The operating problem
Sensitive records, protected data, client files, research IP, and operational telemetry often cannot leave the organization or be processed by a vendor-controlled AI service.
Solution Playbook
Canadian sovereign AI deployment
Deploy private AI workflows for Canadian organizations that need data residency, customer-owned infrastructure, local model options, and reviewable human approval.
Canada-first
rollout planning for customer-owned infrastructure, Canadian private cloud, isolated networks, or approved model endpoints
7
systems and data sources in the playbook
6
repeatable workflow steps before approval
4
control points for human review
Customer profile
Who this is for.
Canadian public-sector teams, defence suppliers, financial institutions, life sciences groups, energy and manufacturing operators, and professional firms that cannot send sensitive work into black-box AI SaaS.
The OpenTeam outcome
OpenTeam scopes a private AI workspace, connects approved data sources, routes work through customer-approved model endpoints, and keeps outputs inside a reviewable approval process.
Connected systems
What OpenTeam connects for this workflow.
Available connectors and built-on-request integrations are separated on purpose, so customers can see the current starting point and the custom scope for rollout.
4 Available 3 Built on request
Customer-owned compute
Built on requestBare metal, private virtualization, GPU nodes, or isolated network environments selected and governed by the customer.
Canadian private cloud or VPC
AvailableCloud inventory and deployment context for customer-approved Canadian regions, private networks, and infrastructure controls.
Azure private cloud
AvailableMicrosoft cloud context for organizations standardizing on Azure landing zones, identity, storage, and private network policy.
License-reviewed local models
Built on requestSelf-hosted or open-weight model endpoints such as Llama, Mistral, Qwen, or DeepSeek, selected after license, security, and infrastructure review.
Private documents and Team files
AvailableControlled access to policies, contracts, reports, research files, SOPs, and working documents used by the AI workflow.
Internal databases and exports
AvailableRead-only schema context, approved SQL access, exports, or customer data marts used for private retrieval and analysis.
Compliance evidence pack
Built on requestCustomer-specific mapping for data residency, Protected B-style controls, CPCSC/ITSP.10.171 readiness, Controlled Goods, privacy, and internal policy evidence.
Daily workflow
How the work runs.
These are the repeatable steps a customer can turn into a Team workflow, skill, or managed review process.
01
Classify the data and use case
Separate public, internal, confidential, regulated, protected, and export-controlled data before choosing the AI deployment pattern.
02
Choose the deployment boundary
Decide whether the workflow runs in a Canadian private cloud, customer VPC, on-prem environment, or isolated network with no public egress.
03
Select model and retrieval paths
Pick local or private model endpoints, define approved retrieval sources, and document when a commercial endpoint is allowed or blocked.
04
Connect private knowledge sources
Index approved documents, databases, files, and exports with source links, access boundaries, retention expectations, and review owners.
05
Build approval-gated workflows
Turn prompts into repeatable Team skills where summaries, analyses, drafts, and actions stay visible before a person approves them.
06
Operate and audit the workspace
Keep deployment notes, model choices, source references, access decisions, and reviewer history available for security, legal, and leadership review.
Ask OpenTeam to
Copyable customer requests.
Assess this Canadian AI use case and identify which data classes must stay inside our private environment.
Compare private cloud, on-prem, and isolated deployment options for this workflow, including approval and audit requirements.
Prepare a local-model rollout plan using only approved documents, databases, and source-linked retrieval.
Draft a governance brief for leadership showing model choices, data residency assumptions, human review points, and unresolved compliance questions.
Expected outputs
What the workspace produces.
Private AI deployment assessment
Data residency and model-boundary map
Local model and retrieval architecture notes
Compliance evidence checklist
Approval-gated pilot workflow
Executive rollout brief
Approval controls
Where people stay in the loop.
OpenTeam should not be represented as certified for Protected B, CPCSC, CMMC, Controlled Goods, or any regulated framework unless certification evidence exists.
Model licenses, export-control concerns, and data-use restrictions require legal, security, and procurement review before deployment.
Customer data classifications, retention decisions, network boundaries, and key-management choices remain customer-owned decisions.
External API use, outbound messages, database writes, file changes, and operational actions stay behind explicit human approval.
Rollout path
How to start.
1
Start with a confidential but bounded pilot, one data domain, one model boundary, and read-only access to approved sources.
2
Document data residency assumptions, model licenses, security controls, reviewer roles, and evidence required by the customer compliance team.
3
Add more models, RAG sources, Team skills, and isolated deployment controls only after the pilot has stable review and audit behavior.
Deployment support
Forward-deployed engineering when the workflow needs hands-on rollout.
Some teams can start with the playbook and existing connectors. Enterprise teams can add a forward-deployed engineer package when the workflow requires custom system access, onsite discovery, user enablement, or a measured production launch.
Map
Confirm the source systems, permissions, approval owners, exception paths, and success measures for this workflow.
Build
Connect available apps, create custom connector or export paths, and turn repeated operator steps into reusable Team skills.
Launch
Run a controlled pilot, train the first users, document the runbook, and graduate the workflow from prototype to production use.
Related playbooks
Build the next workflow around it.
Custom systems
ERP and custom integrations
Use forward-deployed engineering to connect ERP, custom databases, APIs, exports, and operating documents around a production workflow.
Files to workflow
OneDrive and document operations
Search, read, summarize, organize, and produce work from OneDrive, SharePoint, Google Drive, Office files, PDFs, and email attachments.
Legal work product
Legal workflows
Move from matter intake to source-backed research, draft client communications, closing checklists, deadline reviews, and lawyer-approved work product.
OpenTeam prepares operational work inside a Team workspace. Customers remain
responsible for professional review, compliance decisions, and final approvals.
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