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An agent built for enterprise use: permissioned, auditable, evaluated, monitored, with fallback paths and human handoffs — not a demo agent in a production slot.

An AI system that uses context and tools to perform steps in a workflow under defined constraints, rather than just answering a question.

A workflow built on a governed object model so actions, permissions, and context align with the customer's actual business entities — not arbitrary database rows.

A customer- or field-built extension using low-code configuration wherever possible and code only where necessary.

A deployment isolated to a specific customer or environment for security, compliance, networking, or data-control reasons.

Connecting a deployment to customer or cloud network resources through a controlled virtual private cloud — typically needed when the agent must reach internal APIs not exposed to the internet.

A deployment in an isolated environment with no or tightly controlled external network connectivity — changes how the FDE packages updates, credentials, and model access.

Connecting a cloud or SaaS deployment to systems running in the customer's own data center or managed infrastructure. Usually requires a gateway or proxy because the systems are not internet-facing.

The plan for sequencing technical work, customer decisions, risks, rollout, and handoff so implementation reaches production efficiently.

A deployment playbook specific to AI systems — covering use-case selection, data access, evals, model behavior, guardrails, monitoring, rollout, and adoption.

A practical guide for repeating a deployment: prerequisites, architecture, steps, blockers, owners, tests, launch plan, and support model. Lets another FDE run the same play without rediscovering everything.

A repeatable way to get a class of customer use cases into production — architecture, rollout, common blockers, support model — documented after the third similar launch.

A working implementation meant to demonstrate the recommended pattern and give future deployments a tested starting point.

A repeatable approach for connecting a class of systems — auth, data mapping, error handling, operational checks — documented after the second time it's needed.

A reusable product or platform function that can be configured or extended for customer needs without becoming bespoke code. FDEs push custom work toward this.

A concrete deliverable — diagram, runbook, eval set, integration spec, launch checklist, code sample — that helps a deployment move forward or be handed off.

Small, working code showing the right integration pattern or API usage — not a production implementation, but enough for the customer's engineers to build from.

An integration pattern where changes in one system emit events that trigger downstream workflows or updates in near real time.

A clear agreement about the schema, semantics, freshness, quality, and ownership of data flowing into a deployment. Without one, the deployment breaks silently when the source changes.

Connecting the deployment to the customer's single sign-on provider so users authenticate through enterprise identity controls. Usually required before the customer adds frontline users.