AI-Powered Advisory Platform Development

AI platform that helps wealthy families formalize governance, align priorities, and reduce conflict risk through automated multi-agent analysis.

Project category

AI / ML

Industry

Family Offices, Fintech

Location

Global

Duration

2.5 months (MVP)

Managing significant family wealth is never just about money.

— Who makes the decisions?
— How are conflicts between generations resolved?
— What happens when there are no clear rules?

These are real issues that destroy families and cost millions – yet most of them go unaddressed until it’s too late.

Until now, the only option was expensive consulting – months of in-person sessions, subjective conclusions, nothing scalable.

The platform also processes existing family documents – agreements, statements, and records – transforming unstructured data into structured inputs for analysis.

This platform replaces that entire process: family members fill out structured questionnaires online, AI analyses the responses across 7 dimensions, and generates a ready-to-use governance report with recommendations.

Cyber Bee owned the full cycle: from product strategy and architecture to AI agent development, frontend, backend, and deployment on private cloud infrastructure.

How it works

From the user's side, it's straightforward: log in, fill in the questionnaire at your own pace, everything saves automatically. When all family members are done, the owner triggers the analysis. From there, everything runs on its own.

7 AI agents run in sequence. Each analyses its dimension and passes the result forward. The final agent assembles the full picture and produces the report — structured, anonymised where needed, and ready to use.

#	Agent	What it analyses
1	Family Roles Analysis	Maps responsibilities, role conflicts, and structural gaps across family members.
2	Personal Goals & Aspirations	Structures individual expectations and strategic visions of each family member.
3	Governance Priorities & Conflict Mapping	Identifies diverging priorities and risk zones that aren't yet visible on the surface.
4	Strategic Governance Framework	Defines the decision-making structure and establishes the rules of the game.
5	Communication & Transparency	Surfaces communication breakdowns and recommends concrete fixes.
6	Monitoring & Risk Management	Evaluates control mechanisms and early warning indicators.
7	Final Governance Synthesis	Consolidates all analyses into a single report with actionable recommendations.

The whole process takes minutes, not months — and delivers the same quality for every family, regardless of who runs it.

Objectives

Family capital management is not just about finances.

Conflicts arise between generations due to unclear roles, diverging priorities, and a lack of structured decision-making mechanisms.

Traditional consulting addressed these issues but had significant limitations: it was slow, expensive, impossible to scale, and heavily dependent on the individual consultant's judgment.

The client sought to digitize and improve this process using AI — while maintaining confidentiality, institutional-grade quality of results, and the possibility of iterative refinement.

To achieve this, the following objectives were set:

Replace expensive advisory Make institutional-grade governance accessible without six-figure consulting fees.
Remove subjectivity from analysis Same prompts for every family — no human bias, no variance in interpretation.
Institutional-grade confidentiality Full data isolation in a private cloud. No third party ever touches the family's information.
Scalable SaaS model Stripe subscription gives any family or family office access without custom integrations.

Approach used

The product has three parts that together cover the full cycle - from first contact to a finished report in the family's hands.

Public Website

The entry point for new clients: methodology overview, thought leadership content, and lead capture. From here, families subscribe via Stripe and get access to the secured platform.

Governance Platform

The family owner manages the process: adds participants, sets deadlines, tracks who has completed their questionnaire, and triggers the AI analysis when everyone is ready. Each family member gets a personal account with secure login, a save-and-resume questionnaire, and completion tracking.

The admin panel lets the client edit questionnaire content and agent prompts without writing code. Governance logic can be improved at any time - no developers required.

AI Engine

The core of the platform - 7 specialised agents. Each receives questionnaire responses, applies its own prompts, and analyses a specific governance dimension. The final agent consolidates everything into a single PDF report.

The report includes: executive summary, participation analysis, four governance sections, and a concrete list of next steps.

Approach Used

7 specialized AI agents
Each agent owns one governance dimension. The final one consolidates everything and generates the report — no human in the loop.
Private cloud + local LLM
No external APIs. All data stays within the client's infrastructure — critical for UHNW confidentiality.
Editable AI logic without code
Admins update agent prompts via backoffice — no developers needed, no downtime.
Iterative ML fine-tuning
First iteration ships a working engine. Subsequent rounds improve output quality on real data.

Technologies used

Private Cloud Infrastructure
The entire platform lives within the client's environment. No data leaves.
Local LLM Deployment
Language model runs on-premise — no dependency on OpenAI or any third-party provider.
Multi-Agent Orchestration
Custom orchestration layer coordinates 7 agents, minimises overlap, and ensures staged processing.
React / Next.js
Frontend powering the owner dashboard, family member interface, and admin panel.
Stripe
Subscription and paywall between the public site and the secured platform.
Role-Based Access Control
Separate access levels for Family Owner, Members, and Admin.
PDF Report Generation
Automated generation of structured reports from all agent outputs.
Streamlit Demo Interface
Environment for reviewing and evaluating AI outputs before production.
ML Fine-Tuning Framework
Pipeline for iterative agent improvement without full redeployment.

MVP Timeline

Stage	Duration	Dependencies
Product Architecture	2 weeks	Start
Platform Development	7 weeks	Starts after Architecture
AI Agents Orchestration	5 weeks	Parallel with Platform Dev
Testing & Refinement	2 weeks	Starts at week 9
Total Time to MVP	11 weeks	~2,5 months

Tech stack

Results

What used to cost tens of thousands of dollars and take months of consulting work is now a structured, automated process — available as a SaaS subscription with the same output quality and full data privacy.

Before	After	What it means
Months of consulting work	Structured report in days	From questionnaire to PDF — fully automated, no consultant involved.
Subjective analysis	Reproducible AI output	Same prompts for every family — consistent quality, no human variance.
Conflicts no one sees coming	Risks surfaced before they escalate	Agents detect priority gaps and communication breakdowns early.
Static documents once a year	Frameworks that can be updated anytime	Admin updates agent logic via backoffice — no code, no downtime.
Expensive one-off consulting	Accessible SaaS product	Stripe subscription opens access to any family or family office.

The platform turns family governance from a one-off expensive exercise into a repeatable process — one that can be run, measured, and continuously improved.

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