Private AI - enterprise LLMs that stay inside your perimeter
Deploy open-weight models (Llama, Mistral, Qwen, Gemma) with RAG, fine-tuning, and enterprise guardrails - so your teams get ChatGPT-class productivity without sending data outside.
Public GenAI cannot see your regulated data
Legal, financial, and clinical teams cannot upload contracts, portfolios, or patient records to external LLMs. Private AI puts a fine-tuned, RAG-enabled assistant on your own infrastructure - fully audited and role-aware.
A full enterprise GenAI platform
Model Hosting
Llama, Mistral, Qwen, Gemma, and Phi models served on your GPUs with vLLM or TGI.
Retrieval Augmented Generation
Vector search over SharePoint, Confluence, S3, and databases with per-user permissions.
Fine-Tuning Pipelines
LoRA and full fine-tuning on your domain data with automated evaluation.
Guardrails & DLP
Prompt filtering, PII redaction, jailbreak defence, and output moderation.
Audit & Governance
Every prompt, retrieval, and response logged for compliance review.
Assistant Workbench
Ready-made web UI, Slack/Teams bots, and API for internal apps.
Related services
Frequently asked questions
For general assistants, Llama 3 70B and Qwen 2.5 72B are excellent. For code, Qwen-Coder 32B and DeepSeek-Coder. We benchmark against your workloads before committing.
A single H100 node comfortably serves a 70B model at INT4/FP8 for hundreds of users. For 1000+ concurrent users, plan on 2-4 nodes with load balancing.
Yes - and we recommend it. RAG delivers 80% of the value in weeks. Fine-tuning is added once you know which behaviours the base model handles poorly.
Pilot a private assistant in 6 weeks
Fixed-scope pilot: model deployment, RAG over one data source, and 50 users.