirely.

Eyes That Never Tire — AI on Every Feed

A single drone operator currently watches one feed. With AI, one operator supervises 10–20 drones simultaneously. The AI watches every pixel of every feed, flags targets instantly, the human confirms and acts. The engagement cycle drops from minutes to seconds.

Drone feeds only — no satellite
Without Drone AI
  • Operator stares at screen, manually spots target
  • Calls target by voice — delay, miscommunication risk
  • Can only effectively watch 1 feed at a time
  • Night / thermal footage is hard to read — many misses
  • Target ID requires experienced operator — hard to train at scale
With Drone AI
  • AI watches all feeds simultaneously — flags the moment a target appears
  • Target auto-tagged with type, confidence, GPS coordinates
  • One operator handles 10–20 drones — 10x force multiplication
  • Night / thermal / degraded video handled equally well
  • Junior operators as effective as veterans — AI carries the expertise
What It Detects
  • Tanks — classified by type (T-72, T-80, T-90, T-14)
  • APCs, IFVs, wheeled vehicles — type and direction of travel
  • Artillery systems — Grad, Msta, howitzers, mortars
  • Personnel — count, formation type (patrol vs assault)
  • Air defence systems — SA-series, Buk, Pantsir — high priority flag
  • Supply depots, ammo storage — thermal signature detection
How It Works
  • Fine-tuned YOLO v10 or RT-DETR on Russian military imagery
  • Training data: 3 years of Ukraine conflict drone footage — richest dataset on Earth
  • Runs on-device (edge GPU on ground station) — no cloud needed
  • Detection appears on the Unified Frontline Map automatically
  • Confidence score shown — operator sees "T-72, 94% confident, grid 4782"
FPV Kamikaze Integration
  • For FPV attack drones: AI guides final approach to target centre
  • Operator steers to target area — AI takes terminal guidance
  • Works in GPS-jammed environments (uses visual guidance not GPS)
  • Reduces operator workload during high-stress terminal phase
  • Human always in the loop — AI assists, doesn't decide
Unique Ukraine Advantage
  • Ukraine has the world's largest labelled military drone video dataset
  • 3 years of real combat footage — no other country has this
  • Models trained on this data are uniquely accurate for this threat environment
  • Each new mission generates more training data — system gets smarter daily
$5M–$12M
Build Cost
6–8 weeks
To First Deploy
10–20x
Operator Leverage
<1 sec
Detection Latency

Priority 2 — Saves Lives Weekly

📦 Predictive Ammo & Resupply AI

Units run out of ammunition mid-battle. Not because there isn't enough ammo — because nobody knew it was running out until it was gone. This is a pure data problem.

Never Run Dry — Logistics That Sees the Future

Every unit reports its ammo consumption. AI tracks consumption rate, calculates time-to-zero, and automatically generates resupply orders before the unit hits critical levels. Works for ammunition, fuel, food, medical supplies, spare parts — anything consumable.

Pure data — no hardware needed
📊 Unit Consumption Reports
+
🚛 Current Stock Levels
+
⚔️ Combat Intensity Data
+
🗺️ Route Safety (from map)
⏰ Resupply Before It's Needed
What It Predicts
  • Time-to-zero for every consumable at every unit
  • Adjusts prediction based on current combat intensity
  • Accounts for resupply travel time — orders early enough for the truck to arrive
  • Prioritises: critical ammo types vs. nice-to-have
What It Automates
  • Generates resupply request automatically — commander approves or overrides
  • Optimises delivery routing — groups nearby units into one truck run
  • Flags when strategic reserves are being drawn down too fast
  • Gives national-level commanders a true picture of overall readiness
Medical Supply Module
  • Tracks blood type stocks at every field hospital
  • Predicts casualty rates from combat intensity — pre-positions supplies
  • MEDEVAC routing: nearest facility with correct blood type and capacity
  • Surgical team scheduling against predicted casualty load
$2M–$5M
Build Cost
3–4 weeks
To Deploy
Fastest ROI
of all 6 tools
All supplies
Ammo · Fuel · Medical
Quickest win: This is the fastest to build, easiest to demonstrate value, and most universally applicable. Every military unit in the world has this problem. A working demo on Ukrainian logistics data takes 2–3 weeks and immediately shows lives saved.

Priority 4 — Strategic Edge

🔮 Russian Attack Prediction Model

Russia follows observable patterns before every major attack. They've been doing it for 3 years. That data exists. Nobody has trained an AI on it yet.

24–72 Hour Warning Before Every Russian Assault

Before every Russian attack: artillery surges on specific patterns, electronic warfare activates at certain nodes, supply convoys move to forward depots, communications traffic increases, drone reconnaissance intensifies. Each signal alone means little. Together they predict an attack with 70–85% accuracy — days before it happens.

3 years of conflict data — unique dataset
💥 Artillery Fire Patterns
+
📡 EW Activation Events
+
🚛 Supply Convoy Movements
+
📻 Radio Traffic Volume
+
🚁 Russian Drone Activity
🔮 Attack Probability Map — 72hr ahead
Pre-Attack Signals Identified
  • Artillery: shift from harassing fire to systematic suppression 36–72hr before assault
  • EW: GPS jamming intensifies in the specific attack corridor 12–24hr before
  • Logistics: fuel and ammo convoys to specific nodes 48–96hr before
  • Drone recon: intensive ISR over target area 24–48hr before
  • Radio: command net traffic spike indicating orders being issued
Model Output
  • Heatmap overlay on the Unified Frontline Map
  • Per-grid probability: "74% chance of assault in this 5km grid in next 48 hours"
  • Confidence interval and which signals are driving the prediction
  • Commander can request explanation: "Why is this sector flagged?"
  • Track record shown: model's hit rate and false positive rate
Why Ukraine's Data Is Unique
  • 3+ years of documented Russian attack patterns — no other dataset exists
  • Thousands of events: assaults, feints, diversionary attacks — all labelled
  • Includes failed attacks — what patterns didn't lead to assault
  • Continuous learning: every new event refines the model in real time
$3M–$8M
Build Cost
6–10 weeks
To First Model
72 hours
Warning Window
70–85%
Target Accuracy

Priority 5 — Force Multiplier

📡 Electronic Warfare & GPS Jam Detection AI

Russia's EW is Ukraine's #1 drone killer. Not bullets — jamming. An AI that maps, tracks, and routes around jamming zones in real time turns Russia's biggest advantage into a manageable problem.

See the Invisible — Map Every Jamming Zone Live

Russian EW systems emit characteristic radio frequency signatures. Ground sensors detect these passively. AI correlates sensor readings across the network to locate the jammer, predict its coverage zone, and automatically route drones and GPS-guided munitions around it — before they fly into the dead zone.

RF sensor network — no satellites
Detection Network
  • Passive RF receivers — cheap SDR (Software Defined Radio) devices, $200 each
  • Deployed at multiple points along the front — 10–20 sensors covers a 100km sector
  • TDOA (Time Difference of Arrival) geolocation — triangulates jammer position
  • Identifies jammer type from RF fingerprint — known Russian EW systems catalogued
AI Analysis Layer
  • Continuously maps active jamming zones as they switch on/off/move
  • Predicts effective jamming radius based on system type and terrain
  • Overlays on Unified Frontline Map — pilots see the no-go zones
  • Alerts when a new EW system activates — often pre-attack indicator
Automatic Rerouting
  • Drone flight planning: calculates GPS-safe corridors automatically
  • Artillery GPS fuze: switches to inertial guidance before entering jammed zone
  • Comms: automatically shifts radio frequencies away from jammed bands
  • Alerts operator before drone enters jamming zone — not after it crashes
$4M–$10M
Build Cost
8–12 weeks
To Deploy
~$200
Cost per RF sensor
Real-time
Jam zone updates

Priority 6 — Intelligence Edge

🔎 Captured Intelligence Fusion AI

Every captured Russian soldier, seized phone, and captured document contains intelligence. Currently processed slowly by hand. AI that processes, cross-references, and acts on it in hours instead of weeks.

Turn Every Capture Into an Intelligence Cascade

A captured soldier knows his unit, his commanders, his positions, his orders. A seized phone contains contacts, messages, locations. A captured document reveals logistics, plans, call signs. AI that instantly cross-references all of this against every other piece of known intelligence — and finds what was previously invisible.

Pure data fusion — Palantir's core capability
📱 Seized Phone Data
+
📋 Documents / Orders
+
👤 POW Interview Notes
+
📡 Known SIGINT Database
+
🗺️ Known Unit Positions
🔗 Full Unit Intelligence Picture
Phone Data Extraction
  • Extracts contacts, messages, photos, location history automatically
  • Cross-references phone numbers against known Russian military numbers database
  • Location history shows where the soldier's unit has been operating
  • Photos often contain unit insignia, equipment, other soldiers — all extracted
Entity Resolution
  • Links the captured soldier's name to radio intercepts where their name appeared
  • Connects their unit to known positions on the frontline map
  • Identifies their commanders — who else is in that chain of command
  • Builds a picture of the entire unit from a single capture event
Actionable Output
  • "This soldier is from 64th Motor Rifle Brigade, currently in this grid"
  • "His phone contacted this number — which matches a known FSB handler"
  • "3 other members of his unit were captured last month — here's what they said"
  • All findings automatically pushed to relevant commander screens
$2M–$8M
Build Cost
4–5 weeks
To Deploy
Hours
Processing vs weeks today
100%
Cross-referenced automatically

Section 08

Build Plan — All Six in Parallel

With AI-assisted development and a focused team, all six tools can be built simultaneously. Ship the Unified Picture first — everything else plugs into it.

Tool Week 1–2 Week 3–6 Week 7–12 Cost
🗺️ Unified Picture Map backend + GPS ingestion Mobile app + unit reporting ✓ Live — AI deconfliction added $3M–$8M
📦 Ammo AI Data model + consumption API ✓ Live — prediction model running Medical module added $2M–$5M
🚁 Drone AI Dataset prep + model training Edge deployment + UI ✓ Live — feeding into Unified Map $5M–$12M
🔮 Attack Prediction Historical data ingestion Model v1 + backtesting ✓ Live — overlay on Unified Map $3M–$8M
📡 EW Detection SDR sensor network design Deploy sensors + triangulation ✓ Live — jam zones on Unified Map $4M–$10M
🔎 Captured Intel Entity graph + intake app ✓ Live — cross-reference engine Phone extraction module $2M–$8M
Team needed: 25–35 engineers total — 8 backend, 5 mobile/frontend, 6 ML engineers, 4 DevOps/security, 4 domain experts (ex-military), 2–3 on-the-ground Ukraine liaisons. With AI coding tools (Cursor, Copilot), this team outputs 3–5x a pre-AI team of the same size. All six tools in 10–12 weeks is realistic.

🇺🇦 The Ukraine Proposition

Ukraine is fighting the most AI-documented conventional war in history. They have the data, the urgent need, and the moral clarity. What they don't have is the software layer to turn that data into battlefield advantage. These six tools, built in 10 weeks, would make Ukraine's military the most AI-capable non-superpower force on Earth — and create the most powerful live demonstration of sovereign defence AI the world has ever seen.

$19M–$51M
Total package
10–12 weeks
All six tools live
0 satellites
Required
30+ contracts
Follow-on from other govts
Reports
🛰️ Project MAX — Palantir Takedown 🔍 Palantir Service Offerings 💰 Replication Targets Sovereign Stack Deep Dive 📡 Satellite Brief 🔭 Real-Time Satellite Vision 🌍 Palantir Access Map 🟢 No Satellite Stack 🇺🇦 Ukraine Defence AI 🌏 Singapore & Gulf Analysis 🧠 The Product They Cant Refuse 🎯 Swarm Brain — Ukraine 🔮 Predictive Offensive Intel 👁️ Autonomous Border Intel 🛡️ Orb Defence — UAE 3D AI Grid