Rescore Advisor AI

Help every student get the score they deserve by quickly identifying cases for appeals.

How It Works

1. Submit Your File (ECRs & Scores)

Securely upload the file with your STAAR ECR scores and student submissions.

      2. We Bulk Analyze and Report - FAST

      Our specialized, calibrated AI scores every ECR against the rubrics & runs cross-analysis.

      3. You Make Timely, Informed Decisions

      With the prioritized report you receive, you can make quick, well-informed rescore decisions.

      2,000 Successful Rescores for One District

      See how one of the largest districts in Texas was able to quickly identify ECR scores for rescoring, got over 2,000 students’ scores upgraded, and saw 700 students elevated to higher performance levels. 

      Successful Rescores Make a Difference

      Some students are just points away from their goal. A rescore can make all the difference for them and for their school.

      Successful rescores can increase students’ confidence and motivation, allow on-time graduation, eliminate remediation and retesting, and even improve campus accountability data.

      Get a plan in place now!

      Data Security

      Compliance with Regulations

      Our practices comply with applicable student privacy laws, including FERPA (Family Educational Rights and Privacy Act), and COPPA (Children’s Online Privacy Act) to ensure that student data is always safe.

      Data Security Bonafides

      ALL In Learning is the recipient of the most secure category ratings from  Panoray Cyber Posture Rating, BitSight Security Rating, and Intruder.IO Cyber Hygiene Score, and is a signatory of the Student Privacy Pledge.

      No Personal Info Sent Through AI 

      No Personally Identifiable Information is sent through AI processing. Processes is isolated, inly including an encrypted ID that is rematched afterward, then all submission data is discarded from the AI thread.

      No AI Training with Your Data

      Our AI will not be trained using any of your students’ submissions. Our specialized language model is tuned to STAAR exemplars for demonstrable score adjacency utilizing each submission’s  appropriate state rubric. 

      See our security and privacy page here for more information.