What is creating the friction?
For an agency managing multiple client requests, deadlines, and delivery teams, work changes hands without a clear owner. The visible signal is items aging in shared inboxes and handoffs that depend on memory. In insurance, that friction is amplified by submission, policy, claims, and service work where accuracy and traceability matter.
The first useful question is not "Which AI tool should we buy?" It is "What should happen from the first request to a review-ready case or matter record with clear scope, and who owns each handoff?"
What does a practical first workflow look like?
Design the first version around a review-ready case or matter record with clear scope. Capture the request, associate relevant information from existing business software, assign an owner, record status, and make exceptions visible. Keep scope to one workflow type or team so baseline and adoption signals stay clear.
- Define ownership rules, fallback owners, and an escalation clock.
- Define the trigger and the review-ready outcome.
- Preserve source context and capture required information once.
- Assign ownership, fallback ownership, and the next action.
- Route ambiguous cases to human review.
Where can AI assist?
For case or matter intake, useful assistance may include organizing intake notes, spotting missing facts, and preparing a human review brief. AI should assist a defined task, show enough context for review, and have a safe fallback when confidence is low.
Do not use an AI output as an unreviewed decision in a consequential workflow. The appropriate controls depend on the data, decisions, permissions, retention, and regulatory context of the company.
How should a team measure the change?
Baseline the current workflow before implementation. Track the measure closest to a review-ready case or matter record with clear scope, plus time to first response, percentage of work with an owner, manual touches, rework, queue age, exception rate, and adoption. For this problem, start with items aging in shared inboxes and handoffs that depend on memory and turn one signal into a weekly operating review.
What should happen next?
A 30-minute discovery chat is the right first step when the workflow is recurring and important enough to improve. Bring one example, the systems involved, the people who do the work, and what "better" would mean. Herculean can then identify whether the right next step is no project, a free short pilot, a paid pilot, or recurring AI engineering support.