Key facts
| API compatibility | OpenAI-compatible /v1/chat/completions; drop-in base URL change |
| Models | 30+ models behind one API; open-weight options for private deployment |
| Typical patterns | Lesson drafts, feedback drafts, admin comms, multilingual support |
| Integration path | Connects to LMS, SIS and communication platforms through middleware |
| Pricing model | Flat monthly self-serve plans with unlimited fair-use usage; no per-token billing — see the live pricing page |
| Free tier | plugsky-micro and plugsky-lite on the free plan, no card required |
| Deployment | Plugsky cloud, your VPC, on-prem and air-gapped options |
| Compliance posture | SOC 2 Type II and ISO 27001 readiness in progress (not yet certified); validate evidence during diligence |
TL;DR
- Use the API to draft and retrieve; keep educators owning decisions.
- Review student-data handling before any pilot touches records.
- Publish an acceptable-use policy for staff and students.
- Choose region selection and audit logs for institutional governance.
- Start free with plugsky-micro and plugsky-lite, no card required.
How it works, step by step
- Choose a staff-facing workflow such as lesson drafts or policy Q&A.
- Complete a data-protection review of the records involved.
- Write the acceptable-use and academic-integrity rules for the pilot.
- Build against the OpenAI-compatible endpoint with scoped keys.
- Choose deployment and region to match institutional policy.
- Pilot with volunteer staff, measure time saved and quality, then expand.
Original data
Try it yourself
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Where an AI API fits in education
Educators need time back for teaching, not automated judgement. The safe starting points are drafting and retrieval:
- Lesson-plan drafts: generate a structured draft from curriculum objectives for the teacher to adapt.
- Feedback drafts: turn rubric notes into clear draft comments that the teacher edits and owns.
- Administrative correspondence: draft routine letters, notices and policy summaries for staff review.
- Multilingual communication: translate family-facing messages so more households can engage.
- Document Q&A: answer staff questions from institutional policy and handbooks with citations.
Security, privacy and data handling
Student records are among the most sensitive data an institution holds, so the defaults should be conservative:
- Keep student records out of prompts unless there is a documented purpose and a lawful basis.
- Establish an academic-integrity policy that distinguishes staff drafting from student submission.
- Require educator review before any feedback or communication reaches a learner or family.
- Use region selection, scoped keys and audit logs so records stay governed.
Deployment options and model choice
Institutions often begin with cloud for staff tools and move to a private endpoint as student-data scope widens. Plugsky exposes the same OpenAI-compatible endpoint whether the workload runs in shared cloud, your VPC, on-prem or air-gapped, and region-locked planes keep processing where your policy requires. Teams route to 30+ models through one API, with open-weight options when a site has no external connectivity, and port code with a base URL change. Chat, streaming, JSON mode, function calling, embeddings, RAG and agents are live; audio, images, moderation, files, batch, fine-tuning, assistants and the responses API are coming soon. plugsky-micro and plugsky-lite are free with no card, a 14-day full-access trial covers paid tiers, and the live pricing page lists current plans.
From pilot to production
Education deployments fail on policy, not technology. Avoid:
- Piloting with real student records before a data-protection review.
- Letting generated feedback be issued without an educator reading it.
- Assuming staff and student acceptable-use rules are the same.
- Forgetting accessibility requirements in parent-facing communications.
- Skipping bias checks for feedback and grading-assistance workflows.
Start with staff-facing drafting on non-sensitive material, write the acceptable-use policy alongside the pilot, and involve data protection and accessibility leads early. Keep humans accountable for every learner-facing output.
Honest comparison
| Capability | Plugsky | Typical per-token API | Building in-house |
|---|---|---|---|
| API compatibility | OpenAI-compatible chat, embeddings and tools | Usually compatible | Full rewrite |
| Deployment | Cloud, VPC, on-prem and air-gapped | Mostly cloud-only | You operate GPUs and serving |
| Data residency | Region selection and sovereign options | Limited regions | You control fully |
| Pricing | Flat monthly self-serve, fair-use usage | Per-token, harder to forecast | GPU plus operations cost |
| Model choice | 30+ models behind one API | Varies by provider | You host every model |
| Industry fit | Lesson drafts, feedback drafts, admin comms, multilingual support | Generic API, you adapt it | You build every workflow |
Frequently asked questions
Can we keep our existing OpenAI SDK code?
Yes. Plugsky exposes an OpenAI-compatible API, so you change the base URL and model name and keep your integration.
Is there a free plan?
Yes. The free plan includes two free models, plugsky-micro and plugsky-lite, and does not require a credit card.
Can student records be used in prompts?
Only with a documented purpose, a lawful basis and institutional approval. Prefer de-identified or aggregated content, and confirm the DPA terms in writing.
How does pricing work?
Self-serve plans are flat monthly with unlimited fair-use usage; education agreements can add residency and support terms. See the live pricing page for current plans.
Does Plugsky use our data for training?
Plugsky processes customer data to provide the service; training exclusion belongs in your DPA. Confirm the current terms with the enterprise team.
Which endpoints are live today?
Chat completions, streaming, JSON mode, function calling, embeddings, RAG and agents are live. Audio, images, moderation, files, batch, fine-tuning, assistants and the responses API are coming soon.
Can it support multiple languages?
Yes. The same chat endpoint handles multilingual input and output; validate quality with staff who speak each language before family-facing use.