GAT Solutions

AI adoption · Workflow engineering · MCP

Put enterprise AI to work inside the systems your team already runs

GAT deploys Claude and ChatGPT, connects them to Salesforce and the go-to-market stack, redesigns repeatable work around them, and installs the governance, training, evaluations, and monitoring required for production use.

Book a ConsultationSee the outcomes
  • 50+ Salesforce projects
  • 100+ integrations
  • 5.0 client rating
  • 6+ years Salesforce

Most companies now have AI licenses. Very few have AI leverage. The gap is adoption: nobody assigned the tools a real job, connected them to approved business context, redesigned the workflow for each role, or made the safe path easier than shadow AI.

We close that gap the way we closed it for ourselves. GAT has built 59 n8n automations — 21 running live in production — and ships ApexGenius, a Salesforce MCP that lets teams work with live org context from Claude or ChatGPT. The patterns we install for clients — MCP connections, agent workflows, automation, governance — are the ones our own business runs on every day.

And this goes beyond Salesforce. We roll out Claude, Claude Cowork, Claude Code, and ChatGPT for sales, operations, support, finance, and engineering teams; connect them to CRM, help desk, billing, documents, and internal tools; then train the people and measure whether the work actually changed.

Who this is for

Built for teams like yours

Teams with licenses, not leverage

Everyone has a ChatGPT seat and nothing about the work has changed.

  • Workflows designed role by role, not a generic AI training day
  • AI connected to your real systems through MCP, not copy-paste
  • Adoption you can measure in hours saved, not seats assigned

Founders automating the back office

Manual work is scaling faster than revenue is.

  • n8n automations built on patterns from the 21 we run live in production
  • Agent workflows that research, draft, and act with approvals
  • Human-in-the-loop checkpoints where judgment matters

Leaders who need AI governed, not banned

The team is already pasting company data into public chatbots.

  • An acceptable-use policy people can actually follow
  • Permission-aware MCP access instead of bulk data exports
  • Training that channels the enthusiasm somewhere safe

Capabilities

What AI adoption & workflow engineering covers

Claude adoption

Workspace rollout across Claude, Claude Cowork, and Claude Code with roles, permissions, Skills, approved use cases, and role-based playbooks.

ChatGPT adoption

Business or enterprise workspace rollout with plugins, apps, company knowledge, custom MCP connections, access controls, and repeatable team workflows.

MCP & system connections

Claude and ChatGPT wired to Salesforce, CRMs, help desks, documents, databases, and approved actions through MCP, APIs, identity, and permissions.

Workflow & agent engineering

Production workflows that research, draft, classify, and act across systems through n8n or custom orchestration—with approval gates where judgment matters.

Role-based enablement

Hands-on adoption by role, with workflow playbooks, office hours, champions, and usage measures—not one generic training session.

Governance, evaluations & operation

Acceptable-use policy, data boundaries, access controls, auditability, quality evaluations, monitoring, and a roadmap for continued improvement.

Outcomes

Numbers with stories attached

Every figure below comes from a GAT client engagement and is attached to the operating system that produced the change.

+50%

More leads converted with automated follow-up

Automated sequencing and Salesforce task orchestration converted half again as many leads from the same traffic.

GAT Solutions brought strong Salesforce and development depth, communicated clearly, delivered within the agreed timeframe, and earned the client's confidence for future work.

Salesforce delivery partnership · Verified client review

How we deliver

From operating problem to a system your team can run

  1. 01

    Adopt around real work

    Map where the hours go, select the work surfaces and use cases, define identity and policy, and launch role-based playbooks against real tasks.

  2. 02

    Connect and build

    Wire the approved MCP and API connections, then ship the first complete workflows, agents, or automations with human gates designed in.

  3. 03

    Operate and improve

    Measure adoption and quality, monitor failures and overrides, refresh the playbooks, and keep the governance model aligned as capabilities change.

Questions

Frequently asked questions

What does a Claude AI consultant actually implement?
Everything between the license and the leverage: Claude workspace configuration, Cowork and Claude Code rollout where they fit, Skills and MCP connections into business systems, workflows for the roles that need them, team enablement, and the governance model that makes real use safe.
Should our business use Claude or ChatGPT?
Usually both, assigned by task — they have different strengths, and the honest answer changes as the models do. We run both daily and built ApexGenius to work with each, so our recommendation is grounded in current production use, not a vendor relationship.
What is MCP, and why does it matter for a business?
The Model Context Protocol is an open standard that lets AI assistants securely read from and act on your systems — CRM, documents, databases — within permissions you control. It's the difference between an AI that gives generic advice and one that works with your actual data. It's also the layer our ApexGenius product is built on.
Can you connect AI to systems besides Salesforce?
Yes — Salesforce is a specialty, not a boundary. Through MCP and n8n we connect AI to help desks, email, calendars, spreadsheets, billing, databases, and internal APIs. Our own operation runs 21 live n8n automations across exactly that kind of stack.
How do you keep company data safe during an AI rollout?
Governance is part of setup, not an afterthought: business-tier workspaces with training-data controls, permission-aware MCP connections instead of bulk exports, sensitive-data boundaries, and a written acceptable-use policy. The rollout makes the safe path the easy path — which is what actually stops shadow AI.
What does an AI adoption engagement cost?
Scope depends on the number of workspaces, teams, connections, and workflows involved. Book a consultation and GAT will recommend a focused pilot, a broader adoption program, or a custom engineering path based on the work you want to change.

Initial systems consultation

Turn AI licenses into AI leverage.

Book a ConsultationStart with the Audit
  • You leave with
  • A focused consultation with a senior systems consultant
  • A current-state fit and architecture read
  • A recommended path — implementation, ongoing ownership, or product