AI & Automation
AI Enablement
The question isn't whether your organization should be using AI. It's which tools, for which tasks, configured and deployed in a way that actually gets used.
Where Most Organizations Start
Formalizing what's already happening.
The most common pattern we see: a handful of staff are using free-tier AI tools on personal accounts, the organization hasn't made a formal decision, and there's a growing gap between what AI-forward employees are doing and what the organization officially supports.
Formalizing that is the starting point. It means evaluating the right enterprise AI subscriptions, configuring them correctly, connecting them to your identity infrastructure so access is managed through your directory, and helping teams understand what these tools actually do well.
The Models
The models we work with
We work daily with Claude (Anthropic), ChatGPT (OpenAI), and Gemini (Google) across client engagements. Our recommendation on which to use is always task-specific — these models have genuinely different strengths, and the answer isn't the same for every use case.
Our deepest experience is with Anthropic's Claude. It's the model we use for our own operations, infrastructure development, and client work where agentic capability matters. For reasoning-heavy tasks, code generation, complex document work, and autonomous agent deployments, Claude is our default recommendation — and the model where we've pushed the boundaries furthest.
For organizations in the Microsoft ecosystem, Microsoft 365 Copilot's integration with Teams, Outlook, and SharePoint often makes it the right choice for specific productivity workflows. For Google Workspace-first environments, Gemini's native integration changes the calculus. We don't have a religious position — we have an honest one.
What We Help With
What enablement looks like in practice.
Enterprise subscription setup
Claude for Teams or Enterprise, ChatGPT Team or Enterprise, Google Gemini for Business — each has different licensing models, admin controls, and data handling commitments. We evaluate and configure the right tier for your organization’s size, data requirements, and budget.
Identity and access integration
Enterprise AI tools should be provisioned through your identity provider like any other business application — SSO, SCIM provisioning, and access tied to your directory. Employees should access AI tools with their work credentials, and access should be revoked automatically when someone leaves.
Use case identification
The highest-value AI use cases are usually not the most obvious ones. We run structured sessions with teams to identify where AI genuinely saves meaningful time — not tasks where it sounds impressive but tasks where it demonstrably changes the work.
Workflow development
We build and document AI-assisted workflows for specific team functions: drafting and editing, research, summarization, data analysis, customer communication, internal documentation. These aren’t generic prompts — they’re tested workflows designed around how your team actually works.
Training and adoption
Tool availability doesn’t produce adoption. We run practical training sessions focused on what makes AI tools more or less useful — how to frame tasks, what to trust and verify, where AI reliably helps versus where it introduces risk.
The Progression
Where enablement leads
AI Enablement is the starting point. For organizations that want to go further — connecting AI to the platforms they run on, deploying agents that take actions autonomously, and governing that access properly — we build that infrastructure too.
The MCP Tooling, Agent Governance & PAM, and Audit & Accountability services are the next layer. Most clients start with enablement and graduate to one or more of those as their use of AI matures.
Let's Talk
Not sure where to start? That's the most common situation.
Let's figure out what makes sense for your organization.
Schedule a conversation