CASE STUDY

K3 Technology

Private GPT — Multi-Model AI Platform

Every AI Model. Full Privacy. Built Around Your Workflow.

HummingAgent

hummingagent.ai

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30+ Models

GPT, Claude & More

5

Happy Clients

100%

Data Privacy

24/7

Availability

Executive Summary

K3 Technology needed a private AI solution that didn't force a tradeoff between capability and security. Teams were paying for ChatGPT, Claude, and Gemini separately — and still couldn't get privacy, model choice, and custom workflows in one place.

HummingAgent built Private GPT: a self-hosted, multi-model AI platform that gives teams access to GPT, Claude, Gemini, Llama, Mistral, and 30+ more models — all in one interface, with full data privacy and workflows built around how each team actually works.

The Challenge

  • •Teams locked into a single AI provider with no way to compare or switch models
  • •Public AI tools (ChatGPT, Claude) offered no data privacy — conversations could train external models
  • •Private AI solutions were limited to one model and lacked modern capabilities
  • •AI had no memory — every conversation started from scratch with no business context
  • •Generic chat interfaces didn't fit team-specific workflows or processes
  • •Multiple AI subscriptions with overlapping costs and no unified platform

The Solution

Private GPT Multi-Model Platform

  • ✓Access to GPT, Claude, Gemini, Llama, Mistral, and 30+ models from one interface
  • ✓Full data privacy — corporate data never leaves the client's environment
  • ✓Context-aware memory that retains clients, projects, pricing, and past decisions
  • ✓Custom workflows and prompts shaped around each team's processes
  • ✓Microsoft SSO with role-based access control for enterprise security
  • ✓File and document upload with vector search for business context

Platform Features

  • ✓Model switcher — change AI providers mid-conversation without losing context
  • ✓Persistent memory across sessions — AI remembers your business
  • ✓Custom prompt library built around team-specific workflows
  • ✓Document and file context — ask questions against your own data
  • ✓Admin controls — manage users, permissions, and model access
  • ✓Usage analytics — see how your team is using AI

Technical Architecture

TechnologyWhy We Chose It
React 18 + TypeScriptFast, type-safe frontend with Vite and TailwindCSS
Node.js + ExpressBackend API with MongoDB and Redis for data and caching
Azure OpenAI + Custom EndpointsMulti-model AI routing with vector search
Azure Container AppsScalable, containerized infrastructure with Blob Storage
Microsoft SSO + JWTEnterprise authentication with role-based access control
GitHub Actions + DockerAutomated CI/CD pipeline for continuous deployment

Key Achievements

Model Freedom

Locked into one AI provider per tool

30+ models accessible from one platform

Data Privacy

Public AI trained on corporate conversations

100% private — data never leaves your environment

Business Memory

AI forgot everything between sessions

Context-aware memory across all conversations

Custom Workflows

Generic one-size-fits-all chat interface

Workflows and prompts built around your team

Results & Impact

Now Customers Can:

  • ✓ Switch between GPT, Claude, Gemini, and open source models instantly
  • ✓ Ask AI about past client decisions, pricing, and project history
  • ✓ Upload internal documents and query against them in chat
  • ✓ Use custom-built prompts shaped to their specific processes
  • ✓ Access AI 24/7 with guaranteed data privacy

Now Staff Can:

  • ✓ Manage all users, permissions, and model access from an admin dashboard
  • ✓ See usage analytics across the team
  • ✓ Deploy updates through automated GitHub Actions pipeline
  • ✓ Add new AI models or custom endpoints without downtime
  • ✓ Configure role-based access per team or department

Security & Compliance

Azure Hosted

Enterprise infrastructure

100% Private

Data never leaves environment

Microsoft SSO

Enterprise authentication

Role-Based

Granular access control

Future Roadmap

  1. 1. Expanded model library including fine-tuned and domain-specific models
  2. 2. Team-wide shared memory and knowledge base integrations
  3. 3. AI agent workflows — multi-step automations triggered from chat
  4. 4. Native integrations with Slack, Teams, and project management tools
  5. 5. On-premise deployment option for highest-security environments
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HummingAgent

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