The past couple of weeks have been packed with meaningful progress across three major initiatives — all pushing forward in their own ways, but aligned toward the same goal: more reliable systems, smoother operations, and better delivery.
KeyNotes: Integration and Behavioral Health Improvements
Work continued on the KeyNotes platform, particularly around the ICS and Believe in Recovery initiatives.
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We completed new data export logic and improved our import–transform–merge flow to support demographic reporting and data warehouse requirements.
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Behavioral Health (BHO) updates were stabilized for Believe in Recovery, resolving issues in how forms and treatment data was being rendered and stored.
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ISP Review logic was refined to better handle incomplete treatment plans and streamline the review process.
These updates help strengthen compliance, data consistency, and reporting capabilities.
Wide Hollow Development: Creekside Business Park Website
We’re wrapping up the new website for Wide Hollow Development, the team behind Creekside Business Park. The project showcases 40+ acres of professional and medical space across 15 high-quality buildings totaling more than 167,000 square feet. The new site highlights the company’s story, the team behind it, and the properties available — and it’s set to launch soon.
HTML Platform Expansion: Growing Our Dev Team
On the product side, we’ve started expanding our development team to support an upcoming business management system. This involves onboarding a front-end group to help accelerate the interface layer. The collaboration will let keep design and development moving in parallel.
Three separate tracks, one unified direction — improving systems, refining delivery, and setting up for a strong close to the year.
R&D: Bridging LLMs and Backend Logic
On the R&D front, we’ve been exploring how to embed a Copilot-style language model interface into our new Business Management System. The goal is to allow users to interact naturally with the platform — describing what they want in plain language.
This architecture combines three layers: the LLM layer, which interprets user intent; a semantic model layer, which maps that intent to application concepts; and the execution layer, which issues authenticated API calls against live services. The middle layer is where most of our research is centered — developing the schema and translation model that bridge free-form requests (“create a new payable for Precision Paving”) into precise backend commands. This is the foundation of a future AI-assisted workflow engine built directly into the platform.