Operating platform

Deal Pros

Business brokerage operating platform

My role: Founder and owner — direction across the business model, financial structure, legal and compliance requirements, operations and vendors, go-to-market, workflow design, and AI-assisted product development
Current status: Pre-launch. No performance or adoption figures are published.
Shown as case studies of my work; not offered as products or services.

The origin of the platform

Deal Pros grew from a need I knew firsthand. While developing the operating system at my previous brokerage, and later helping set up another brokerage after going out on my own, I spent years researching and testing dozens of CRM, data-room, deal-room, communication, and related tools. The available options were often costly, disconnected, or built around residential real-estate logic rather than the work of business brokerage and commercial real estate.

I planned an outsourced enterprise platform build in fall 2025. As AI-assisted development improved, I began testing whether I could direct the development myself. Those tests became the flagship platform: an integrated, multi-tenant operating system. The reason it exists is simple. The tools I needed didn’t solve the problem, so necessity drove me to build a better fit.

The decisions and workstreams I directed

I set the direction across these business, operating, market, and product workstreams. AI-assisted development is one part of the work — not the whole of it.

Business and ownership structure

The entity, the ownership model, and the decision about what kind of business this should be: who it serves, what it charges for, and where it stops.

Financial model and unit economics

Subscription and service pricing structured against the cost of delivering it, so the model works at the size it would realistically reach rather than only on a spreadsheet.

Legal and compliance

The confidentiality, document-handling, and client-data obligations that brokerage and M&A advisory work carries — designed into the platform as rules, not written into a policy nobody reads.

Operations, vendors and support

Tool and vendor selection, the support model, and the internal process the firm would actually run on day to day.

Market and go-to-market

Who this is for, what they currently use, why they would move, and how the offer is positioned against how brokerage firms already work.

Product, workflow and AI-assisted development

Workflow architecture, role and permission model, product direction, and AI-assisted development used to turn the concept into working software.

Why the system exists

What was broken

Business brokerage and M&A advisory work runs on scattered tools. Deal information, client communication, documents, tasks, and advisor coordination sit in separate systems, so the operating picture of the firm is never in one place.

What became possible

The work of an advisory firm is highly repeatable even though every deal feels unique. Once the underlying workflow is described accurately, most of the coordination burden can be designed out rather than managed manually.

How I designed the response

Start from how the firm actually operates rather than from software features. Map roles, deal stages, documents, and hand-offs, then design a single operating platform around that model, with AI assistance applied where it removes real work instead of where it demonstrates novelty.

What was designed

Deal management across the full engagement lifecycle
Role-based workflows for advisors, staff, and clients
CRM and pipeline structure built around deal stages
Document-management concepts tied to the deal record
Client and deal coordination in one operating view
Subscription and service business-model structure

Directing the connected decisions behind a business concept — model, economics, legal requirements, operations, market, workflow, and AI-assisted product development — rather than treating each as a separate function.

Business model design
Financial structure and pricing
Confidentiality and compliance design
Advisor operations
Vendor and tool selection
Go-to-market positioning
Business workflow architecture
Deal management
Role-based access
Document management
Operating-system design
Subscription business models

How the System Works

One operating environment for a brokerage firm: the people, the deal work, the AI that helps move it, and the boundaries that keep each firm's and client's information separate.

Layer 1
Advisor workspace
Where the firm's daily deal work happens.
- Advisors, staff and clients by role (People)
- CRM and pipeline built around deal stages (Workflow)
- Deal management across the engagement (Workflow)
- Client and deal coordination in one view (Output)
Layer 2
Knowledge and communication
Firm knowledge lives inside the platform, not in side tools.
- Intranet for process, templates and firm information (Communication)
- Design Studio for client-facing materials (Output)
Layer 3
AI layer
AI is scoped to the work in front of the advisor.
- AI Deal Pilot, scoped to a specific deal (AI)
- AI support grounded in platform knowledge (AI)
- Escalation to a person and ticket handoff (Human decision)
Layer 4
Deal data and documents
Documents stay attached to the deal they belong to.
- Documents tied to the deal record (Data)
- Confidentiality and document-handling rules built in (Security)
Layer 5
Security and separation
Boundaries are a property of the platform, not of user discipline.
- Role-based access for advisors, staff and clients (Security)
- Firm, team and client separation (Security)
- Administrative controls over AI support (Human decision)

People
Workflow
Output
Communication
AI
Human decision
Data
Security

Features that are part of the product, not separate products

AI Deal Pilot

An assistant scoped to deal context that helps advisors move a specific engagement forward rather than answering generic questions.

Intranet

An internal knowledge and operations surface so process, templates, and firm information live inside the platform teams already work in.

Design Studio

Controlled creation of client-facing materials inside the platform, so presentation quality doesn’t depend on ad-hoc external tools.

Multi-tenant separation

Firm, team, and client boundaries enforced structurally so data separation is a property of the platform, not of user discipline.

AI Support

A reusable AI support layer built into the platform: platform-specific knowledge grounding, AI chat support, escalation to a human, support-ticket handoff, and administrative controls.

AI Support and multi-tenant separation are architectural patterns reused across the platforms rather than rebuilt each time.

What I took from it

The hard part isn’t the software. It’s describing how a business genuinely operates precisely enough that a system can support it, and deciding what shouldn’t be built.

This one comes directly from the seat: six years as COO of a regional M&A firm and current work as a business intermediary under real estate salesperson licenses in Wisconsin, Minnesota, and Florida. I designed the operating system around work I know firsthand.

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