Precision engine
Rerank EngineSlimContext™ — the right tokens, none of the bloat.
The Rerank Engine takes raw candidates and squeezes them into the smallest, sharpest context window possible. SlimContext™ compression typically cuts LLM token spend by a third while raising answer accuracy.
31%
lower LLM spend
99.2%
answer accuracy
3.4x
context density
<15ms
rerank latency
What makes Rerank Engine a beast
Cross-encoder reranking
A fine-tuned cross-encoder reorders candidates by true relevance, not just vector distance.
SlimContext™ compression
Redundant and low-signal passages are pruned so the model sees only what matters — fewer tokens, sharper answers.
Citation enforcement
Every passage is tracked end-to-end so answers come with verifiable, clickable sources.
Hallucination guardrails
Confidence scoring flags weak grounding before a response ever reaches your users.
Technical specs
- Token reduction
- Up to 62% with SlimContext™
- Rerank latency
- <15ms for 100 candidates
- Grounding
- Span-level citations
- Deployment
- Cloud, VPC, on-prem