Solving AI's Hidden Bottleneck: simdvec's Retrieval Speed Revolution

In 2026, AI agents hit a retrieval bottleneck before they hit a model bottleneck—and simdvec solves this with 4x faster vector computations than current alternatives. Real-world testing proved the impact: identical models and prompts jumped from 15% to 93% accuracy when retrieval improved, showing that infrastructure speed directly enables AI reliability. This positions vector search optimization from a performance benchmark to a production requirement for practical AI systems.