Build Proprietary AI with Custom LLM & SLM Integration.
Fine-tune open-weights models on your proprietary business data. Deploy air-gapped language models inside your private cloud with zero data leakage and 8x lower inference costs.
Trusted by 350+ technology leaders and defense-grade enterprises.
Data Leakage Risk
0% Air-Gapped Vault
8.4x Lower Cost
< 25ms Token Latency on Edge.
Enterprise LLM & SLM Capabilities
From parameter-efficient fine-tuning (QLoRA) to production vector RAG and high-speed vLLM inference.
Domain Fine-Tuning (QLoRA)
Adapt Llama 3.2, Mistral, and specialized SLMs to your enterprise ontologies, internal documentation, and industry terminology.
Enterprise Agentic RAG
Connect models to millions of unstructured PDFs, spreadsheets, and SQL databases with hybrid BM25 + dense semantic retrieval.
Air-Gapped & VPC Hosting
Deploy inside AWS Nitro Enclaves, GCP Confidential VMs, or on-premise Kubernetes clusters with zero internet egress.
Small Language Models (SLMs)
Lightweight 1B to 8B parameter models engineered to run directly on edge devices and local hardware with sub-20ms latency.
Inference Engine Optimization
Leverage FlashAttention-2, vLLM paged attention, and AWQ 4-bit quantization to achieve 10x higher token throughput.
Constitutional AI & Guardrails
Deterministic guardrails prevent model drift, block prompt injections, and ensure outputs conform strictly to company brand voice.
Complete inference & model observability.
Monitor GPU cluster memory, track per-token generation latency, review semantic retrieval accuracy, and inspect automated evaluation metrics in real-time.
- Real-time token generation telemetry & GPU load
- Automated RAG hallucination and citation verification
- Continuous model evaluation against gold-standard benchmarks
- Turnkey API endpoints compatible with OpenAI SDKs
Inference Engine Telemetry
cfc-llama3.1-70b-enterprise
Inference Latency
22ms / tok
RAG Recall Score
99.2%
Ready to build your private AI model?
Consult with our machine learning engineers to evaluate data readiness, fine-tuning feasibility, and GPU hosting architecture.