Give each agent a job it can finish.
A useful agent starts with a specific piece of work. We turn that work into a role, connect the knowledge and tools it needs, and configure how it produces a result you can use.
Illustrative setup
Set up an agent that prepares customer reviews from our meeting notes and account history.
The agent receives a defined research brief, access to the relevant sources and a repeatable output format. It prepares a referenced review, identifies missing information and leaves customer-facing actions to the agreed approval step.
Illustrative scenario, not a live product result.Start with the work and its owner
We define the agent’s purpose, its inputs and the result that counts as complete. A research assistant, account specialist and engineering reviewer need different instructions. The brief also names the person who owns the workflow and the situations the agent should hand back instead of guessing.
- A role and a bounded task
- An output format with completion criteria
- An owner for questions and exceptions
Configure the environment around the role
We set up the instructions, model choice, available skills and tool connections in the selected agent environment. Memrain supplies persistent context through MCP. Source grants determine which knowledge the agent can retrieve and where it can save updates; application connectors provide any additional data or actions.
Make the setup usable from day one
We run representative tasks, inspect the result and document how to start the workflow. You receive the role brief, configuration, source map and worked examples. A personal setup can begin with one agent; a team setup can add specialist roles when the work benefits from separate responsibilities.
Keep the context. Move the work forward.
Connect your knowledge to the AI you already use. Find your starting point and make the next conversation count.