01
Research agents
Assemble company, customer or case context from approved sources and show the evidence behind the result.
AI AgentsAgents that do the work.
Agents that do the work.
Built around your operation.
We build AI agents that gather context, reason through a task and carry out agreed actions across your systems. From commercial research to operational casework, each agent has a clear job, tested boundaries and a route back to your team.
Research · operational casework · controlled actions
Related workDwyer Enterprises2 to 4 weeksto a focused working proof
Senior engineeringresponsible for the implementation
Magus.AGENT WORKFLOW
From request to next action
ExampleRequestContextPrepared case
01
UnderstandRead the request and find its records
02
PrepareCheck evidence and flag gaps
03
RouteSend the next step for review
A bounded agent, connected to the operating workflow.
Read the request and retrieve the relevant business context.
01 · THE WORK
Built for the work your business needs
We build AI agents that gather context, reason through a task and carry out agreed actions across your systems. From commercial research to operational casework, each agent has a clear job, tested boundaries and a route back to your team.
02 · THE IMPLEMENTATION
Where it can make a difference
02
Operational agents
Triage incoming work, compare records, investigate exceptions and prepare the next step.
03
Action taking agents
Update systems, coordinate followups and execute approved steps with an activity history and clear escalation.
03 · THE IMPLEMENTATION
What we implement
01
Define the job
Agree what the agent may decide, what it may do and when it must involve a person.
02
Connect the context
Give it the records and tools needed for the task, with access limited to its role.
03
Test beyond the happy path
Evaluate missing data, conflicting evidence and tool failures before introducing live actions.
IMPLEMENTATION EXAMPLE
From an incoming request to a prepared next step
A request arrives with documents attached. An agent prepares the work before the responsible team picks it up.
THE EVIDENCE
What the system needs
- Incoming request and attached documents
- Relevant customer or case records
- Approved routing rules and task permissions
THE CHECKS
What this example checks
- Identify the request and retrieve the matching records.
- Compare the request with the available evidence and flag missing or conflicting details.
- Prepare the next task, route it to the right owner and request approval before any consequential action.
THE WORKING RESULT
What reaches the team
A prepared case with source records, outstanding questions and a proposed next step.
The decision boundaryThe team approves consequential actions and reviews uncertainty. The agent only performs the actions explicitly allowed for its role.
WHAT THIS EXAMPLE WOULD TEST
Compare preparation quality, routing accuracy and review effort against historical examples. Include missing records and unavailable tools.
Illustrative implementation scope. This describes a possible build, rather than a claimed client result.
05 · THE WORK
From a useful proof to daily use
We compare completion quality, review effort and time against the current process. A useful agent must handle the difficult cases or stop clearly when it cannot.
A focused proof of concept ships in 2 to 4 weeks. We use the findings to scope production integrations, access, monitoring, rollout and support.
DELIVERED THROUGH OUR SERVICES
The work behind the solution.
YOUR NEXT STEP
Where could an agent take a process further?
Bring us one workflow, real examples and the people who know the work. We’ll identify a practical first build.