Skynet vs ChatGPT
How does Skynet compare to ChatGPT? The core difference: Skynet is a workspace, not a single-model chatbot. It routes across models, including GPT, and adds what a standalone chatbot can’t: live connectors into your tools, memory that compounds across your whole team, and a strict policy against training on your data, on any plan. See data uses.
ChatGPT vs Skynet
| Capability | ChatGPT | Skynet |
|---|---|---|
| AI model access | OpenAI models only | Multiple models, including GPT |
| Persistent memory | Limited (custom instructions) | Full persistent memory across all sessions |
| Email connectors | ✗ | Gmail, Outlook |
| Chat connectors | ✗ | Slack, Teams |
| Meeting attendance | ✗ | Zoom, Google Meet |
| Document connectors | File upload only | Live Google Drive, Dropbox integration |
| Autonomous agents | GPTs (limited) | Full autonomous agents with task execution |
| Collective memory for teams | ✗ | With selective memory controls |
| On-premise deployment | ✗ | Enterprise plan |
| Memory import from other services | ✗ | Import from Claude & ChatGPT |
What Skynet offers that ChatGPT doesn’t
- Unified workspace: ChatGPT is a chat interface. Skynet combines multiple AI models (including GPT), connectors, agents, and memory in one place.
- Real-time connectors: Skynet connects directly to your email, chats, meetings, and documents instead of working in isolation.
- Collective memory: Skynet’s collective memory shares your team’s knowledge in real time, not just one user’s history.
- On-premise Enterprise: Skynet Enterprise can run on your own data centre; your data never has to leave your servers.
- Autonomous agents: Skynet’s agents attend meetings, execute tasks, and take action, not just respond to prompts.
- Memory import: switching to Skynet doesn’t mean starting over; import your history and context from ChatGPT.