Benchmarks
Evidence-bounded comparisons against RAG, vector databases, extended context windows, and weight quantization. Every claim is testable.
Comparison 01
| Category | Trinity Sky | RAG Systems |
|---|---|---|
| Recall Mechanism | Exact recall from NEOMORPHIC™ memory | Embedding similarity search |
| Structured Relations | Native relationship storage | Chunk retrieval |
| Partial-Cue Recall | Native | Query reformulation needed |
| Temporal Ordering | Built-in time ordering | No native model |
| Recall Latency | <132 μs | 100 ms – 1 s |
| Update Coherence | Instant updates | Re-index needed |
| Inspectability | Audit trail + match confidence | Chunk metadata |
Comparison 02
| Capability | Trinity Sky | Pinecone / Weaviate / Qdrant |
|---|---|---|
| Search Type | Exact retrieval | Approximate Nearest Neighbor |
| Composition | Native composition of ideas | Flat vectors |
| Representation | Patent-pending NEOMORPHIC™ format | Generic float embeddings |
| Compression | 16× smaller | PQ / SQ (lossy) |
| Accuracy | 99.97% accuracy | 95–99% recall@10 |
| Sovereignty | Local / air-gap | Cloud-first |
Latency
NEOMORPHIC™ recall in under 132 μs (p99). RAG retrieval: 100 ms–1 s. Re-reading a long context window gets slower and slower as it grows. For real-time AI, only NEOMORPHIC™ memory keeps up.
Hallucination
LLMs hallucinate at 5.6–13.6% (benchmark-dependent). Trinity Sky scores every recall for confidence — low-confidence results are blocked before they ever reach the user.
Compression
Proprietary compression shrinks every memory 16× while retaining 0.987 fidelity. Small enough to sit in the processor’s fastest cache, so recall stays instant even on edge hardware.
Energy
An M4 Max sovereign edge node runs the complete real-time stack at approximately 30 watts. Compare: a single A100 inference at 250–400W. Brain-inspired, ultra-low-power chips go lower still.
Trinity Sky
