Start with the work.
An agent is useful when a task needs interpretation across several steps. A fixed workflow is often sufficient when the rules and sequence are already known.
Build assistants and agents for defined business tasks, with approved data, limited permissions and a human review path.
An agent is useful when a task needs interpretation across several steps. A fixed workflow is often sufficient when the rules and sequence are already known.
Founders and teams with repeat research, document handling, support triage or internal knowledge work.
Example tasks, approved sources, access boundaries, review rules and the person responsible for operation.
These are the main result areas for this work. The final scope depends on the current process, systems, people and constraints.
Defined against the business need and reviewed as part of the delivery.
Defined against the business need and reviewed as part of the delivery.
Defined against the business need and reviewed as part of the delivery.
Defined against the business need and reviewed as part of the delivery.
The exact delivery changes by project, but the sequence stays practical: understand the work, build the right thing and improve it after real use.
Select one task, its source material and the actions the agent may take.
Connect approved information and tools. Require approval for consequential actions.
Check normal cases, missing information, misleading instructions and failed tool calls before controlled use.
The task has a measurable output, an owner and information the business is authorised to use.
Example tasks, approved sources, access boundaries, review rules and the person responsible for operation.
Use these related Martzine tools and resources to define the work before a project starts or verify part of the decision.
The structured sections above give the quick path. The existing Martzine content below keeps the longer explanation and supporting links available for people who need more detail.
Build assistants and agents for defined business tasks, with approved data, limited permissions and a human review path.
An agent is useful when a task needs interpretation across several steps. A fixed workflow is often sufficient when the rules and sequence are already known.
Founders and teams with repeat research, document handling, support triage or internal knowledge work.
Select one task, its source material and the actions the agent may take.
Connect approved information and tools. Require approval for consequential actions.
Check normal cases, missing information, misleading instructions and failed tool calls before controlled use.
The task has a measurable output, an owner and information the business is authorised to use.
Example tasks, approved sources, access boundaries, review rules and the person responsible for operation.
Relevant Martzine tools and resources can help prepare the work. Make Knowledge Work Easier to Review · Use an Assistant for Approved Business Knowledge · Automation & Workflows.
AI Agent Development can vary by workflow, systems, access, data quality and the amount of change required. Where the requirements are not stable, discovery is used before implementation and the exact deliverables are agreed before the work starts.
Share the business problem, current process, desired outcome and known constraints through Martzine contact. The first useful conversation is about the work, not a pre-selected software stack.
Do not force the problem into a preset service. Tell us what you need and we can start from the work itself.
Tell us what needs to be done and where the work is today.
Request a ServiceStart with the business problem when the right path is not obvious yet.
Request a SolutionShare the workflow, users and first-release requirement for a custom system.
Start an Application ProjectHave a product, tool, calculator or workflow idea? Put it in front of us.
Suggest an IdeaTell us what you are trying to build, what problem you are solving and where the digital part becomes difficult. Martzine is built around that gap. Start with the outcome and the constraint, then work back to the right digital layer.