DcisionAI

April 23, 2026 
DcisionAI × MATAURO
A conversation about the decision layer built for wealth managers serving complex, high-net-worth clients — and the compliance obligations that come with them.
DcisionAI
The Intelligent Enterprise Decision Layer
Decision infrastructure for the regulated enterprise — where every high-stakes choice becomes provable, auditable, and permanently traceable.
The Analytics Landscape
Descriptive Analytics
Where reporting tools live
What happened to the portfolio?
Performance reports, drift alerts, attribution analysis
Tools: Black Diamond, Orion, Tamarac
Output: A dashboard
Predictive Analytics
Where AI/ML tools Live
What is likely to happen?
Probabilistic forecasts, scenario modeling, risk projections
Tools: eMoney, MoneyGuidePro, most LLM-based tools
Output: A recommendation to consider
Certified Prescriptive Analytics
Where DcisionAI operates
What is the optimal action — proven across all constraints simultaneously?
Multi-constraint optimization: tax, risk, ESG, concentration, fiduciary, Regulation Best Interest
Output: A certified optimal decision with mathematical proof
Every binding constraint named. Every tradeoff costed. Audit trail built in.
The third tier isn't just better analytics — it's a different category. DcisionAI operates here.
The Problem
High-stakes portfolio decisions are still trapped between complexity, accountability, and manual work. The result is fragile judgment where teams need durable, defensible decisions.
Institutional Amnesia
42% of industry AUM sits with advisors whose decision logic exists only in spreadsheets and email threads (McKinsey, Feb 2025)
Rebalancing rules, client-specific tax situations, and client-specific overrides live in advisor heads and ad-hoc files. 
When the advisor leaves, the decision logic leaves.
The Black Box Governance Gap
55% of advisors cite compliance and regulatory hurdles as the top barrier to scaling AI (Advisor360°, Jan 2026)
The EU AI Act, fully enforceable August 2026, classifies investment recommendation AI as high-risk. Fines up to €35M or 7% of global turnover.
Unverifiable AI is not automation. It's liability.
Manual Optimization at Scale
2–3 hours per complex case, per review cycle — for every client with overlapping constraints
Solving drift, tax, concentration, and ESG one constraint at a time — in any tool — means the best answer across all of them is never found.
Complexity compounds across the book.
The Modern Wealth Management Stack — and Where DcisionAI Fits
Most wealth management firms have strong tools across custody, reporting, and planning. The layer that's typically missing is the decision layer.
DcisionAI activates at the two highest-stakes moments in every client cycle.
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1
Client Onboarding
KYC, risk profiling, goals intake
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2
Financial Planning
Scenario modeling, cash flow, goals-based planning
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3
Portfolio Construction & Decision
Optimal allocation certified across all constraints
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4
Trade Execution
Orders routed to custodian
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5
Performance Reporting
Portfolio analytics, client reporting
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6
Review & Re-optimization
Rebalancing triggers, drift detection, re-run on demand
Your reporting tells you what happened. Your planning tool tells you what's planned. DcisionAI tells you what to do — and proves it.
Our Solution
DcisionAI: Decision Infrastructure
An advisor describes the problem in plain English — drifted portfolio, tax constraint, concentration limit, fiduciary and Regulation Best Interest requirement. DcisionAI routes it through a six-agent pipeline — Discovery, Research, Planning, Model, Solve, Explain — with mathematical audit gates at every stage. The output is not a suggestion. It is a certified optimal decision.
Intent Layer
DcisionAI agents interpret the advisor's intent, extract every constraint — tax lots, risk profile, ESG mandates, concentration limits — and translate them into a precise mathematical formulation. Explicit conflict detection flags any inconsistency between user intent and translated spec before it reaches the solver.
Deterministic Layer
DcisionAI solver agents find the mathematically optimal answer across all constraints simultaneously. Every output carries a proof of optimality — proof that no better solution exists given the constraints. Fiduciary and Regulation Best Interest audit trail built in.
Explanation Layer
Results return in plain English: which constraints are binding, what each one costs in dollars to relax, and what the tradeoffs are. Ready to present to the client or submit to compliance — in minutes.
Not a recommendation. Not a prediction. A certified optimal decision — with every binding constraint named in business language and every shadow price shown in dollar terms.
Each run compounds: the context graph grows richer with rules, precedents, and tradeoffs, making every future decision faster, more consistent with the firm's prior decisions, and fully auditable.
How DcisionAI Fits Your Day
From the morning call to the afternoon trade — DcisionAI fits directly into how your advisors already work.
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Key Decision Moment
Morning — Discovery
Your client calls. The portfolio has drifted — tech is 34% vs. 25% target. $200K unrealized gain. The client wants minimal tax impact. Fiduciary duty and Regulation Best Interest both require documented rationale.
Pull Black Diamond, export to Excel, manually model scenarios. 2–3 hours per complex case.
With DcisionAI: Describe the problem in plain English. Optimal trade set returned in minutes — every constraint named, every tradeoff costed.
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Key Decision Moment
Midday — Recommendation
Your advisor presents to the client and documents the fiduciary and Regulation Best Interest rationale.
Based on our judgment and the model, this allocation is appropriate. Defensible in most cases. Harder when the client challenges the specific trade.
Certified optimal allocation with shadow prices quantifying every tradeoff in dollars. Audit trail generated automatically — fiduciary and Regulation Best Interest documentation built in.
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Afternoon — Execution & Memory
The trade list goes to Fidelity. Straightforward once the decision is made.
Decision knowledge lives in the advisor's head. Next similar client starts mostly from scratch.
Trade list goes to Fidelity. Context graph captures the full record. Every run makes the platform — and the firm — smarter.
Four Ways DcisionAI Works for MATAURO
Portfolio Rebalancing
Given risk profile, tax situation, and concentration limits — DcisionAI finds the certified optimal rebalance in minutes. Every binding constraint documented. Fiduciary and Regulation Best Interest audit trail. No Excel.
Tax-Efficient Allocation
DcisionAI optimizes across tax lots, harvests losses, and handles multi-constraint tradeoffs that today require significant analyst time. Every decision documented.
Retirement Income Optimization
Optimizes withdrawal sequencing across Roth, traditional, and taxable accounts — subject to RMD rules, Social Security timing, and income constraints simultaneously.
New Client Portfolio Construction
For HNW clients with ESG preferences, concentration limits, and illiquid alternatives — plan to certified first portfolio recommendation in one step.
The Compounding Advantage — Why DcisionAI Gets Better Every Run
Every Decision Is Encoded
Each run captures the full record — constraints applied, tradeoffs made, shadow prices, Regulation Best Interest rationale. Nothing lives in an advisor's head or a spreadsheet. Every client decision is permanently encoded.
The Firm Gets Smarter
The context graph accumulates rules, precedents, and client-specific patterns across every advisor, every client, every review cycle. The 50th rebalance is faster and more consistent with the firm's prior decisions than the first — because the platform has seen it before.
Institutional Memory That Stays
When a senior advisor is on vacation, moves on, or a new client arrives with similar complexity — the platform already knows. The knowledge belongs to MATAURO, not the individual. That is a durable competitive advantage.
Every decision DcisionAI makes for MATAURO makes the next one better. The platform compounds with the firm.
How DcisionAI Compares to eMoney Decision Center
eMoney models what could happen under different planning assumptions. DcisionAI computes what to do given hard constraints. These are different layers of the workflow — most firms will use both.
eMoney Decision Center is a strong planning tool. DcisionAI is a different layer — built for the moment of decision, not the moment of planning.
eMoney models what could happen across planning scenarios — a powerful planning layer. DcisionAI computes the optimal action given hard constraints simultaneously — a different layer of the workflow. Most firms will use both.
Our Ask
Built for firms that are building.
MATAURO serves complex clients with sophisticated planning needs. DcisionAI is built for exactly that kind of environment: a decision layer that grows smarter with every client, every constraint, every run.
What a Design Partnership Looks Like
Early Access
Direct access to the platform before general availability. Your edge cases shape the roadmap.
Roadmap Influence
Your most complex client scenarios become the problems we solve first.
Relationship Pricing
Pricing that reflects the partnership, not a standard license.
We're being deliberate about who we build with first. We'd like MATAURO to be one of them.
What We're Asking For
Letter of Intent
A non-binding LoI for a 90-day design partner engagement, scoped to one use case (rebalancing or tax-loss harvesting), with bi-weekly check-ins and a written readout at end of period.
Use Case Identification
Two or three real client scenarios to pressure-test against. The harder the problem, the better.
Regular Feedback Cadence
Monthly check-ins to review outputs, surface edge cases, and shape the roadmap together.
Internal Champion
One advisor or ops lead who engages directly with the platform and owns the feedback loop.
No long procurement cycle. No IT lift. We start with one use case and prove value before expanding.