Latency Overhead of AI Safety Checks

Every safety check adds time to agent operations. Understanding and minimizing this overhead is essential for building agents that are both safe and responsive. This post breaks down where latency comes from and how to keep it under control.

Latency Breakdown

A typical Authensor safety evaluation involves several stages, each with its own latency profile:

Policy lookup: 0.1 to 1 millisecond. Fetching the active policy from cache or database. With in-memory caching, this is sub-millisecond.

Regex-based content scanning: 0.5 to 2 milliseconds. Authensor's Aegis scanner with regex rules processes input quickly. The cost scales linearly with input length and rule count.

ML-based content scanning: 10 to 100 milliseconds. Running a classifier model adds the most latency. API-based classifiers add network round-trip time on top of inference time.

Policy evaluation: 0.5 to 3 milliseconds. Authensor's synchronous policy engine evaluates rules in memory with no I/O.

Receipt creation: 1 to 5 milliseconds. Writing the cryptographic audit receipt to the database. Can be made asynchronous for non-blocking operation.

Total typical overhead: 3 to 15 milliseconds without ML scanning, 15 to 120 milliseconds with ML scanning.

Context: LLM Inference Latency

LLM API calls typically take 500 milliseconds to 5 seconds. A 10-millisecond safety check adds 0.2% to 2% overhead relative to the LLM call. This is almost always acceptable.

Optimization Strategies

Cache policies aggressively. Policy definitions change infrequently. Cache them in memory with a TTL of 30 to 60 seconds.

Run scans in parallel. If you use multiple detection methods, run them concurrently rather than sequentially.

Make receipt writes asynchronous. The agent does not need to wait for the audit record to be persisted before proceeding with an approved action.

Use tiered scanning. Run fast regex checks first. Only run expensive ML classifiers if the input scores above a risk threshold.

Batch evaluations when possible. If an agent plans multiple actions, evaluate them in a single batch call to amortize the overhead.

Authensor's architecture is designed to keep safety checks off the critical path where possible while maintaining fail-closed guarantees for the checks that must be synchronous.