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 | Literature synthesis, regulatory drafting, intake summaries, lab docs |
| Integration path | Connects to RIM, CTMS-adjacent, QMS and document systems via 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
- Synthesise and draft; keep qualified review on every output.
- Record reviewer, model version and sources for traceability.
- Index approved revisions only, never mixed drafts.
- Keep patient data out until privacy terms are settled.
- Start free with plugsky-micro and plugsky-lite, no card required.
How it works, step by step
- Pick one document class, such as literature briefings or SOP training drafts.
- Agree with quality how the workflow is verified and documented.
- Build a revision-controlled index of approved source documents.
- Build against the OpenAI-compatible endpoint with logging and audit export.
- Require reviewer sign-off and record model version per output.
- Extend to another class only after the first is stable and documented.
Original data
Try it yourself
Open the embedding model comparison →
Where an AI API fits in life sciences
The value is in synthesising dense, regulated documents. Every workflow should have a qualified reviewer and a retrievable record:
- Literature synthesis: summarise publications and competitive intelligence into referenced briefings.
- Regulatory drafting support: assemble first drafts of module sections from approved source documents.
- Protocol and admin summaries: condense protocol amendments and correspondence into reviewer-ready summaries.
- Safety intake summaries: structure adverse-event intake notes for qualified pharmacovigilance review.
- Training content: turn approved SOPs into draft training material for QA review.
Security, privacy and data handling
Regulated content demands data integrity, traceability and human accountability by design:
- Keep patient data out of prompts unless there is a documented basis and approved environment.
- Log inputs, outputs, model version and reviewer so records are reconstructable.
- Keep validation expectations in view; document how each workflow is verified and controlled.
- Require qualified review for anything regulatory, clinical or safety-related.
Deployment options and model choice
Regulated content usually sits in a private or region-locked environment, with per-document-class access. The same OpenAI-compatible API runs across Plugsky cloud, a private endpoint in your VPC, on-prem and air-gapped, with region-locked planes for residency. One key reaches 30+ models, including open-weight options for offline deployment, and migration is 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 remain coming soon. The free plan includes plugsky-micro and plugsky-lite with no card, and a 14-day full-access trial covers paid tiers — see the live pricing page for current plans.
From pilot to production
In a validated environment, undocumented shortcuts create findings. Avoid:
- Running a pilot outside the quality system, then retrofitting documentation.
- No reviewer identity or model version in the record.
- Mixing approved and draft source documents in one index.
- Assuming a general-purpose model output is submission-ready.
- Handling patient data before privacy and contract terms are settled.
Choose one document class, index only approved revisions, and record reviewer, model version and sources for every output. Treat prompt changes as controlled changes, and expand only after the quality function signs off.
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 | Literature synthesis, regulatory drafting, intake summaries, lab docs | 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.
Is Plugsky validated for GxP?
No validation claim should be assumed. Document your own verification approach and validate controls with the enterprise team.
Can it process patient data?
Only in an approved environment with a lawful basis and contract terms that cover it. Prefer de-identified content where the workflow allows.
How does pricing work?
Self-serve plans are flat monthly with unlimited fair-use usage; enterprise agreements cover private deployment, residency and SLA terms. See the live pricing page for current plans.
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.
How do we keep an audit trail?
Log the requester, prompt, retrieved sources and revisions, model version and reviewer for every assisted output, and export logs to your records system.