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The Challenge
Planning Faster Than Reality Changes
When the clock is already running
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US personnel must evacuate a country within 72 hours.
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A natural disaster devastates a region and thousands need immediate support.
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Weather shifts mid-mission and the tanker rendezvous needs to move.
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An analyst needs to assess activity across 200 airfield images before tomorrow's brief.
In each case, the mission isn't static, and someone has to keep up with what's possible as conditions change.
The Gap in Traditional Tools
For years, mission planning tools in the DoW have been built for perfectly defined missions; they assume planners arrive with complete information and need help optimizing a known mission.
In reality, planners need help understanding what's possible, and then need to keep replanning as reality evolves.
The consequences compound: missions slip when constraints surface late. Suboptimal plans fly because there wasn't time to explore alternatives. And once execution begins, there's no system watching for when the plan no longer matches reality.
The real bottleneck isn't computation. It's iteration speed—from first contact through mission complete.
Vista Sora Approach
Four Phases of Mission Support
Enter at any point in the mission lifecycle. Get useful output immediately. Iterate as clarity develops or as the situation changes.
Phase 1: Preplanning
Explore the option space before constraints are known. Understand what's possible before committing to an approach.
Phase 2: Planning
Validate approaches against constraints. Generate optimized options with full reasoning chains.
Phase 3: Execution & Replanning
When parameters change mid-mission, regenerate alternatives in seconds, not hours.
Phase 4: Monitoring
Agents that watch missions in progress and surface when plans no longer match reality.