Integration Studio
An early-stage venture exploring how businesses can make useful information accessible through AI-compatible integrations.
The problem
Businesses may have useful data or capabilities that people cannot easily access inside AI conversations. Demonstrating a connection is different from proving a secure, commercially reliable integration.
Who it's for
Businesses exploring whether their catalogs, information, or services could become useful inside AI-enabled conversations.
The approach
Explore the opportunity with an industry-neutral demonstration and synthetic land and automotive examples, then validate search accuracy, client compatibility, and data rights before attempting a real business integration.
What exists today
- A public website with synthetic land and automotive demonstrations and clearly labeled hypothetical value modeling.
- A connected ChatGPT demonstration plugin invoked the synthetic land-search tool and returned a matching fictional North Carolina parcel for explicit acreage, price, and state filters.
- A second ChatGPT plugin invocation explicitly rejected unsupported Asheville proximity and barn requirements rather than presenting the fictional result as an exact match.
- Read-only discovery and prepared-only inquiries: the prototype does not send actual leads or access licensed business inventory.
My contribution
I identified the entrepreneurial opportunity, set product direction and demonstration requirements, and guide iterative AI-assisted development and review. The prototype does not establish independent technical authorship of all code, customer adoption, or validated commercial outcomes.
Current status
Public synthetic-data prototype verified in October 2026. Two live ChatGPT plugin calls demonstrated a supported structured search and transparent rejection of unsupported city/proximity/barn criteria. This confirms tool invocation in ChatGPT, not integration with real business inventory or validation in Claude. Cross-channel search semantics, customer use, and commercial reliability still require testing.
Next steps
- Verify consistent treatment of supported and unsupported filters across the website, connected plugin, and hosted MCP endpoint.
- Independently test other AI clients and production authorization before making broader client-compatibility claims.
- Obtain business permission, data rights and security validation before any real partner integration.