AI agents & tool integration

The task

A chat assistant can draft an answer, but a business task may require reading records, updating a system and knowing when to stop for approval.

Choose the right autonomy level

An assistant prepares information for a person. A bounded agent may call approved tools and propose changes, but pauses where the customer requires approval. Higher autonomy is considered only after the task, permissions, test cases and rollback are clear. The choice follows the risk and benefit of the actual workflow.

What Gateflow delivers

• A task and autonomy boundary: assistant, reviewed agent or a higher-autonomy workflow.
• Connections to approved knowledge and named tools, with identity and permissions.
• Human approval points for consequential actions, plus traces, test cases and fallback.
• An owner for costs, monitoring and later changes.

Delivery and acceptance

Gateflow begins with one workflow and one or two tools. Tool protocols such as MCP are chosen where they fit the customer systems. Production use follows a controlled pilot.

Where this fits

For teams that can name the action an agent should perform and the person accountable for the result.

What Gateflow needs to begin

The buyer defines the task, the tools an agent may use, data access limits, approval authority and the cost ceiling. Gateflow needs representative successful cases and failures to test before production access is granted.

How Gateflow checks the result

Gateflow tests ordinary, ambiguous and adversarial inputs. The checks cover wrong-tool calls, permission limits, the approval stop, trace completeness, cost and the behavior when a tool or model is unavailable.

What the customer receives at handover

A production owner receives the tool and permission inventory, test set, monitoring view, change procedure and a route to disable the agent safely.