Get the best of Copilot, ChatGPT, Gemini and Claude
Each of these sold your organization on enterprise AI — and each keeps its models, and your people's memory, inside its own product. Ally puts them to work together: one conversation where models from different vendors hand work to each other, every contribution signed, one place to see what each model cost you. You keep the vendors you already trust; you stop choosing between them.
Last reviewed: September 13, 2026 · reviewed monthly — this market moves fast.
| Capability | Ally Platform | M365 Copilot | ChatGPT Enterprise | Gemini Enterprise | Claude Enterprise |
|---|---|---|---|---|---|
| Models from multiple vendors | ✓ Claude, GPT, Gemini | ✓ GPT + Claude (user-selectable in several experiences) | ✕ OpenAI models | ✕ Google models | ✕ Anthropic models |
| Delegate part of a task to another vendor's model, inside one conversation | ✓ user-directed, per-contribution attribution | ✕ model choice is per-experience, not in-conversation delegation | ✕ | ✕ | ✕ |
| Cross-vendor independent review (different provider critiques the draft) | ✓ | ◐ Critique pairing is system-composed | ✕ | ✕ | ✕ |
| Cross-vendor image generation in the same chat | ✓ | ✕ | ✕ | ✕ | ✕ |
| Memory that persists across model vendors | ✓ follows the user | ✕ | ✕ product-bound | ✕ product-bound (offers import from other AIs) | ✕ account-bound |
| Admin scope for memory (per user/group), admin cannot read content | ✓ | — | ◐ org-level disable | ◐ | ◐ Enterprise-tier retention controls |
| DLP on cross-model handoffs and memory writes | ✓ built-in, before the model | ◐ via Purview — inside Microsoft only | ◐ third-party | ◐ Model Armor (chat) | ✕ not offered |
| Per-model cost tracking | ✓ | ✕ | ✕ | ✕ | ◐ spend controls, Anthropic only |
✓ yes ◐ partial / qualified ✕ no — not applicable
We keep this table honest — competitor cells are marked generously where products have genuinely moved, and the page is re-reviewed monthly. Spot something stale? Tell us and we'll fix it.
Choose Ally when…
- Your teams already use two or more of these — and you want one rollout instead of four.
- You want the best model for each task, from whichever vendor makes it, without starting over each time the leader changes.
- You need to know what each model cost you last month — by user, by team, by agent.
- You'll put agents in front of customers and need to prove they behave before they do.
See it on your stack
A comparison table answers "what"; a conversation answers "does it fit our architecture, security model, and use cases?" That's the meeting we're built for.