Giving Teachers Back Ten Hours a Week Without Lowering the Bar on Feedback
Teachers spend close to ten hours a week grading on average, with the large majority taking that work home. Heavier feedback loads correlate directly with burnout, and rushed grading under time pressure usually means shorter, less useful feedback for the students who need it most.
Why this keeps costing you
Manual grading does not scale with class size, and the tradeoff is almost always the same: either spend hours giving genuinely detailed feedback, or grade fast and give students little more than a number. Neither option is good for the teacher or the student, and it is one of the most cited reasons educators consider leaving the profession.
How we build it
Rubrics are converted into structured prompt chains rather than a single generic grading instruction — each criterion on the institution's actual rubric becomes its own evaluation pass, so a five criterion essay rubric produces five distinct, criterion specific pieces of feedback rather than one holistic paragraph. Every AI generated score and comment is written to a review queue before it reaches a student, and a teacher can accept, edit, or override any individual score in seconds, so the system functions as a first pass draft grader, not a black box final authority.
What this looks like once it is running
- 1Automated evaluation across reading, writing, speaking, and listening
- 2Rubric based scoring tuned specifically to the institution's own standards
- 3Consistent grading quality regardless of time of day or grading fatigue
- 4Detailed, specific feedback generated automatically for every submission
- 5Full teacher review and override built into the workflow, never a black box
Zaltech's own assessment platform has driven a 95 percent reduction in grading time for institutional clients, with more consistent standards across large classes and hours of time genuinely returned to teachers for actual instruction.
For more details, click the relevant case study link below.
View AI Assessment Platform case studyAI Assessment Platform
This is Zaltech's live AI Assessment Platform, which fully automated grading across reading, writing, speaking, and listening for a language testing provider, eliminating manual evaluation entirely. It uses advanced prompt engineering for consistent scoring, runs a dual portal design for administrators and students, and holds a 95 percent reduction in grading time alongside 98 percent assessment accuracy and full report generation in under two minutes — built on WebSockets, speech to text, and text to speech, with LMS integration for grade sync.
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Want this one built for your business?
We will walk you through the architecture, what it takes to integrate with your systems, and a realistic timeline — before anyone signs anything.