Slash your LLM token spend and orchestration overhead.
Scaling AI is brutally expensive. We optimize your context pipelines to drastically reduce token usage, while fixing the I/O bottlenecks that crash your backend during streaming.
Target: Massive OpenAI/Anthropic bills and heavy orchestration layers.
You are bleeding money on two fronts.
1. Token Bloat You are sending redundant context. Standard AI wrappers waste millions of tokens on unoptimized prompt chains and lack exact or semantic caching. You are paying providers for the same data, repeatedly.
2. Infrastructure Exhaustion Meanwhile, your backend is burning CPU. Keeping thousands of concurrent SSE (Server-Sent Events) streams open exhausts connection pools. Chunk parsing blocks your main thread, causing degraded latency.
We implement surgical caching pipelines to drop raw token volume, and replace your orchestration layer with low-level socket management. Lower API bills, resilient infrastructure.
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