Key facts
| Engagement isolation | Separate API keys or endpoints per client and engagement |
| Access control | Scoped keys with rotation; enterprise SSO and RBAC options |
| Deployment | Cloud, VPC, on-prem or air-gapped for restricted engagements |
| Data grounding | Embeddings and RAG are live for methods, research and deliverables |
| Auditability | Request, source and response logging per key |
| Structured output | JSON mode returns deliverable sections and review records in schemas |
| Pricing model | Flat monthly self-serve plans; no per-token billing on self-serve |
| Endpoint roadmap | Audio, images, moderation, batch and fine-tuning are coming soon |
TL;DR
- Isolate engagements with separate keys and namespaced retrieval.
- Never let one client's content enter another client's context.
- Give subcontractors scoped, revocable access with their own logging.
- Honor client residency commitments per engagement, not per firm default.
- Review every client-facing output before it leaves the firm.
How it works, step by step
- Map each AI workflow to the engagements and client data it may access.
- Issue separate keys per engagement or client and namespace all retrieval indexes.
- Record client residency and confidentiality commitments and choose deployment accordingly.
- Define a subcontractor access process with scoped keys, logging and time-bound revocation.
- Index methodologies and approved research separately from client-specific material.
- Gate deliverables through a review step that checks claims, citations and confidentiality.
- Audit key inventories and retrieval namespaces after every engagement close.
Try it yourself
Open the AI data residency checklist →
Engagement isolation by design
Consulting firms routinely work for competing clients, which makes cross-contamination the primary risk. The controls are concrete: a distinct API key per engagement or client, a retrieval namespace per engagement, and no shared conversation history across accounts. If a workflow needs cross-engagement synthesis, use anonymized and aggregated inputs reviewed by the engagement lead first.
Where a client requires stronger separation, use a dedicated endpoint or private deployment for that account. The OpenAI-compatible interface keeps the workflow identical.
Subcontractors, partners and access lifecycle
Delivery often runs through associates, subcontractors and partner firms. Give each external team its own scoped key, keep secrets in a manager they cannot read directly, and set expiry dates that match the engagement. Enterprise SSO and RBAC options govern console access, so departures remove permissions centrally.
Reconcile the key inventory at engagement close: dormant credentials after a project ends are a recurring audit finding.
Client residency and confidentiality commitments
Client contracts often specify where data may be processed and who may see it. Translate each commitment into an architecture decision: region selection for cloud workflows, and VPC, on-prem or air-gapped deployment where the contract requires it. Document the data path per engagement so a client security review has evidence rather than assurances.
See the DPA checklist for the terms to compare before signing.
Deliverable review and quality control
Generated content belongs in the same quality process as human drafts. Require citations for factual claims, check for client identifiers that should not appear in shared material, and keep a named reviewer for every client-facing output. Structured output in JSON mode lets a checklist validate required sections automatically, while the reviewer owns judgment and tone.
Honest comparison
| Control area | Plugsky capability | Common gap | Owner |
|---|---|---|---|
| Engagement isolation | Keys and namespaces per client | One shared workspace key | Delivery IT |
| Subcontractor access | Scoped, revocable keys with per-key logging | Long-lived shared credentials | Resourcing |
| Residency | Region selection plus VPC, on-prem and air-gapped | Firm default ignores contract | Legal |
| Confidentiality | Retrieval scoped to engagement content | Client docs in general indexes | Engagement lead |
| Audit trail | Request and source logging per key | No client-level traceability | Risk and compliance |
| Deliverable review | Citations and structured output for checks | AI drafts sent unreviewed | Quality partner |
Frequently asked questions
How do we prevent cross-client leakage?
Use separate keys and retrieval namespaces per engagement, avoid shared conversation state, and require review before any cross-engagement synthesis using anonymized inputs only.
Can client data stay in a specific region?
Yes for supported regions, and by construction with private deployments. Translate each contract commitment into an architecture choice and document the data path per engagement.
What access should subcontractors have?
Scoped keys limited to the engagement, stored centrally, with expiry dates and per-key logging. Remove access at engagement close as part of the checklist.
Is fine-tuning available for firm methodologies?
Fine-tuning is coming soon. Prioritize retrieval over approved methodologies, which keeps citations and updates immediately when methods change.
How do we review AI-assisted deliverables?
Require citations for claims, run a confidentiality check for client identifiers, and have a named reviewer approve the output before delivery.
Which endpoints are live today?
Chat, streaming, JSON mode, function calling, embeddings, RAG and agents are live. Audio, images, moderation, files, batch, assistants, responses and fine-tuning are coming soon.
Where should a pilot start?
Pilot on public research and internal methodology with the free plan, then extend to one client engagement with isolated keys and logging in place.