For decision makers evaluating Chaparral Software's track record — 40 years of production systems across entertainment, healthcare, defense, education, and technology.
The Trail So Far
Four decades of building production systems. Each era built on the one before it. Here's the arc.
The Arc
The thread through 40 years is the same: complex data, real constraints, systems that have to work in production.
1986–2000: Databases
Custom database solutions. FileMaker Pro when it was the serious tool for serious data problems. MySQL and Postgres when relational databases were the backbone of everything.
2000–2015: APIs & Web Services
RESTful architectures, Python, Node.js. The shift from desktop applications to connected systems. Integration work across healthcare, entertainment, and education.
2015–2023: Cloud
AWS RDS, DynamoDB, API Gateway. Enterprise-scale systems for regulated and complex environments.
2023–Present: Production AI
Knowledge graphs, orchestration pipelines, verification frameworks, and the tooling to run them. Systems that run in production, that are tested, that handle edge cases. Each era built on the one before it. Forty years of compounding technical judgment.
FileMaker + AI
Many of Chaparral's longest client relationships started with custom FileMaker solutions — systems that have been running production workloads for 10, 15, sometimes 20 years. I've been a frequent speaker at FileMaker developer conferences, and in 2023 I presented to Claris on the AI implications for the platform.
Deep FileMaker API integration experience informs my approach to leveraging FileMaker as a persistence layer backing inference solutions. In 2023 I published a case study on using a custom FileMaker solution to mediate GPT-4 conversations and structure prompt pipelines for manufacturing schema design — the same pattern that now powers more complex AI orchestration work.
If you're running FileMaker in production and wondering how AI connects to what you already have — that conversation starts from the data side, not the hype side.
In the Field
Four articles published between January and April 2023, early in the AI wave — before the hype cycle peaked.
"Mastering Token Limits and Memory in ChatGPT and other Large Language Models" — published March 2023, 52,000 lifetime views, 28,000 reads. The #1 article on token limits through most of 2023 and 2024. A working engineer's explanation of a real problem, written from production experience.
- "Mastering Token Costs in ChatGPT and other Large Language Models" — the economics of token usage. Companion to the above. (April 2023, Medium)
- "The AI Revolution: Leveraging Skills and Expertise for Real Value" — AI amplifies existing expertise, doesn't replace it. This was contrarian in January 2023. It's consensus now. (Medium/Bootcamp)
- "GPT4 in Action: Streamlining Schema Development" — case study using a custom FileMaker solution to mediate AI conversations and structure prompt pipelines for manufacturing schema design. (March 2023, LinkedIn)
Current Work
The same diagnostic rigor that built these systems now powers Ground Truth Assessment — an independent technical diagnostic for organizations navigating AI decisions.