Key facts
| Access control | Scoped API keys with rotation; enterprise SSO and RBAC options |
| Deployment | Cloud, VPC, on-prem or air-gapped with region selection |
| Auditability | Request, model and response logging for ban and appeal review |
| Data grounding | Embeddings and RAG are live for policies, patch notes and support content |
| Structured output | JSON mode returns moderation and support records in validated schemas |
| Pricing model | Flat monthly self-serve plans; no per-token billing on self-serve |
| Free tier | Free plan with 2 free AI models; 14-day full-access trial |
| Endpoint roadmap | Moderation, audio, images, batch and fine-tuning are coming soon |
TL;DR
- Treat player safety and moderation as a core requirement, not a feature flag.
- Keep payment and identity credentials out of prompts and logs.
- Escalate ambiguous moderation decisions to trained humans.
- Log interactions so bans, mutes and appeals have evidence.
- Choose region or private deployment based on player demographics and rules.
How it works, step by step
- Classify player data: account identity, payment, chat content, behavioral and anti-cheat signals.
- Design the payment boundary so store and wallet credentials never enter prompts.
- Build moderation as a pipeline: classify, score, act and escalate, with human review for edge cases.
- Scope keys per service - game servers, live ops, support - with rotation and central storage.
- Ground policy and support answers in current rules with citations.
- Use JSON mode for moderation and support records so tooling validates decisions.
- Log request IDs, model versions, sources and actions for bans, appeals and audits.
Try it yourself
Open the AI API key security checklist →
Player data and minors
Gaming platforms hold account identities, payment methods, behavioral histories and, for younger players, data under stricter protection. Start with classification: what may reach a model, what must stay behind tools, and what may never leave a private environment. Payment and store credentials belong in the never category, as do raw identity documents.
Behavioral signals used for anti-cheat or matchmaking should be handled with the same discipline, because they can be sensitive when combined.
Chat moderation and safety escalation
Moderation is a pipeline, not a single call: classify the message, score severity, take an automated action where policy is clear, and queue ambiguous cases for trained reviewers. The moderation endpoint is coming soon; until then, use the chat API with a strict policy prompt and a structured output schema, and keep human escalation for anything borderline.
Log both the automated decision and the human outcome so an appeal can be reviewed against the same evidence.
Live ops, anti-cheat and payment boundaries
Live operations teams need fast access to patch notes, event rules and support history. Retrieval over current content with citations speeds that work without letting the model invent policy. Anti-cheat teams can use AI to summarize evidence for human review, but enforcement decisions stay with people. Keep store and wallet credentials entirely outside the model path, with tools returning status only.
Logging for bans, appeals and audits
Enforcement actions need defensible records. Log request IDs, model and version, retrieved sources, outputs and the resulting action, then retain them long enough to cover your appeal window and any legal hold. Restrict log access to authorized staff, and review a sample of moderation decisions regularly to catch drift in policy interpretation.
Honest comparison
| Control area | Plugsky capability | Common gap | Owner |
|---|---|---|---|
| Player safety | Structured moderation pipeline with human escalation | Fully automated bans | Trust and safety |
| Payment boundary | Tools return status only; prompts exclude credentials | Store data pasted into prompts | Platform engineering |
| Access | Scoped keys per service, enterprise SSO and RBAC options | Shared credentials across game services | Security |
| Policy grounding | RAG over current rules with citations | Answers from outdated policy | Live ops |
| Appeal evidence | Request, source and action logging | No reconstruction path | Player support |
| Resilience | Fallback patterns for launch spikes | No degraded mode for peak events | SRE |
Frequently asked questions
Is the moderation endpoint available?
Moderation is coming soon. Until then, use the chat API with a strict policy prompt and a structured schema, and keep human review for ambiguous cases.
How do we protect minors' data?
Minimize what reaches the model, keep identity and payment data behind tools, and use private deployment for sensitive flows. Map the rules that apply in each market you serve.
Can AI issue bans automatically?
Only for clear, high-confidence policy violations defined by your team. Anything ambiguous should queue for a human reviewer with the evidence attached.
How do we handle launch traffic spikes?
Self-serve plans are flat monthly with fair-use usage, so spikes do not change the bill. Load-test latency and define a degraded mode for peak events.
What should we log for appeals?
Request ID, model and version, retrieved sources, output and the action taken, retained for your appeal window. That lets a reviewer replay the decision.
Can AI power in-game NPC dialogue safely?
It can, within confined prompts and content filters, but keep an abuse path and rate limits, and never expose credentials or internal systems through NPC tool access.
Where do we start?
Pilot moderation and support on non-sensitive content with the free plan, validate escalation rates, then extend to live systems with scoped keys and logging.