Overview

For software companies managing multiple products or business units, leveraging internal knowledge at scale is often a challenge. A secure, self-hosted AI assistant can change that—helping teams answer questions instantly, access siloed data, and improve efficiency across departments. With the rise of AI assistants like ChatGPT, many organizations are now looking to deploy their own version—but the cost of enterprise AI licensing is quickly becoming a concern.

Why Self-Hosting Is Gaining Popularity

OpenAI's enterprise pricing is not publicly available, but reports suggest it may cost around $60 per user/month, with a 150-user minimum and 12-month commitment. That’s over $100,000 per year—before you even add integrations or private data handling. While this includes features like SOC 2 Type 1 compliance, unified billing, and a dedicated workspace, many companies are realizing they can achieve the same capabilities with full control at a fraction of the cost by self-hosting open-source LLMs.

A self-hosted assistant enables you to:

• Avoid per-user pricing models

• Deploy on your own infrastructure (cloud or on-prem)

• Retain full control over data privacy and compliance

• Customize the assistant around your exact internal workflows

Project Objectives

• Deploy a self-hosted AI assistant capable of understanding and responding using internal company data

• Maintain full control over data privacy, infrastructure, and access permissions

• Build with flexibility and scalability to support multiple business units or teams

Phase 1: Discovery & Proof of Concept (POC)

Duration: ~2-4 weeks
Investment Estimate: AUD $5,000–$15,000

What You Get:

• Stakeholder workshops to define needs and architecture

• A functional AI assistant prototype tailored to your data

• Basic user interface (custom or prebuilt)

• Ingestion and indexing of internal sources (PDFs, wikis, etc.)

• Hosted securely on your infrastructure or a private cloud instance

• Privacy-first setup with access control and internal deployment

Tech Stack Options:

• LLM: Mistral, LLaMA 3, or Phi-3 (open-source)

• Inference: Ollama or vLLM

• Retrieval: LangChain or LlamaIndex

• Vector Store: Qdrant, Chroma, or Postgres + pgvector

Phase 2: Production-Ready AI Deployment

Duration: ~4–8 weeks
Investment Estimate: AUD $20,000–$40,000

Includes:

• Scalable deployment using Docker or Kubernetes

• Role-based authentication and permission controls

• Custom branding and enhanced user interface

• Real-time or asynchronous query handling

• Integrations with internal tools like CRMs, SQL databases, SharePoint, etc.

• Monitoring, logging, and system observability

Optional Add-Ons

• Ongoing Maintenance & Support: $2,000–$5,000/month

• Automated Data Syncing: Connect to existing sources with n8n or scheduled updates

• Custom Training or Fine-tuning: Improve performance on internal language

• White-Label Support: Ready to scale the assistant across your product portfolio or business units

Questions to Ask Before Building Your AI Assistant

To align on goals and architecture, here are key discovery questions:

Use Case Clarity

• What will the AI assistant be used for (support, knowledge retrieval, reporting)?

• Who will use it, and what data do they need access to?

Technical Fit

• What platforms or systems does your company already use (e.g., Confluence, SharePoint, SQL)?

• What security or compliance constraints exist (e.g., air-gapped, on-prem only)?

• Do you prefer instant responses or are async queries acceptable?

Operations

• What is the expected budget and timeline for deployment?

• Will the assistant serve a single unit or scale across multiple teams?

Final Thoughts

A private AI assistant isn’t just a chatbot—it’s a long-term asset that turns internal knowledge into an always-on support system for your team. Whether you're exploring automation for support, internal documentation, or decision-making, a self-hosted AI assistant built with open models gives you full control without sacrificing flexibility.

With OpenAI’s enterprise tier pricing starting to resemble traditional SaaS licensing costs, the time to consider open, self-hosted alternatives is now.

Ready to explore what a tailored assistant could do for your organization? We’d love to discuss it with you.