AI for Advisors · Proposal Generation
AI proposal generation for financial advisors
Every recommendation deserves a clear proposal: what you propose, what it costs, what the alternatives were, and why. entropyFA drafts that document from the household's actual data — numbers from the deterministic engine, narrative in plain language.
Built on the same engine as planning, tax, and portfolio analysis.
What It Handles
The work this replaces
Recommendation proposals
Analysis becomes a decision-ready proposal: the recommendation, the trade-offs considered, and the rationale — written for the client, reviewed by you.
Client-ready presentation
Plans and memos come out presentation-ready, so the gap between finishing the analysis and delivering it to the client disappears.
Every number backed
Figures come from the deterministic quantitative engine — liquidation comparisons, projections, simulations — with an audit trail behind each one.
How It Works
From household data to advisor-approved action
1. Analyze
The engines do the work
The generative engine gathers household context; the quantitative engine runs the comparisons — every strategy priced, plan impact simulated.
2. Draft
The proposal writes itself
Results become a structured proposal: recommendation, alternatives, trade-offs, and plain-language rationale a client can actually follow.
3. Review
You approve, then deliver
The advisor reviews, edits, and approves before anything reaches the client. Proposals stay documented with their assumptions and reasoning.
Capabilities
What the agent brings
- Recommendation drafts with rationale
- Client-ready plan presentations
- Scenario and trade-off comparisons
- Plain-language explanation of the analysis
- Deterministic numbers behind every figure
- Advisor review and approval workflow
Why You Can Trust It
Grounded in the household, not a template
Template proposals read like templates. entropyFA drafts from the household's actual accounts, lots, entities, and plan, so the proposal answers this client's situation — and the reasoning shown is the reasoning used.
Review the trust architectureFAQ
Common questions from advisory firms
What goes into a generated proposal?
The recommendation, the alternatives evaluated, the quantitative comparison — tax consequences, projections, simulation results — and a plain-language rationale. The dual-engine design means the narrative explains numbers that deterministic math produced.
Can I edit proposals before clients see them?
Yes — nothing goes to a client without you. The agent drafts, you review, adjust, and approve. Your judgment and voice stay in the document; the assembly work does not stay on your desk.
Where do the numbers come from?
From the quantitative precision engine working on the household's actual data: lot-level tax analysis, cash-flow projections, and Monte Carlo simulation. The generative AI never invents a figure.
Does this work for new households too?
Proposals draw on whatever the household record contains, so once documents and accounts from onboarding are mapped, proposal generation works from that same structured picture.
Are proposals documented for compliance?
Yes. Each proposal keeps its assumptions, analysis, and approval history attached, giving you audit-ready documentation of what was recommended and why.
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See it on your own workflow
Tell us about your firm and client mix. We will set up a free trial and show you where entropyFA fits first.