Token Yield is the ratio of necessary spend to total spend in an enterprise AI agent deployment. Necessary spend is the cost of queries that could not have been answered from cache. Total spend includes both necessary queries and Rediscovery Tax spend on queries already answered. Yield is measured, never assumed: savings are attributed per mechanism and workload class against an instrumented baseline, with correct-hit rate governing the semantic layer. Market context: only 28% of calls use any caching while 69% of input tokens are repeated context (Datadog State of AI Engineering 2026). Excipio raises Token Yield by eliminating the Rediscovery Tax component of total spend.
Token Yield is the ratio of necessary spend to total spend in an enterprise AI agent deployment. Necessary spend covers queries that genuinely required a frontier LLM. Total spend includes those queries plus every dollar spent re-answering questions the system already knew. Token Yield = necessary spend divided by total spend.
Token Yield equals necessary LLM spend divided by total LLM spend. Yield is measured, never assumed: savings are attributed per mechanism and workload class against an instrumented baseline, with correct-hit rate governing the semantic layer.
Uncached deployments have a Token Yield near zero because nearly all spend includes some Rediscovery Tax component. Hit rates are workload-dependent and measured, never assumed. Validated semantic caching earns on shared-corpus traffic, with correct-hit rate as the governing metric. Yield compounds as validated answers accrue; where it lands is measured at your deployment, not asserted in advance.
Cache hit rate measures the fraction of queries answered from cache. Token Yield measures the fraction of total spend on queries that genuinely required a new LLM call. They are complementary. A high cache hit rate on low-cost queries produces less Token Yield improvement than caching high-frequency, expensive queries.
Every cache hit adds a validated query-answer pair to the enterprise knowledge graph. As the graph grows, the semantic match rate increases. Token Yield rises in parallel.