Turn a view from above into a decision on the ground. AI-assisted analysis for the assets, landscapes and operations you need to understand.
The image is the beginning.
The intelligence is what comes next.
AirQtel brings aerial observation, data processing and AI-assisted interpretation into one assessment workflow. Looking Glass connects what you can see with the context you need: asset records, earlier observations and the question your team is trying to answer.
Find the changes that deserve attention. Understand the uncertainty. Give the right people a clear next step.
See how the analysis worksCapture the right evidence.
Put change into context.
Prioritize the next move.
Explore how an observation becomes a reviewable finding. Switch scenarios, reveal the analysis layer and inspect the evidence.
INTERACTIVE EXAMPLE · NOT A LIVE ASSESSMENT
AI suggests where to look. Evidence determines what to conclude.
Our review principlesOur AI workflow is designed to connect visual observations with operational context. The result is a finding your team can question, verify and use.
Computer vision helps surface visible assets, land-cover patterns and candidate anomalies. Analysts check these against image quality, coverage and the question being asked.
OBJECTS / PATTERNS / ANOMALIESCompare aligned observations while accounting for viewpoint, season, shadows and capture conditions. A difference in pixels is a lead to investigate, not automatic proof of damage.
TEMPORAL COMPARISON / QUALITY CHECKSBring imagery together with inspection histories, asset registers, weather records and operating requirements. AI helps reconcile conflicting evidence and identify the information still missing.
MULTIMODAL ANALYSIS / EVIDENCE LINKSConsider the consequence of a finding, the asset's importance and the strength of the evidence. Draft a review queue, targeted inspection brief or follow-up task for the responsible team.
RISK TRIAGE / HUMAN APPROVALConnect the observation, supporting sources, reviewer decision and recommended action in one assessment record. Revisit the conclusion when new evidence arrives.
SOURCE RECORDS / REVIEW HISTORYStart with the operational question, then design the observation and analysis around it.
COMMERCIAL ASSET ASSESSMENTBuild a consistent visual record of large sites and corridors. Identify candidate changes around access routes, structures and asset boundaries, then focus the next inspection.
A georeferenced review map, prioritized findings and an inspection handoff.
An assessment combines collection planning, imagery processing and interpretation. Scope, acquisition options and delivery timing are agreed for each project.
Set the area of interest, assets, baseline and acceptance criteria. Identify who will use the result and what they need to decide.
Plan suitable aerial collection or supplied imagery. Confirm permissions, capture conditions and the sensor data the task requires.
Process the imagery, surface candidate findings and compare relevant context. Keep uncertainty visible through analyst review.
Deliver annotated findings, supporting sources and recommended follow-up in a format your operating team can use.
*Export formats, system connections and acquisition specifications are agreed in the project scope.
AI should make a complex scene easier to understand, without making the conclusion harder to question.
Distinguish what the image shows from what the analysis infers. Keep source dates, coverage and known limitations with the finding.
High-consequence findings need qualified review. Imagery alone cannot certify structural safety or establish the cause of damage.
Define the authorized area and collection purpose. Focus on assets and environmental conditions, not personal identification.
Define access, retention, transfer and deletion requirements in the engagement. Confirm controls before sensitive data is shared.
Start with a focused assessment or plan recurring observations. The service follows the decision cadence of your business.
For a baseline, condition review or event-driven investigation. Agree the evidence required and a clear set of deliverables.
For portfolios and landscapes that change over time. Establish a baseline, compare subsequent observations and track follow-up.
Project-based proposals in USD. Scope depends on geography, permissions, source data, analysis requirements and review needs.
An engagement can combine aerial acquisition planning, imagery processing and AI-assisted analysis. The proposed output is an assessment package with annotated observations, supporting evidence and recommendations for review. The exact scope is agreed before work begins.
The focus is the observation and intelligence service rather than a standalone aircraft or camera. Platform selection depends on the area, permissions, capture requirements and available collection partners.
The intended workflow uses computer vision to surface candidate findings and contextual reasoning to connect them with records and prior observations. AI-assisted conclusions remain reviewable; an analyst checks consequential findings before they become operational recommendations.
Existing imagery, asset registers and inspection records can be considered during scoping. Suitability depends on permissions, timestamps, georeferencing, resolution and completeness. Integration and export formats must be confirmed for the project.
No universal guarantee applies. Delivery latency and collection suitability depend on the platform, sensor, transmission environment, weather and permissions. Thermal or multispectral analysis requires suitable calibrated source data; an ordinary photograph cannot substitute for it.
Access, retention, processing location and transfer requirements should be agreed before data exchange. Please do not include confidential documents or precise sensitive-site details in a website project brief.
Start with a location, an operational question
and the decision you need to make.