OCR & Handwriting Recognition for Education & EdTech

A flattened table is a destroyed table. We preserve layout structure, because a financial statement without its columns is not data.

In education & edtech, student data protection and academic integrity constrain what may be automated at all. That single fact reshapes how ocr & handwriting recognition has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is attendance and records automation, usually integrated against assessment platforms. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

Multi-model by default, so a provider outage is a routing decision rather than an incident. You own the code, the models where they are open-weight, and the documentation to run it without us.