Quality of Service
Architecture
AIone employs a multi-layered architecture to ensure service reliability:
- Official API Sources: Claude, GPT, and Gemini are all accessed through official cloud services or official APIs
- Multi-Channel Redundancy: Each model can be routed through multiple upstream channels to eliminate single points of failure
- Health Probing & Smart Routing: Continuously monitors success rates, latency, and error rates; automatically isolates unhealthy channels
- End-to-End Encryption: HTTPS/TLS protects the entire transmission pipeline; request content is never used for model training
SLA Commitments
| Metric | Target |
|---|---|
| Availability | 99.9% (monthly) |
| API Response Time | < 200ms (excluding model inference time) |
| Incident Recovery Time | < 30 minutes |
Model Sources
All models are accessed through official channels:
| Provider | Access Method |
|---|---|
| Anthropic Claude | AWS Bedrock |
| OpenAI GPT | Azure OpenAI / OpenAI API |
| Google Gemini | GCP Vertex AI |
100% authentic, officially sourced resources. No unauthorized channels.
Data Security
- No content storage: AIone only relays requests -- it does not cache or log conversation content
- No model training: Your data is never used for any model training
- Audit logs: Metadata for every API call (timestamp, model, token count) is available for review; content is not retained
- API Key isolation: Each key can be restricted to specific models
Monitoring & Status
- Public status page: portal.aiin1.ai/status -- real-time platform health
- Usage dashboard: View call volume, latency, and error rates in the console
- Changelog: portal.aiin1.ai/changelog -- transparent record of all platform updates