Key facts
| Standard interface | One OpenAI-compatible endpoint for 30+ models |
| Router model | model="plugsky-fusion" selects the model per request (live) |
| Policy surface | Strategies and custom rules scoped to workspace, API key or request |
| Decision log | Model, strategy and matching rule recorded for every request |
| Deployment | Cloud, VPC, on-prem, air-gapped and bring-your-own-cloud topologies |
| Residency | Region pinning with data staying in the pinned region |
| Availability | 99.9% to 99.95% uptime SLAs, 99.99% on multi-region deployments |
| Roadmap | Classifier routing /v1/plugsky/route (model=auto) is coming soon |
TL;DR
- Give every team one endpoint instead of N provider integrations.
- Express policy as strategies and rules rather than code reviews.
- Use decision logs as the evidence layer for audits and chargeback.
- Choose topology once: cloud, VPC, on-prem, air-gapped or BYOC.
- Keep deterministic overrides for tier-one and regulated systems.
How it works, step by step
- Inventory current model usage by team, including providers, regions and monthly cost drivers.
- Define service tiers: what may run on cheap models, what needs strong reasoning, and what must be deterministic.
- Encode those tiers as strategies and custom rules per workspace or key.
- Choose a deployment topology and residency per workload before migration, not after.
- Migrate one workload at a time, comparing quality and cost against its old provider.
- Wire routing logs and SLA-relevant metrics into your observability stack, and review rule changes like any other change.
Original data
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One endpoint, many workloads
The architectural win is subtraction. Instead of every team integrating its own provider SDK, key rotation and retry logic, the organisation standardises on one OpenAI-compatible endpoint that fronts 30+ models. Teams send model: "plugsky-fusion" and receive a result; the platform chooses the model.
That single interface also simplifies exit and entry: a new model tier does not require a new integration, and a workload can move between tiers by configuration. Reference architectures that previously needed a gateway, a router and a secrets layer reduce to one dependency with well-defined behaviour.
Policy as configuration
Strategy is where governance becomes concrete. Set balanced as the default for general traffic, cost_saver for batch and internal tools, and max_quality for customer-facing or regulated paths. Custom rules evaluate in order, so you can express things like "documents over 4,000 tokens go to a long-context model" without shipping code.
- Scope: strategies can be attached to a workspace, an API key or a single request.
- Overrides: any explicit model name bypasses routing, giving you a deterministic escape hatch.
- Evidence: each request logs the model, strategy and rule, giving auditors a readable decision chain.
Topology, residency and resilience
Model choice is only half the architecture; where inference runs is the other half. Plugsky supports multi-tenant cloud with region pinning, VPC deployment inside AWS, GCP, Azure or OCI, on-prem Helm installs, fully air-gapped bundles and a bring-your-own-cloud option where inference runs in your account.
Resilience should be designed with the same intent: multi-region deployments carry a 99.99% SLA, while single-region enterprise commitments sit at 99.95%. Pair that with the router's automatic fallback behaviour and a fixed-model override for the systems that cannot tolerate variation, and the platform story holds together under audit.
Honest comparison
| Concern | Plugsky Model Fusion | DIY model gateway | Single-vendor lock-in |
|---|---|---|---|
| Model access | 30+ models, one endpoint | One integration per provider | One catalogue |
| Policy controls | Strategies and rules, scoped | Custom code | Vendor tooling |
| Decision logging | Model, strategy, rule per request | You build it | Vendor logs |
| Deployment | Cloud, VPC, on-prem, air-gapped, BYOC | Whatever you host | Vendor regions |
| Availability | SLAs to 99.99% multi-region | Your own resilience | Vendor SLA |
Frequently asked questions
How do we enforce different policies per team?
Attach strategies per workspace or per API key. Teams keep their own keys and limits while the platform applies a consistent default.
Can we prove which model handled a request?
Yes. Every request records the chosen model, the strategy and the rule that fired, plus token, latency, status, key, project and region metadata.
What happens if the preferred model fails?
The router escalates or falls back based on strategy and availability, and you can pin a fixed model where automatic fallback is not acceptable.
Which deployment models exist?
Multi-tenant cloud with region pinning, VPC inside your hyperscaler account, on-prem, air-gapped and bring-your-own-cloud.
What SLA can we expect?
Builder and Scale tiers carry 99.9% monthly uptime with 10% credit on miss, Enterprise 99.95% with 25% credit, and 99.99% on multi-region deployments.
How do we migrate teams off other providers?
Move one workload at a time onto the same endpoint, compare quality and cost, then standardise. The API stays OpenAI-compatible, so client code rarely changes.
Is automatic classifier-based selection available?
Not yet — POST /v1/plugsky/route with model=auto is coming soon. Today, strategies and custom rules handle per-request selection.