Our own engines, already running in our production - and which we deploy at your side as a foundation, not a prototype.
Comparison of SLA targets, VRAM requirements, hosting mode, deployment time, and primary use-case.
| Dimension / Engine | BGE-M3 Search | OpenClaw | Doc Intelligence |
|---|---|---|---|
| SLA target | 99.95% (<50ms p95) | 99.99% (multi-model failover) | 99.9% (queues + human-gate) |
| VRAM requirements | 8-16 GB VRAM (FP16) | 0 GB (gateway) / 24+ GB (local LLM) | 16-24 GB VRAM (VLM + OCR) |
| Hosting mode | On-premise / Docker / K8s | VPC Hybrid / On-premise | Self-hosted (zero-retention) |
| Deployment time | 3-5 business days | 5-10 business days | 7-14 business days |
| Primary use-case | Hybrid semantic retrieval and RAG foundation | Centralized LLM routing, PII masking, and cost control | Structured field extraction from PDFs and scans |
| Action | Request deployment → | Request deployment → | Request deployment → |
deployment protocol
We start with one process, measure the outcome on our own metrics and only then scale. Nothing is sold from slides.