Status quo
Single-vendor AI
Pick one big-lab API. Live with their model line, their pricing, their outages, their data policy.
See trade-offs ↓
◆ Solutions · Compare
Three ways to run enterprise AI.
Three ways to run enterprise AI.
Only one of them is yours.
Most enterprises pick a single AI vendor and pray, or build a stack from scratch and bleed quarters. Ordis AI is the third path — a vendor-neutral orchestration layer with 200+ models, autonomous agents, voice AI, and on-premise GPU infrastructure, all governed by your policies and audit trail.
The orchestration layer
Ordis AI
Route across every major lab. Deploy autonomous agents and voice AI. Keep your data on your GPUs. Audit every decision.
Start a pilot →
Build it yourself
DIY internal stack
Hire a platform team. Wire integrations. Roll your own routing, audit, voice, and approval queues. Maintain forever.
See trade-offs ↓
◆ Feature matrix
Compare across 10 enterprise capabilities.
The same evaluation criteria your CTO and CISO will use.
| Capability | Single-vendor AI | Ordis AI | DIY internal stack |
|---|---|---|---|
| Models available | 1 provider · 4–8 models | 200+ models · 18 providers | Whatever you wire |
| Intelligent routing | None — one model for all queries | Alphe — automatic per-query selection | Manual if/else per workload |
| Avg AI cost saving | Baseline (high) | −70% vs single vendor | Highly variable |
| Voice AI stack | TTS + STT only | TTS, STT, real-time agents, voice cloning, emotion | Stitch 3–5 vendors yourself |
| On-premise / air-gapped deploy | Cloud only — data leaves the perimeter | Full platform on your GPUs | Possible · 6–12 months |
| Human-in-the-loop approvals | Not built in | Per-dept queues · SLA tiers · cryptographic audit | Build from scratch |
| Vendor lock-in | Total — pricing, T&Cs, deprecations | Zero — automatic failover | Per integration |
| Cryptographic audit trail | Provider-dependent | Yes · included | Your audit, your problem |
| MCP integrations | Closed ecosystem | 20+ — GitHub, Jira, Slack, Postgres, Datadog, Stripe | Hand-rolled |
| Time to production | 2–6 weeks | Under 2 hours | 3–9 months |
200+
AI models routed via Alphe
18
Providers behind one API
−70%
Avg AI cost saved vs single vendor
100%
On-premise capable
<2h
Time to first deploy
Audit-ready
Compliant by default
Stop renting your AI stack.
Pilots ship in under two hours. Bring your own data, your own GPUs, your own policies — Ordis AI does the rest.