GPT for reasoning, the Agents SDK for tool-using workflows, and Azure OpenAI when your security team wants Microsoft-stack residency. We implement the path that matches your controls, then connect it to Salesforce, n8n, and your memory layer.
These are the use cases we usually pair with OpenAI. Each one is a real page, not a slogan.
Follow-up and enrichment agents on top of Salesforce.
Reasoning layer for voice and chat, with memory behind it.
Spec, ticket, and research agents for product teams.
Drafting and campaign variants with human review.
OpenAI API
Direct access for product and engineering teams building internal agents.
Azure OpenAI
Same models inside your Azure tenant, with Microsoft identity and regional controls.
Agents SDK
Tool-calling agents that can reach Salesforce, ERP, and internal APIs through MCP.
Model routing
Send a task to OpenAI, Claude, or Gemini based on cost, latency, and policy.
Tell us what you are working with. We respond within 24 hours with a frank assessment of what it would cost, how long it takes, and whether it fits your situation.
Get in TouchTell us what you are working with. We respond within 24 hours with a frank assessment of what it would cost, how long it takes, and whether it fits your situation.
Get in TouchYes. Azure OpenAI is the usual path when data residency, Microsoft identity, or an existing Azure estate matters. The public API is faster to start when those constraints are not in play.
Both. We deploy GPT as a model and the Agents SDK as a runtime. Agents then call your tools through MCP and, when needed, talk to other agent frameworks over A2A.
No. We routinely route legal work to Claude and Workspace tasks to Gemini. OpenAI is one option in the stack, not the stack.
Per-team budgets, model routing, and logging. You see which use case spends what before the bill surprises finance.
Tell us whether you need the public API, Azure OpenAI, or an agent runtime. We will come back with the architecture and the gaps.
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