geo.qaAsk any place on Earth what it looked like, and when.
geo.qa is a managed deployment of the open emem protocol. Public satellites, plus the cameras, drones and sensors you run, file into one addressed, signed record. Every answer carries the observations behind it and a receipt that verifies at emem.dev, without us.
What it is
Ask a place. Prove the answer.
Put an AI agent into production and, sooner or later, it answers a question about a place it has never observed: fluently, and wrong. geo.qa is the fix. One call returns what was observed at a place, with a signed receipt anyone can check offline, no key and no account. When the ground cannot answer, it says so, instead of guessing.
How it works
From sensor to signed fact.
For the cameras, drones and ground sensors you run, the encoder sits at the edge of capture, so what leaves is a latent, not raw footage. For satellites, geo.qa builds on the signed embeddings of the open emem.dev ledger. A decoder resolves each latent onto one shared, addressable Earth memory.
Observe
Satellites, drones, vehicle cameras and fixed CCTV, all on the same ground.
→Encode → latent
For the sensors you run, a frame becomes a latent vector on-site, so raw footage never leaves. Satellite scenes arrive already encoded, as emem.dev embeddings.
→Decode → memory
The decoder resolves each latent onto the cell lattice: one shared Earth memory.
→File a fact
Filed with its band, its time and a signed receipt. Nothing is overwritten.
→Agent cites
Your model answers with the exact observations that support it, receipt attached.
Use it
An interface agents already speak.
One call shape, shared with the open emem.dev protocol, so an agent reads public and private memory in a single answer. Every source writes into the same addressable record.
# ask the live API about a place: land cover from satellite curl -s \ "https://geo.qa/api/tool/satellite/lulc/analyze?lat=25.276&lon=55.296" \ -H "Authorization: Bearer $GEOQA_KEY" # → { "class": "water", # "coverage": { "water": 0.94, … }, # "source": "sentinel-2" }
Autonomous fleets
The vehicle’s cameras write to the memory; the car reads neighbouring cells to know what is round the corner before it sees it.
what is in the next cell right now?
Energy & infrastructure
Pads, lines and stations watched by every sensor at once. A page goes out only when independent witnesses agree.
did pressure at G-247 drop overnight?
Insurance & risk
Price and settle against what was observed, not what was claimed, and every fact arrives with its receipt.
was this parcel underwater on 04 May?
Defence & GEOINT
An owned, airgapped memory with full provenance: answers built to survive an audit, weeks later.
what changed at this site since Tuesday?
Own it
Train your own model. Keep everything.
The memory is not only something to query, it is a substrate to learn from. Every dated, multimodal fact is supervision for a model you train, own and deploy, without your data ever leaving the boundary.
# train a model on your own memory (Max plan) curl -s -X POST https://geo.qa/api/world-model/training \ -H "Authorization: Bearer $GEOQA_KEY" \ -d '{ "bands": ["optical","sar_vv","thermal","weather"], "horizon": "7d" }' # → { "job_id": "wm_…", "status": "queued" }
What never leaves
the boundary holds by design, not by policy
- ◇Raw imagery. Encoded at the edge of capture; only the latent vector moves on.
- ◇Your memory. A single tenant: your keys, your retention, your jurisdiction.
- ◇Your models. Trained and served inside your boundary. No calls home, no training on your data by us.
What you keep
provenance that survives a hostile review
- ◇Provenance. Every answer carries a signed, verifiable receipt.
- ◇Audit. Replay any decision against the exact observations it used.
- ◇Interop. The same call shape as the open emem.dev protocol.
Where it sits
Under the models, on emem.
Several layers of intelligence are converging, and each one needs something to be true about a real place. geo.qa is the ground truth they sit on.
| World & geospatial models | geo.qa | |
|---|---|---|
| Output | an inferred representation | an observed fact, dated |
| Trust | black-box inference | a signed, verifiable receipt |
| Deployment | a cloud service you call | your tenancy, airgapped |
| Time | a single snapshot | every tslot, append-only |
| Fusion | mostly one modality | many, one address |
| To build on | a fixed, pretrained model | a memory you train your own on |
World Labs’ Marble and DeepMind’s Genie generate a plausible world; they do not claim to reproduce the real one. Niantic’s Large Geospatial Model and Google’s AlphaEarth do read the real Earth, but as a model you call, not a memory you hold the keys to, cite and train on. geo.qa is the layer underneath: a dated, signed record of what was observed, that your own models can learn from.
| # | Modality | What it writes into the memory | Cadence |
|---|---|---|---|
| 01 | Satellite opticalmultispectral surface | land cover, water, change, vegetation indices | daily–weekly |
| 02 | Satellite SARall-weather radar | structure, moisture, flood, motion, through cloud | 1–6 days |
| 03 | Thermal / IRheat signature | flares, fires, equipment activity, anomalies | sub-daily |
| 04 | Drone surveycentimetre detail | close-range inspection of a single asset | on tasking |
| 05 | Vehicle camerasstreet level | what is round the corner, lane by lane | continuous |
| 06 | Fixed CCTVthe perimeter | gate, yard, fence line, occupancy | continuous |
| 07 | Ground sensorsSCADA / IoT | pressure, flow, level, vibration | seconds |
| 08 | Weather fieldsenvironment | rain, wind, temperature, soil moisture | hourly |
| 09 | AIS / vesselmaritime tracks | who is where on the water, and when | minutes |
| 10 | Field reportssigned human notes | a person's observation, attributable | on event |
| 11 | Cadastral / GISthe record of record | parcels, assets, boundaries, ownership | on change |
| 12 | Acousticsound events | alarms, gunshots, machinery, leaks | continuous |
Give your model a memory.
Stop letting it guess about the world. Start letting it cite, and train on what it cites.
geo.qa · a vortx ground decoder · emem.dev open protocol