Research assistants
Gather and organize bounded information.
aiqorxAI & intelligent workflows / AI Agents
An AI agent combines instructions, tools, and execution state to perform a specified class of tasks.
Talk through your project
A connected engineering approach
People, tasks, accessibility
Components, logic, integrations
Data, operations, maintenance
The architecture follows your product requirements.
01 / Where it fits
Gather and organize bounded information.
Review an output against supplied evidence.
Help navigate a defined product workflow.
02 / Architecture
Specify allowed inputs, tools, outputs, and escalation behavior for each role. Keep credentials and approvals outside untrusted text.
A second agent is not automatically an independent source of truth. Verify critical outputs against records or rules.
03 / Delivery & care
Evaluate representative inputs alongside ambiguous, adversarial, and unsupported requests. Track quality, latency, cost, and human corrections against a defined acceptance set.
Review the users, existing systems, constraints, and definition of success.
Document the architecture, interfaces, risks, and delivery scope.
Review working increments against real use cases and failure conditions.
Prepare operating guidance, ownership, and a practical maintenance plan.
04 / A few useful questions
A second agent is not automatically an independent source of truth. Verify critical outputs against records or rules.
Start with a code and architecture review. The useful outcome is a clear decision about what to keep, improve, or replace, with the dependencies and delivery risks made explicit.
The estimate depends on the workflows, integrations, platform requirements, and quality expectations. A focused discovery phase can reduce uncertainty before committing to the full build.
Agree on source ownership, documentation, monitoring, support responsibilities, and a maintenance plan as part of the engagement.
Something in mind?
Let's build