What is Sleev

Sleev cuts your token spend by 30% to 80% per session without changing your agentic stack. Our edge: keep the signal, cut the noise, spend fewer tokens getting the same or better work done.

The problem

Agent sessions are inherently messy. Requests pile up: tool responses, skills, explorations, error backtracks, logs, file reads... The important bits get buried under noise, things get lost in the middle. As the session grows, this compounds. Requests get bigger, more expensive, and inevitably worse. At scale, this is incredibly inefficient and every request adds to this debt.

How Sleev works

By exposing a purpose-built context management toolkit to your agents, and transparently managing transient session state, your sessions get optimized with each passing request.

• Deep Optimization: Tool responses, intermediate steps, inactive explorations, redundant file reads, bash commands... Every session part is intelligently optimized, at the right time.
• Guidance: Your agents just know what to do, and how best to leverage Sleev.
• Non-Intrusive: By operating in the background, Sleev abstracts all optimization away for a seamless experience.

Prompt caching and cost

Prompt caching discounts repeated tokens, but unmanaged sessions still spend the bulk of their budget repeatedly reading expanding context. Sleev compacts stale history so each turn runs against a permanently smaller prefix, lowering ongoing inference costs.

For measured benchmarks, cache economics, and turn-by-turn cost breakdowns, see our Performance report .

Smarter sessions

Smaller context is not automatically better. Simple compaction just loses information. Sleev is built around keeping recall useful. By filtering out dead-ends, repetitive tool outputs, and stale context, it reduces distractions. The model can focus on the current goal and immediate constraints. That leads to fewer hallucinations, fewer runaway loops, and higher task completion rates.