Applied AI use case / product recommendation and quote assistant
Help buyers find a suitable option and prepare the right commercial next step.
Requirements, constraints, configuration and quote preparation joined into a guided buying workflow.
The assistant maps customer requirements to approved product rules, explains relevant options and prepares a quote request for commercial review.
- Delivery
- sales
- Scope
- Human-owned
- Control
- Measured outcome
Business workflow
Relevant recommendation- 01Customer requirement
- 02Approved catalogue
- 03Configuration
- 04Suitability decision
- 05Commercial review
- 06Quote preparation
- 07Qualified recommendation
The operating problem
Complex catalogues and service configurations force buyers and sales teams to repeat discovery before a suitable option or quote can be prepared.
System mechanism
Product recommendation and quote assistant workflow
A real operating path showing the information, decisions, systems and accountable people required to produce a useful result.
Product recommendation and quote assistant: Customer requirement to Approved catalogue to Configuration to Suitability decision to Commercial review to Quote preparation to Qualified recommendation.
- 01Business inputCustomer requirement
The intended use, constraints and priority are captured.
- 02Approved contextApproved catalogue
Current products, services and evidence provide the answer boundary.
- 03Controlled workflowConfiguration
Compatibility and required options are evaluated.
- 04Decision pointSuitability decision
The workflow exposes alternatives, limits and missing information.
- 05Human gateCommercial review
Pricing exceptions and consequential claims return to sales.
- 06Business systemQuote preparation
The selected configuration and buyer context enter the quoting process.
- 07Business valueQualified recommendation
The buyer receives a relevant option and clear next action.
Fatbunny responsibility
Fatbunny maps the current workflow, information authority, decision owners, integration boundary, review states and measurable release criteria before implementing the automation.
Capabilities
- 01
Current-workflow and exception mapping
- 02
Retrieval and source-authority design
- 03
Bounded tools and system integration
- 04
Human review and outcome measurement
Delivery decisions
- 01
Define the business result before selecting a model
- 02
Keep deterministic rules outside probabilistic interpretation
- 03
Return missing evidence and consequential action to an owner
- 04
Measure the completed workflow rather than model activity
Expected outputs
- 01
An agreed workflow and operating boundary
- 02
A working scenario connected to approved information and systems
- 03
Evaluation evidence, ownership controls and a measured next backlog
Honest limits
- !
Automation cannot repair missing source information or unclear decision ownership.
- !
Sensitive data and consequential actions require explicit permissions and review.
- !
A convincing demonstration is not treated as production evidence.
Start with the real work
Complex catalogues and service configurations force buyers and sales teams to repeat discovery before a suitable option or quote can be prepared.
The first release should remove a specific coordination constraint without hiding missing information or transferring accountability to a model.
Connect information, decisions and systems
The workflow may involve Product catalogue, Configuration rules, Pricing system, CRM or quoting. Each connection receives a narrow purpose, known failure behavior and a responsible owner.
Measure the business result
Useful evidence includes relevant recommendation, quote-ready request, reduced sales discovery. Model confidence and conversation volume are not substitutes for those outcomes.
Direct answers
Common questions
What does product recommendation and quote assistant automate?
The assistant maps customer requirements to approved product rules, explains relevant options and prepares a quote request for commercial review.
Does the AI make every decision?
No. Known rules remain deterministic, and uncertain or consequential work returns to the accountable person shown in the workflow.
Can this connect to existing business systems?
Yes, when those systems provide suitable APIs, exports, CLI operations or MCP tools with appropriately scoped access.