[ Section 00 - Introduction ]
We shipped something that works. People are using it. But we're not done - we're just getting started. This is an honest look at where we're headed and what it'll take to get there.
[ Section 01 - Current Status ]
FOUNDATION LAID
Orca started in Miami. Dense urban environment, messy street-level reality, enough complexity to stress-test everything. It worked. The benchmarks validated our approach, and more importantly, people found it useful.
Now we've expanded into Europe. Multiple metros, different architectural styles, new visual vocabularies. The model is learning to generalize without forgetting what it already knows.
[ Section 02 - Strategic Priorities ]
OBJECTIVES
Expansion
Widening the map. More European metros, Asian cities, and strategic coverage in Latin America.
Reasoning
Making model explanations feel more natural - closer to how a human geoguesser thinks.
Access
Clean APIs, good documentation, and simple demos. No PhD required to integrate.
Speed
Reducing inference latency to sub-second response times for real-time video analysis.
[ Section 03 - The Hard Parts ]
SCALING COMPLEXITY
Expansion isn't just adding more training data. Every new city introduces new edge cases, new architectural styles, and new ways that visual cues can mislead the model. Tokyo alleys don't look like Paris boulevards. Both need to work.
"The future isn't predetermined. It's shaped by the people who show up and do the work."
[ Section 04 - Core Philosophy ]
OPEN INTELLIGENCE
We believe geolocation AI shouldn't be locked away behind expensive software and niche expertise. It should be accessible to anyone with an image and a question. That's why we're building this in the open.
Live System
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