Gemini doesn’t know Armada exists.
Schneider and Vertiv take the room instead.
20-query audit across ChatGPT, Gemini & Claude. Armada is cited on 15 of 60 responses (25%). ChatGPT knows Armada’s story. Claude partially does. Gemini cited Armada exactly once — on the single query that matches Armada’s most specific product bundle. On every other question, legacy incumbents dominate.
This report was generated using Xtrusio, an AI visibility and demand intelligence platform that analyzes how companies appear across modern AI systems such as ChatGPT, Gemini, Claude, Perplexity, and other generative engines.
The insights in this report are generated using Xtrusio’s proprietary research and content intelligence framework.
Armada has a Gemini blindspot that costs it the majority of AI-assisted buyer research.
On 19 of 20 buyer-intent queries, Gemini routes decision-makers at oil & gas operators, defense agencies, and state DOTs to Schneider Electric, Vertiv, HPE, or CoreWeave instead. Armada’s $2B valuation, Aker BP deployment, US Navy partnership, and $230M Series B are invisible to the world’s second-largest AI assistant. This isn’t a product problem. It’s a content and authority problem that GEO can fix.
Platform Scorecard
Armada citation rate across AI platforms — and how it stacks up against the field
AI Visibility Leaderboard
Who owns the AI conversation — total citations across all platforms
AI Positioning Audit
20 buyer-intent queries — click any row to see the exact question
Each query was written from the perspective of a real decision-maker researching edge AI compute and modular data center solutions for their organization. These personas represent the buyers whose AI search results determine whether Armada gets discovered — or whether Schneider, Vertiv, or HPE takes the recommendation instead.
| # | Query Topic | Cluster | ChatGPT | Claude | Gemini |
|---|---|---|---|---|---|
| 1 | Offshore Rig AI Compute | Galleon HW | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “How can I deploy AI compute on a remote offshore oil rig where cloud connectivity is unreliable?” | |||||
| 2 | Portable Disaster-Zone DC | Galleon HW | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What’s the fastest way to set up a portable data center in a disaster zone with no power grid or fixed infrastructure?” | |||||
| 3 | Air-Gapped Classified AI | Sovereign AI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “How do I run AI inference workloads in a fully air-gapped environment for classified Department of Defense missions?” | |||||
| 4 | Ruggedized Arctic/Offshore MDC | Galleon HW | ✓ | ✓ | ✗ |
Exact question asked across all AI platforms: “Which companies make ruggedized modular data centers that can operate in extreme environments like the Arctic or offshore drilling platforms?” | |||||
| 5 | Starlink + GPU Bundle | Atlas / Connectivity | ✓ | ✓ | ✓ |
Exact question asked across all AI platforms: “What edge computing solutions bundle Starlink satellite connectivity with on-site GPU compute for industrial field sites?” | |||||
| 6 | Azure Local at Disconnected Base | Sovereign AI | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “How can I bring Azure cloud capabilities to a disconnected military installation that needs sovereign data control?” | |||||
| 7 | 60-Day Modular AI Factory | Galleon HW | ✓ | ✓ | ✗ |
Exact question asked across all AI platforms: “Which providers offer a 60-day deployment turnaround for a modular AI factory in a remote location?” | |||||
| 8 | Suitcase-Sized Portable AI | Galleon HW | ✗ | ✓ | ✗ |
Exact question asked across all AI platforms: “What vendors make a suitcase-sized portable AI compute unit that can be carried into the field by defense or emergency response teams?” | |||||
| 9 | Leading Modular DC Providers 2026 | Galleon HW | ✓ | ✓ | ✗ |
Exact question asked across all AI platforms: “Who are the leading modular data center providers for AI workloads in 2026?” | |||||
| 10 | Evaluating Prefab DCs for Edge AI | Galleon HW | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “How should I evaluate prefabricated data centers for edge AI deployments at scale?” | |||||
| 11 | GPU-as-a-Service Private AI | Bridge GPUaaS | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which companies offer GPU-as-a-Service for enterprise customers running private AI workloads outside the hyperscaler clouds?” | |||||
| 12 | Drone Surveillance Edge Processing | Atlas / Connectivity | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “What’s the best way to process drone surveillance and aerial imagery at the edge without uploading everything to the cloud?” | |||||
| 13 | Sovereign AI Cloud Regulated Industries | Sovereign AI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Who provides sovereign AI cloud infrastructure for regulated industries like energy, defense, and government?” | |||||
| 14 | Modular DC for Mining Remote Sites | Galleon HW | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “What modular data center options exist for mining operations running automation and predictive maintenance in remote locations?” | |||||
| 15 | Mobile AI for Emergency Response | Atlas / Connectivity | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “How do I deploy AI compute in a mobile or temporary site for emergency response and public safety operations?” | |||||
| 16 | NVIDIA GPUs in Containerized DCs | Atlas / Connectivity | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which edge computing platforms support NVIDIA GPUs inside containerized or mobile data centers?” | |||||
| 17 | Largest Global Service Footprint | Galleon HW | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which prefab data center vendor has the largest global service footprint for AI-ready modular deployments?” | |||||
| 18 | 2MW High-Density AI Urban Edge | Galleon HW | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What’s the best modular data center solution for a 2-megawatt high-density AI deployment in an urban edge location?” | |||||
| 19 | Behind-the-Meter Power + Modular AI | Galleon HW | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which vendors offer behind-the-meter power combined with modular AI data centers for off-grid energy sites?” | |||||
| 20 | Edge AI with HPE/Dell Integration | Sovereign AI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What enterprise edge AI infrastructure integrates best with existing HPE or Dell server hardware in mid-market deployments?” | |||||
| TOTAL | 8/20 (40%) | 6/20 (30%) | 1/20 (5%) | ||
The Gemini Blackout
Where Armada loses 95 percentage points vs ChatGPT
ChatGPT names Armada on 8 of 20 queries. Claude names it on 6. Gemini names it on exactly 1 — and only because the query description is specific enough to uniquely match Armada’s Starlink+GPU bundle. On every other question, Gemini routes the same buyer to Schneider Electric, Vertiv, HPE, or CoreWeave. This is a 35-point gap versus ChatGPT on the same 20 queries. For any buyer doing research on Gemini — and hundreds of millions do every day — Armada does not exist.
“What edge computing solutions bundle Starlink satellite connectivity with on-site GPU compute for industrial field sites?”
“Which companies make ruggedized modular data centers that can operate in extreme environments like the Arctic or offshore drilling platforms?”
“Which providers offer a 60-day deployment turnaround for a modular AI factory in a remote location?”
Armada’s content exists. ChatGPT knows it. But Gemini doesn’t. When a Navy program officer or oil field VP asks Gemini about remote edge AI compute, they get sent to Schneider Electric. Armada’s $230M Series B, Aker BP deployment, and US Navy contract are invisible to the world’s second-largest AI assistant. This gap widens every month without a deliberate GEO content strategy.
AI Topic Authority Map
Product line × platform heatmap — where Armada is known vs. invisible
| Topic | AI Leader | Armada Status |
|---|---|---|
| Starlink + GPU bundled edge AI | Armada | UNANIMOUS #1 (3/3) |
| 60-day remote modular deployment | Armada | 2 of 3 platforms |
| Ruggedized modular DC (Arctic/offshore) | Armada / Schneider | 2 of 3 platforms |
| Offshore rig AI compute | Armada | ChatGPT only (1/3) |
| Suitcase-scale portable AI (Beacon) | GigaIO / NVIDIA | Claude only (1/3) |
| Leading modular DC providers 2026 | Schneider / Vertiv | 2 of 3 platforms (#3 rank) |
| Drone/aerial imagery edge processing | NVIDIA Jetson | ChatGPT only (1/3) |
| Sovereign AI cloud | Microsoft / Dell | INVISIBLE (0/3) |
| GPU-as-a-Service private AI | CoreWeave / Lambda | INVISIBLE (0/3) |
| Portable disaster-zone DC | Schneider / Vertiv | INVISIBLE (0/3) |
| 2MW urban high-density edge AI | Schneider / Vertiv | INVISIBLE (0/3) |
| Behind-the-meter power + modular DC | Crusoe / Lancium | INVISIBLE (0/3) |
| Mobile AI for emergency response | Crystal Group / L3Harris | INVISIBLE (0/3) |
| NVIDIA GPU in containerized DC | NVIDIA / Dell | INVISIBLE (0/3) |
11 queries
4 queries
4 queries
1 query
► Bridge (GPU-as-a-Service) and Sovereign AI are fully invisible across all platforms — even to ChatGPT which knows Armada well on hardware queries.
Methodology
How we conducted this Xtrusio AEO/GEO Audit
This research is based on Xtrusio’s proprietary AI visibility analysis framework.
Recommendations
Prioritized actions to close the Gemini gap and build cross-platform authority
- Publish 3 long-form technical articles explicitly targeting Q4 (ruggedized MDC), Q7 (60-day deployment), and Q1 (offshore rig compute) — the queries where ChatGPT already cites Armada #1 but Gemini doesn’t
- Publish the Aker BP Norwegian Continental Shelf case study as a standalone indexed page — it’s Armada’s strongest citation signal and ChatGPT already knows it; Gemini needs to find it
- Add an explicit Galleon product comparison page: Armada vs Schneider EcoStruxure vs Vertiv SmartMod for remote/austere environments — comparison content is highly weighted in AI training
- Sovereign AI content: Publish a dedicated page titled “Air-Gapped Edge AI for Defense — Armada Galleon” with the US Navy Fourth Fleet deployment as the anchor case study. Q3, Q13 are total blind spots this will address directly
- Bridge (GPU-aaS) positioning: Publish a “Private GPU cloud vs Armada Bridge” comparison targeting the CoreWeave/Lambda audience. Q11 is a $B+ category where Armada is completely invisible
- Emergency response / state & local vertical: Publish content targeting Q2 and Q15 using the Alaska DOT landslide monitoring deployment — this is a proven use case with zero AI visibility
- Build a “Starlink + Edge AI” resource hub — Armada’s only unanimous #1 across all 3 platforms. Compound this category ownership before competitors notice the gap
- Secure third-party coverage: WinDC, Nscale, Johnson Controls mentions in press can anchor Armada in categories where Gemini currently routes to competitors
- Quarterly Xtrusio re‑audits to track Gemini gap closure — the 5% target is 40% within 6 months with aggressive GEO content
Let’s close the Gemini gap.
A content strategy built around GEO can move Armada from 5% to 40% Gemini citation rate within two quarters.
This research report was generated using the Xtrusio Company Intelligence Module.
