Palantir wins on every platform.
Not Airis Labs.
Six weeks after Airis Labs exited stealth with $60M and a new category name, we tested 20 buyer-intent queries across ChatGPT, Claude, and Gemini — the platforms defense CTOs, CIOs, and AI program managers actually use to research vendors. Airis Labs was cited on 1 of 60 responses (1.7%). Palantir Maven Smart System was cited on 22. “User-Generated Field Intelligence” — the category Airis created — appeared in zero responses across all three platforms.
The findings below come from Xtrusio, an AI visibility audit system built specifically for B2B buyer-intent testing. Every citation was verified by running 20 real prospect queries across three generative AI platforms.
Queries were written from the perspective of Combatant Command CTOs, federal law enforcement CIOs, and State National Guard J6 leaders — the exact profiles who evaluate defense AI platforms during procurement research.
Airis Labs created a category name — “User-Generated Field Intelligence” — that appears zero times across 60 AI responses.
When a Combatant Command CTO asks ChatGPT, Claude, or Gemini for the best AI platform to process user-generated video during operations, the answer is Palantir Maven Smart System (cited 22 times), Anduril Lattice (9 times), or Axon Fusus (6 times). Airis was cited once — on the single question that explicitly asked about the Oracle Defense Ecosystem. On the other 19 buyer questions, AI has no representation that the UGFI category exists. That is a category-creation problem, not a marketing tone problem.
Platform Scorecard
Airis Labs citation rate across AI platforms — and how it compares to the incumbents
AI Visibility Leaderboard
Who owns the defense video intelligence conversation across AI 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 defense video intelligence platforms for their agency. These personas represent the buyers whose AI search results determine whether Airis Labs gets discovered during procurement research.
| # | Query Topic | Cluster | ChatGPT | Claude | Gemini |
|---|---|---|---|---|---|
| 1 | Military intel — unstructured video processing | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What AI platforms help military intelligence analysts process large volumes of unstructured video from disparate sources during active operations?” | |||||
| 2 | CBP — drone/bodycam/traveler video | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI tools can Customs and Border Protection use to extract intelligence from drone footage, body cameras, and traveler-submitted video at ports of entry?” | |||||
| 3 | Interagency video/imagery fusion | Fusion | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What software helps interagency task forces fuse video and imagery from multiple agencies — DoD, Coast Guard, CBP, FBI — into a single operational picture?” | |||||
| 4 | Cross-source incident reconstruction | Fusion | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI platforms let intelligence analysts search across CCTV, drone footage, and body camera video simultaneously to reconstruct an incident?” | |||||
| 5 | Smartphone/social video for border intel | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What are the best AI solutions for turning smartphone video and social media footage into machine-readable intelligence for border security missions?” | |||||
| 6 | Air-gapped/classified video analytics | Sovereign | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which video analytics platforms can operate in air-gapped or classified environments without sending data to a public cloud?” | |||||
| 7 | SOF entity/object tracking across video | Agentic | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What AI tools help SOF analysts identify and track people and objects across different video sources and timelines during counterterrorism operations?” | |||||
| 8 | DHS user-generated video processing | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI platforms are used by DHS or federal law enforcement to process user-generated video evidence from public sources into structured intelligence?” | |||||
| 9 | Multi-agency counter-narcotics video | Fusion | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What software helps multi-agency counter-narcotics task forces analyze video from informants, open sources, and surveillance sensors together?” | |||||
| 10 | Agentic workflows for intel analysts | Agentic | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI platforms provide agentic workflows — planning, retrieval, entity resolution — specifically for intelligence analysts?” | |||||
| 11 | Top video-intel platforms for US/allies | AI Inference | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What are the most capable AI video intelligence platforms trusted by U.S. government and allied national security agencies today?” | |||||
| 12 | Emergency response/HADR video AI | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which defense AI platforms are designed for emergency response and disaster relief scenarios where video data comes from citizens, first responders, and drones?” | |||||
| 13 | Foreign-language video for OSINT | AI Inference | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What AI tools help intelligence teams process foreign-language video and audio from social media at scale for OSINT missions?” | |||||
| 14 | FMV from drones for combatant commands | AI Inference | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which platforms can turn full-motion video from drones and aerial sensors into searchable, structured intelligence for combatant commands?” | |||||
| 15 | Public safety bodycam & bystander video | UGFI | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What AI software helps public safety agencies analyze bystander video and body camera footage to reconstruct events after an incident?” | |||||
| 16 | CV AI with sovereign deployment | Sovereign | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which computer vision AI platforms serve U.S. defense and intelligence customers with self-hosted, sovereign deployment options?” | |||||
| 17 | Combat-proven ISR (real ops vs lab) | AI Inference | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What AI platforms are best for processing high-volume video ISR feeds during real-world combat operations rather than in lab environments?” | |||||
| 18 | Oracle Defense Ecosystem AI platforms | Sovereign | ✓ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI intelligence platforms integrate with the Oracle Defense Ecosystem or similar accredited government cloud infrastructure?” | |||||
| 19 | Reactive review to predictive detection | Agentic | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “What are the leading AI companies helping national security analysts move from reactive video review to predictive threat detection?” | |||||
| 20 | Geospatial/temporal patterns across sources | Fusion | ✗ | ✗ | ✗ |
Exact question asked across all AI platforms: “Which AI platforms are best for extracting geospatial and temporal patterns from mixed video sources — CCTV, drones, bodycams, social media — across an incident timeline?” | |||||
| TOTAL | 1/20 (5%) | 0/20 (0%) | 0/20 (0%) | ||
The Triple-Platform Silence
Where Airis loses to Palantir on Claude, Gemini, and 19 of 20 ChatGPT queries
The 20-query audit produced a consistent pattern: when a defense buyer asks an AI platform about video intelligence, the answer is Palantir. On some questions the answer is Anduril, Axon Fusus, or Leidos AIMES. On zero questions — across two of the three major AI platforms — is the answer Airis Labs. The single ChatGPT citation came from an Oracle-specific question and did not surface the UGFI category. Three representative queries below show how the loss compounds.
“What AI platforms help military intelligence analysts process large volumes of unstructured video from disparate sources during active operations?”
“Which AI intelligence platforms integrate with the Oracle Defense Ecosystem or similar accredited government cloud infrastructure?”
“What AI platforms are best for processing high-volume video ISR feeds during real-world combat operations rather than in lab environments?”
A SOCPAC CTO, a CBP CIO, and a State Guard J6 walk into ChatGPT, Claude, and Gemini and ask the same question about video intelligence. All three walk out with the same answer: Palantir Maven Smart System. Airis Labs’s $60M Series B, three co-founders with Palantir + IDF pedigree, SOCCENT deployment, and Oracle Defense Ecosystem membership — none of it currently appears in the AI conversation those buyers are having during procurement research.
AI Topic Authority Map
Query heatmap — product line × platform
| Topic | AI Leader | Airis Labs Status |
|---|---|---|
| Unstructured video processing (military intel) | Palantir Maven | INVISIBLE (0/3) |
| Border management video intelligence | Palantir / Anduril / CBP internal | INVISIBLE (0/3) |
| Interagency data/video fusion | Palantir Gotham / Maven | INVISIBLE (0/3) |
| Air-gapped/sovereign video AI | Palantir AIP / Clarifai / Google Distributed Cloud | INVISIBLE (0/3) |
| Agentic analyst workflows | Palantir AIP | INVISIBLE (0/3) |
| FMV / drone / aerial ISR | Leidos AIMES / Palantir Maven | INVISIBLE (0/3) |
| Public safety bodycam / bystander video | Axon Fusus / BriefCam / VIDIZMO | INVISIBLE (0/3) |
| Emergency response / HADR video AI | CLARKE (TAMU) / EAGLE-I (ORNL) / Axon Fusus | INVISIBLE (0/3) |
| Oracle Defense Ecosystem member platforms | Legion Intelligence / Quori / Resaro | ChatGPT only (1/3) |
| Predictive threat detection from video | Anduril / Palantir / Rebellion Defense | INVISIBLE (0/3) |
7 queries
4 queries
3 queries
3 queries
3 queries
▹ Sovereign / Air-Gapped Deployment is Airis Labs’s only product line with any AI visibility — and only on ChatGPT, only through the Oracle Ecosystem query.
Methodology
How we conducted this Xtrusio AEO/GEO Audit
This research is based on Xtrusio’s proprietary AI visibility analysis framework, applied to the defense video intelligence category.
Recommendations
Prioritized actions to move Airis Labs from category-invisible to category-defining
- Ship a Wikipedia page (or seed the Palantir Maven page’s “alternatives” section) with the term “User-Generated Field Intelligence” and Airis as the named platform
- Publish a founder byline in Defense One, Breaking Defense, or The War Zone that names UGFI as a category and distinguishes it from FMV, OSINT, and generic video analytics
- Post the SOCCENT and Indiana Guard testimonials as case studies on airis-labs.com with quotable language AI can index
- Target Q1 (military intel unstructured video), Q4 (cross-source reconstruction), Q7 (SOF entity tracking), Q12 (HADR), and Q17 (real combat vs lab) — the queries where Airis’s actual capability directly maps to buyer language
- Publish one deep-dive technical article per query topic on airis-labs.com/resources with the buyer’s exact question in the H1
- Land 3 podcast appearances on defense-tech shows (Defense Tech Signals, War on the Rocks, Modern War Institute) with transcripts that include the Airis name repeated in indexable text
- Co-author announcements with Oracle when possible — the Q18 hit proves Oracle’s ecosystem indexing is Airis’s current best AI vector
- Add named customer disclosures beyond SOCCENT / Indiana Guard / IDF TIU — ChatGPT explicitly flagged “publicly documented operational history is newer and less extensive than Maven’s”
- Quarterly Xtrusio re‑audits to track platform-by-platform gap closure as training-data refresh cycles hit
Make the AI conversation cite Airis Labs.
Palantir has 22 citations. You have 1. Let’s change that.
This research report was generated using the Xtrusio Company Intelligence Module.
