Research, product updates, and engineering insights.
May 2026
Every AI cache on the market invalidates by time. That's the wrong unit. When a source document changes, time-based caches keep confidently serving the old answer for hours, sometimes days. Here's how Synapse fixes the silent correctness problem that's quietly limiting enterprise AI rollouts.
Read more → ProductMay 2026
Semantic caching is the single fastest way to cut AI inference costs. It's also where most teams quietly start serving wrong answers to customers. Here's how we built a cache that does both jobs at once, and why the rest of the market still hasn't.
Read more → ProductMay 2026
Most AI budgets are inflated by one quiet mistake: treating every request like it deserves the most expensive model. Synapse routes each request to the cheapest capable model, tracks the savings, and keeps quality where it matters.
Read more → ProductFebruary 2026
Every AI application today is stateless. We built the missing memory layer: semantic caching, KV-cache inference acceleration, and persistent agentic memory in one platform.
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