Cut LLM Costs up to 60% - Twelve-Layer Optimization

Twelve stacked layers. Up to 60% saved. No added latency.

Cut LLM spend up to 60% – without adding a millisecond to the hot path.

LLM bills balloon from repeated prompts, oversized context, and premium models doing cheap work. DeepintShield stacks twelve inline optimizers – caching, coalescing, routing, compression, and reasoning throttling – that cut spend while a built-in drift sampler proves quality holds against an un-optimized baseline. Every saved token reconciles into one workspace-isolated ledger your finance team can read.

Key Features

Semantic + Prompt Caching

In-process exact and semantic caching plus provider native prompt-cache passthrough (Anthropic / Bedrock / OpenAI / Gemini).

Request Coalescing

Sharded single-flight dedup, with optional fuzzy-embedding matching, collapses identical concurrent calls into one upstream request.

Cascade Routing (beta) & Reasoning Throttling

Downshift easy prompts to cheaper models and cap reasoning effort on o-series / extended-thinking / Deep Think.

Compression & RAG Trimming

Advanced Prompt Compression Algorithms and Re-Ranker trimming shrink oversized context in a self-hosted sidecar.

Drift-sampled Quality

Every optimizer A/Bs a slice of traffic un-optimized, so you can prove the savings didn’t cost quality.

One Savings Ledger

Seven-source, model-accurate attribution reconciles every saved token and dollar per workspace.

LLM cost optimization gateway, semantic caching for LLMs, prompt caching, prompt compression, cascade model routing, reasoning effort throttling, request coalescing

Start For Free Start For Free Start For Free

Cost Optimization

"Govern, Secure and Control every AI Action"