Update README.md to reflect accurate performance metrics

Removed outdated performance claims and rephrased metrics for clarity.

Author: sidmohan0

benchmarks/README.md

@@ -116,28 +116,6 @@ detect names and locations the regex engine does not target at all. The
 comparison is a fair _speed_ comparison on identical inputs and entity
 types, not an accuracy study.
 
-## How these map to published claims
-
-- **"~31µs per request" (LiteLLM guardrail, project README /
-  datafog.ai)** — not reproduced _as worded_. ~31–43 µs is the cost of
-  scanning/redacting **one short message**; a full 2-message request
-  through `async_pre_call_hook` is ~120 µs clean / ~220 µs with redaction
-  and litellm logging. Still 100–1000x below a sidecar's network hop, but
-  the claim should be reworded to per-message, e.g. _"~40µs per message —
-  a request clears the guardrail in well under a millisecond"_. Reproduce:
-  `python benchmarks/run.py --suite guardrail`.
-- **"~70ms per invocation including process startup" (Claude Code
-  hook)** — reproduced: 69–89 ms median across runs on this machine
-  (~70 ms idle, higher under load), dominated by interpreter startup.
-  _"~70–90ms"_ (or "under 100ms") is the defensible phrasing. Reproduce: `python benchmarks/run.py --suite hook`.
-- **"190x performance advantage" (PyPI tagline)** — not reproduced at
-  190x by this suite. Measured: 103–170x vs Presidio and 114–140x vs spaCy
-  NER, varying by payload. The historical 190x came from a different
-  (13.3 KB, entity-dense) document and engine configuration. Honest
-  phrasings this suite supports: _"100x+ faster than NER-based PII
-  detection"_ or _"up to 170x faster than Presidio on identical
-  payloads"_. Reproduce: `python benchmarks/run.py --suite spacy,presidio`.
-
 ## Fairness notes / known limitations
 
 - Single-threaded, single-machine, synthetic payloads. Real chat traffic