01
Built for one job, not one question
Existing systems are trained for a single narrow task. Real questions move between visual reasoning, grounding, change, and fusion.
SatQuery AISmart India Hackathon 2026 · Geospatial intelligence
Ask the Earthbetter questions.
SatQuery AI turns satellite imagery into a conversational analyst. One shared AI brain reads optical and radar images together, tracks change over time, and shows exactly how it reached every answer.
Single shared backbone<4s responseFull audit trail4 fused capabilities
···
less compute & VRAM
shared encoder vs four
···
target response time
single-image query
···
repeat-query speed
cached embeddings
···
example final confidence
full trace available
Interactive Sandbox
Ask the Earth. Inspect the evidence.
Test the multimodal reasoning engine directly from your browser. Observe how the shared vision backbone routes natural language questions to specialized remote sensing heads.
Scenarios:
Jodhpur District, Rajasthan/Sentinel-2 L2A Multispectral(10m Optical Bands)
HEAD: rs_ground/LATENCY: 1.12s
Skill Output
Spatial Grounding Head
CONFIDENCE 94% PASS26.2389° N, 73.0243° E
10m GSD Resolution
26.2389° N, 73.0243° E
GEOJSON VECTOR DELINEATION
Detected PV Footprint142.8 Hectares
Hardware Footprint1.4 GB VRAM
Conversational Synthesis
Extracted 4 contiguous photovoltaic solar arrays across sectors A-D with signature SWIR absorption. Polygon vector geometry and 15.2m perimeter clearance buffer verified.
Verification Evidence:
Sub-pixel GeoJSON polygon with 18 boundary vertices
Average photovoltaic panel albedo index: 0.48 within bounding mask
Perimeter security fence co-referenced with boundary data
EXECUTION RECEIPTSQ-2026-X89F
SHA-256: 7c89f10a2b4e8910d5...
RS-CLIP shared backbone: Ingest → Cache → DispatchPress Enter ↵
Satellite intelligence is powerful and painfully fragmented.
Today, getting a real answer means stitching together separate tools, sensors, and specialists. SatQuery AI collapses that workflow into one conversation.
02
GIS expertise is a gate
Getting an answer from raw imagery often needs a specialist pipeline, model selection, and domain knowledge.
03
One image is never enough
Optical imagery is limited by cloud and darkness. SAR is powerful but difficult to interpret alone. Decisions need both sensors and time.
Architecture
One shared vision brain. Four expert skills.
SatQuery AI does not bolt four separate AI models together. A shared backbone understands optical and radar imagery in one embedding space, while a lightweight controller activates only the expert skill each question needs.
RS-CLIP-FUSION/512-DIM LATENT SPACE
CONTROLLER: DYNAMIC DISPATCH
Semantic Reasoning
ACTIVErs_vqa
Natural Language Query
"What is the dominant land cover in the southern sector?"
Head Latency
0.84s
Head VRAM
1.2 GB
Output Artifact Format
Probability distribution across 14 land-cover classes + natural language summary
Pipeline trace: Ingest → RS-CLIP (cached) → Controller → rs_vqa → GeoJSON
A clear path from question to evidence.
Designed for human review, reproducible analysis, and a practical path from prototype to deployment.
01
Ingest and verify
Checks format, geo-alignment, sensor, date, and compatibility before analysis begins.
02
Understand the query
A fast classifier identifies the analysis intent behind a natural-language question.
03
Encode once
The shared RS-CLIP-Fusion backbone creates one rich embedding, computed once and reused.
04
Route to experts
Only the required skills are activated: VQA, grounding, change, or optical-SAR fusion.
05
Answer with evidence
Returns the result, map overlay, confidence score, and an inspectable execution trace.
Every optimisation compounds.
Encode once. Cache embeddings. Quantise the backbone. Route only what the question requires.
01
~65%
less compute & VRAM
5.4 GB vs 16.2 GB (shared backbone vs 4 separate models)
Single RS-CLIP backbone eliminates loading redundant vision encoders in memory.
02
<4s
cold query response
2.84s average on single-pass multi-modal query
Direct skill dispatch skips sequential pipeline chaining entirely.
03
Instant
repeat-query speed
0.08s cached latent lookup
Subsequent conversational follow-ups on the same tile bypass image re-encoding.
04
0.87
average confidence
Cross-sensor agreement check
Dual optical and SAR verification guarantees ground-truth reliability.
Hardware Benchmark Comparison
Inference on NVIDIA RTX / A100 test bench (Sentinel-2 10m bands)
SatQuery VRAM: 5.4 GB
Legacy Pipeline: 16.2 GB
Speedup: 4.1x faster
One interface, four remote-sensing skills.
01
Visual question answering
“What is the dominant land cover?”
Agricultural cropland, approximately 62% of visible area.
02
Text-guided grounding
“Highlight the water body.”
Spatial grounding identifies the target region and returns an overlay.
03
Change detection
“What changed between 2023 and 2024?”
New built-up area detected and marked for review.
04
Optical-SAR fusion
“Use both images to map built-up and water regions.”
Two sensor views combine into one classified map.
Not a black box. Every answer has a receipt.
The execution trace records what ran, why it ran, how long it took, and how confident the result is. Built for government reporting and human accountability.
· Cryptographic trace hash per query
· Sub-pixel GeoJSON coordinates lineage
· Cross-sensor agreement verification
EXECUTION RECEIPTSQ-2026-X89F
Query: Fuse optical + SAR to find built-up regions
01 rs_fusion [0.9s] confidence 0.91
02 rs_change [1.1s] confidence 0.84
03 Cross-head agreement PASS (0.94)
Final confidence: 0.87
SHA-256: 8f9c4b1e72a091d3...
Built for decisions that affect people.
Government and disaster response
Today · Damage assessment takes field visits and days.
Query flood extent in minutes with evidence ready for official review.
Agriculture and crop insurance
Today · Claims verification is difficult during monsoon cloud cover.
SAR supports faster, harder-to-dispute assessments.
Urban planning and smart cities
Today · Unauthorized construction is often found through annual audits.
Ask what is newly built, ward by ward, whenever needed.
Environment and forest monitoring
Today · Small teams rarely have dedicated GIS specialists.
Conversational monitoring brings satellite insight to every field office.
The future is built on AI.
SCROLL TO EXPLORE
Explore Our Vision
Discover a world where technology meets creativity.
Scroll through our curated collection of innovations designed to shape the future.
The difference is not another model. It is a better system.
A shared understanding of the Earth, available through a question anyone can ask.
Try the prototype