01
Persistent advisory records
Each case has a structured home in the product, allowing context to carry forward instead of resetting with every new conversation.
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Case study
AI assistance inside an owned decision process
AI Decision-Support & Advisory SaaS
An advisory product that keeps AI-assisted analysis inside an owned workflow, so recommendations can be challenged, revised, accepted, and revisited instead of disappearing into chat history.
AI decision supportAI advisory SaaSHuman-reviewed AIAdvisory workflow
Client
Private AI Advisory SaaS Client
Status
Launched
Category
AI Integration & Workflow Automation
Timeline
2026
Overview
The advisory case became the product object, not the chat session
The client was building a SaaS product for situations where AI could help a user work through an open-ended choice. That required more structure than a sequence of prompts and answers. The work needed a durable place in the product so it could continue over time.
That structure also made responsibility clearer. Different people could contribute at different stages, and an authorized user could send the work back for revision or accept the outcome when it was ready.
Product context
The product needed a clear boundary between AI assistance and final authority. A recommendation could help move the work forward, but an authorized person still needed to choose what happened next.
Challenge
A recommendation needed ownership and state
Without an owned record, teams can lose track of what is being considered, what changed after feedback, and whether anyone actually accepted the recommendation. The product needed to preserve those distinctions without presenting AI output as the final authority.
What we built
We designed the product around the advisory lifecycle
The system separates the AI-assisted contribution from the controls that determine ownership, feedback, revision, and acceptance.
02
Role-aware participation
Different users can contribute with different levels of authority, so participation and final acceptance do not collapse into the same action.
03
Visible revision loop
An authorized user can send the work back when the current recommendation is not ready, making iteration an explicit product state rather than an informal side conversation.
04
History and reporting
Dashboards and activity history make it easier to see where a case stands and how it changed as the advisory process progressed.
Result
AI-assisted advice became something a team could operate
The launched SaaS gives advisory work continuity beyond a single AI interaction. A case can stay owned, move to the right person, return for another pass when needed, and reach an accepted outcome without hiding those changes inside conversation history.
The boundary is visible in the product itself. AI contributes analysis, while people retain responsibility for the action that follows.
The impact
Why this mattered
The value came from what these decisions changed for the people using the product and the team responsible for running it.
Advisory work gained continuity
A case remains available as an owned product object instead of ending when one AI interaction is over.
Feedback could change the path
A recommendation can return for another pass before acceptance, making iteration visible and recoverable.
Final authority stayed human
The product keeps the acceptance step with an authorized person instead of turning an AI response into an automatic outcome.
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