Cheaper than per-seat ChatGPT Enterprise or Glean at scale, once seat count crosses ~100 users.
Private AI implementations across regulated and confidentiality-sensitive industries.
Your data stays in your tenant — no third-party LLM provider sees a token of it.
What you get from a private-AI deployment
Six outcomes regulated companies — and any team uneasy about feeding client data to OpenAI — get from a private deployment.
Data Sovereignty
Your documents, conversations, embeddings, and audit logs all live in your tenant. The LLM runs on your infrastructure, so no third-party AI provider sees a token of it.
Open-Source Stack
Onyx, LibreChat, Open WebUI, vLLM, Ollama. Battle-tested, MIT-licensed software with no vendor that can change pricing on you or shut you down.
Permission-Aware Retrieval
Connector-based RAG that respects RBAC, matter walls, and file-level permissions. Employees only see what they have access to in source apps.
Cost Predictability
One-time deployment plus a flat managed retainer. No per-seat surprises as headcount grows. At scale, 5–10× cheaper than ChatGPT Enterprise or Glean.
Compliance-Ready
HIPAA, GDPR, SOC 2, attorney-client privilege, and government data-residency rules are all addressable when the LLM and data live in your tenant.
Bring Your Own LLM
Run Llama, Mistral, Qwen via vLLM or Ollama, or route to OpenAI, Anthropic, Gemini through an LLM gateway. Switch models without rebuilding the stack.
Why off-the-shelf SaaS misses on private AI
ChatGPT Enterprise, Glean, and other multi-tenant LLM SaaS were designed for the median knowledge worker at a typical mid-market company. Once your data sensitivity, seat count, or industry constraints diverge from that median, three things break: per-seat pricing punishes you for rolling AI out widely, data exposure fails your legal / compliance / InfoSec review past pilot, and ranking and model selection are tuned for the average customer rather than yours.
Private AI is the open-source path that fixes all three. The catalog above is how we deliver it.
The open-source stack we deploy
Onyx — Open-source Glean alternative
- Enterprise AI search and chat over 40+ workplace apps
- Plug-and-play connectors: Slack, Drive, Confluence, GitHub, Jira, Salesforce, SharePoint, Notion
- Permission-aware retrieval — respects each source's ACLs
- In production at Netflix, Ramp, and 1,000+ teams
LibreChat / Open WebUI — Self-hosted ChatGPT
- Multi-model chat UIs — OpenAI, Anthropic, Gemini, Bedrock, plus self-hosted
- Agents, code interpreter, web search, SSO, MCP support
- Battle-tested at Shopify, Daimler, Boston University, ClickHouse, Stripe
- Replaces ChatGPT Team / Plus subscriptions on your tenant
vLLM / SGLang — Production LLM serving
- High-throughput inference for Llama, Mistral, Qwen, and other open models
- Paged attention, continuous batching, low-latency serving on Kubernetes
- Throughput tuning, per-team quotas, full observability
- Where private AI gets economic at scale
Ollama — Easy local model deployment
- Fastest way to run open-source LLMs on a workstation, single GPU, or production
- Pairs with Open WebUI for an instant private-ChatGPT setup
- Local-first option for the smallest pilots
- Same model API surface as OpenAI / Anthropic
The private-AI catalog — solutions we deploy
Eight ways we deploy private AI in your tenant. Pick the one that matches the job you’re trying to do — or talk to us and we’ll help you sequence the right combination. The first five are live engagements you can scope today; the rest are part of how we ship the full stack and have dedicated pages coming soon.
Self-Hosted Enterprise Search
Onyx (formerly Danswer) deployed in your tenant, indexed against 40+ workplace apps with permission-aware retrieval. The open-source Glean alternative — same chat-with-citations UX, your data never leaves your environment. See the engagement →
Private ChatGPT for Business
Self-hosted LibreChat or Open WebUI connected to your Slack, Drive, and corporate documents. BYO-LLM across OpenAI, Anthropic, or self-hosted Llama / Mistral. Replaces the ChatGPT Team subscriptions your employees are already paying for out of pocket. See the engagement →
Self-Hosted AI for Business — Full Stack
The full private-AI stack — LibreChat + Onyx + vLLM — deployed end-to-end as one engagement. Chat, search, BYO-LLM serving, SSO, audit, and observability wired together on day one. One stack, one bill, one rollout sequence. See the engagement →
Air-Gapped AI for Regulated Industries
Fully disconnected AI for classified, IL5, sovereign-cloud, and SCIF environments. Open-weight models on your GPUs, zero outbound at runtime, FedRAMP / IL5 / GovCloud aligned controls and audit logs. See the engagement →
Private RAG / Chat With Documents
Single-corpus document chat that stays inside your tenant. Tuned ingestion, hybrid retrieval, and BYO-embedding + BYO-LLM. Ideal for legal matter files, M&A data rooms, regulatory libraries, and research corpora. See the engagement →
LLM Inference & Serving Infrastructure
Production model serving on your GPUs — vLLM, SGLang, or TensorRT-LLM — with horizontal scaling, observability, and per-team routing. The serving half of the stack, sized and tuned for your traffic and your GPU budget. Dedicated page coming soon — talk to us for an early engagement.
vLLM Development & Deployment
High-throughput vLLM deployment with paged attention, continuous batching, and Kubernetes-native scaling. Tuned for your specific model and traffic pattern, with FP8 / FP16 / INT8 quantization sized to your GPU footprint. Dedicated page coming soon — talk to us for an early engagement.
Ollama Deployment & Integration
Local-LLM deployment for workstations, single GPUs, or small production instances. The fastest path to an end-to-end private-AI pilot before scaling to vLLM serving in production. Dedicated page coming soon — talk to us for an early engagement.
Talk to a Private AI expert
Bring us your industry, your data-sensitivity profile, and your seat economics. We’ll come prepared with the right stack — and a directional read on what you can stand up in your tenant next sprint.
Ask us about
- Open-source Glean alternative (Onyx / Danswer) deployment
- Private ChatGPT for business (LibreChat / Open WebUI)
- Production LLM serving with vLLM / SGLang on your GPUs
- Permission-aware retrieval (Slack / Drive / Confluence / iManage)
- Air-gapped + compliance-ready (HIPAA / SOC 2 / privilege)
- Bring-your-own-LLM gateway and LLMOps observability
Not sure where to start?
Most teams come to private AI for one of three reasons: data sovereignty (documents and embeddings have to stay inside your tenant), scale economics (per-seat SaaS becomes punitive past ~100 users), or ranking and model control (out-of-the-box vendor behavior doesn’t fit your corpus or workflow). If one of those describes you, the catalog above is the starting point. If you’re not sure which engagement to start with, the strategy session below maps your situation to the right entry point.
Frequently asked questions
Additional resources
AI Transformation Workshop
Half-day strategy workshop to identify the highest-ROI private-AI moves for your team. Book a workshop →
AI Strategy Session
60-minute scoping call. Directional read on the right private-AI stack for your environment + a sample architecture. Book a session →
AI Consultant vs In-House Team
Honest tradeoffs comparison for build-vs-buy decisions on private AI for your organization. Read the comparison →
Ready to deploy private AI?
A 45-minute strategy call. We come prepared with the right stack for your industry, your data sensitivity, and your seat economics — and a directional read on what you can stand up in your tenant next sprint.