DCS Design and Implementation Services

Move from dependency to controlled delivery.

DCS turns assessment evidence into a staged migration from Microsoft 365/Azure/Copilot, Google Workspace/Cloud/Gemini, ChatGPT, Claude, and other non-transparent AI services toward a data-resident DCS environment built around OpenDesk, open-source collaboration, and self-hosted Mistral private AI where appropriate.

Request an implementation plan Download spec sheet

Why it matters

Migration is governance work, not just data movement.

The goal is to bring critical information assets, access decisions, records evidence, collaboration spaces, export paths, AI workflows, and selected cost levers back under the organization's policies. DCS starts with the workflows where control and cost benefit overlap, while preserving compatibility with the tools users already know.

Target environment

OpenDesk plus private AI, delivered as an operating model.

The target can include OpenDesk components such as Nextcloud, Collabora, XWiki, OpenProject, Matrix/Element, Jitsi, OX App Suite, Nubus/Keycloak-style identity integration, and a DCS private AI gateway using Mistral where appropriate.

Delivery model

From assessment to implementation to managed control.

The implementation work turns assessment evidence into a controlled pilot, validates adoption and cost assumptions, then prepares the environment for trusted managed operations.

DCS delivery model showing Assess, Implement, and Manage around a secure data and AI control core.

High-level project plan

A staged path from assessment to production.

W10

W11

W12

Discover and Design

Scope, risks, architecture

Build Foundation

Platform, identity, backup

Configure Governance

Roles, audit, retention

Migrate Pilot Workflows

Files, records, knowledge

Enable Private AI

Mistral, RAG, permissions

Validate and Handoff

Test, train, operate

Implementation scope

Designed for controlled coexistence first, expansion second.

Target-state architecture and migration strategy Microsoft, Google, Copilot, Gemini, ChatGPT, and Claude dependency mapping License transition, cloud waste, and AI token-control planning OpenDesk and open-source workplace design Identity, SSO, MFA, roles, groups, and privileged access Data-resident storage, collaboration, knowledge, and records workflows Mistral-enabled private AI and RAG design Security, audit logging, backup, retention, export, and recovery baseline Training, adoption, go-live, and managed-services handoff

Deliverables

What clients receive.

Target architecture

A practical design for the DCS environment, coexistence model, identity integration, and platform components.

Migration wave plan

A phased plan for moving sensitive workflows while validating license, cloud, and AI spend assumptions.

Pilot environment

A working DCS environment for selected data, communication, knowledge, project, or AI workflows.

Operations handoff

Runbooks, test evidence, support process, and readiness package for DCS Managed Services.

Next step

Turn assessment findings into a controlled pilot.

DCS Design and Implementation Services are the bridge between strategy and production. The best first project is usually a board workspace, secure data room, private AI assistant, or records-heavy collaboration workflow where control, adoption, and cost evidence can be proven together.

Implementation spec sheet