Building a successful coordination marketplace requires a clean architectural split. MarketForge provides the structured, step-by-step engineering roadmap that takes a target vertical from diagnostic scoping through local simulation and launch.
To ensure scalable and rapid deployments, DeeperPoint divides the building blocks of a vertical marketplace into two clear layers:
DeeperPoint operates on a highly generic, extensible role schema designed to fit any complex transaction corridor:
The open-source project provides pre-packaged server building blocks (software containers) that configure the matching engine and search database automatically.
The founder configures a simple settings file to define the unique traits, qualifications, and questions required for their specific market.
The founder gathers standard contracts, government regulations, and industry guidelines and loads them into the reference library.
The core software analyzes the loaded documents, and the founder reviews the results to ensure the system understands precise local industry terms.
The founder finds and maps the alternative paths or "escape hatches" in regulations that allow smaller businesses to qualify.
The founder locks these workaround options directly into the market's settings file so they can be triggered automatically.
The founder designs a diverse group of mock participants (mock buyers, sellers, and inspectors) to test how they interact under different conditions.
The core engine runs simulated trades and matches between the mock participants to prove the marketplace arithmetic works before launching to real users.
The founder builds a clean, lightweight web page or mobile screen tailored to their users, connecting it directly to the matching engine.
The core software translates complex matching scores into simple, step-by-step plain English stories that explain to both sides why they are a great fit.
The founder creates simple guidebooks, manuals, and value explanations to help real-world businesses sign up easily.
The founder sets up alert channels so when a match is blocked by a missing rule, they can quickly update the library with a new workaround.
Before launching to real businesses, the founder sets up a **Digital Twin** (a local computer simulation) to test their marketplace. They create three groups of simulated users:
Before launch, the founder uploads industry rulebooks to teach the software the baseline terminology and workarounds.
Result: Calibrates matching models to regional industrial realities.If a business gets blocked during matching because of a missing qualification, the software automatically messages them to ask for their workaround and updates their profile instantly.
Result: Unlocks blocked matches in minutes without manual support.If a transaction is blocked by a brand new regulatory barrier, the system alerts the founder, who quickly uploads the appropriate workaround to make the market smarter.
Result: System gets progressively smarter with every match.Explore the core Cosolvent suite and download the MIT licensed transaction database blocks.