Encompass Math
The Client
Encompass Math is an educational platform designed to support rich mathematical thinking, helping educators guide students through deeper problem-solving, reasoning, and conceptual understanding.
Built on a foundation of high-quality mathematics mentorship and instructional feedback, Encompass Math sought to make its educational expertise more accessible and scalable for teachers. To support this next phase of innovation, Encompass Math engaged RevStar to develop an AI-powered feedback system that could help educators generate meaningful, concept-driven responses to student work.
Summary
Educational Learning Platform
EdTech
Amazon Bedrock, Bedrock Agents, Amazon S3, Amazon OpenSearch Serverless, RAG Architecture, Vector Embeddings
Solution Architecture, Delivery Management, AI/Data Engineering, Cloud Engineering, Quality Assurance
RevStar helped Encompass Math transform decades of mathematics education expertise into an AI-powered feedback system, leveraging Agentic AI, retrieval-augmented generation (RAG), and AWS cloud infrastructure to support scalable, high-quality student feedback workflows.
Established a scalable AI foundation capable of transforming historical educational expertise into actionable teaching support while helping educators deliver more personalized, concept-driven student feedback.
The Challenge
As Encompass Math continued supporting rich mathematics learning experiences, the organization saw an opportunity to make high-quality instructional feedback more scalable for educators.
Years of student-mentor interactions contained valuable pedagogical knowledge, but that expertise needed to be centralized, structured, and made easier to access in order to support future AI-powered teaching workflows. At the same time, educators needed a more efficient way to generate personalized, concept-driven feedback without compromising the thoughtful instructional quality that defines the Encompass Math experience.
To support this next stage of growth, Encompass Math needed a scalable AI foundation capable of transforming historical educational content into practical, teacher-facing support.
The Problem
Encompass Math needed a scalable way to transform historical student-mentor interactions into AI-powered feedback support while preserving instructional quality and consistency.
The Solution
RevStar developed an AWS-native AI framework designed to help Encompass Math make its historical educational expertise searchable, retrievable, and actionable for teachers.
The solution centered on a retrieval-augmented generation architecture that organized student-mentor interaction data into a secure, vector-indexed knowledge base. This allowed the AI system to retrieve relevant instructional examples and generate feedback drafts based on teacher-selected student work.
By combining Agentic AI, semantic search, and educator validation workflows, Encompass Math established a scalable foundation for AI-assisted feedback generation that supports teachers while preserving the organization’s unique instructional approach.
The Team
