How an AI learning platform turns any source into a validated, personalized lesson on AWS
The company builds an adaptive AI learning platform for school students, college students, and people building career skills. As demand grew, it needed a platform that could build lessons from any source, ground answers in real material, and scale with exam-season peaks. Flentas delivered a multi-agent AI platform on AWS, with seven agents that plan, generate, validate, and assess learning content.
- AI agents plan, generate, validate, and assess learning content
- 7
- Languages supported on one platform
- 19
- Platform serving both direct learners and institutions
- 1
Needed an AI platform that could deliver this reliably, safely, and at scale.
Learners face more material than they can organize, and one-size-fits-all content leaves many behind. Giving every learner a good teacher, in their own language, at any hour, does not scale with people alone. The customer needed an AI platform that could deliver this reliably, safely, and at scale.
One-size-fits-all content was leaving learners behind
Learners face more material than they can organize, and giving every learner a good teacher, in their own language, at any hour, does not scale with people alone. The company needed an AI platform that could do this reliably and safely.
Trustworthy, reliable AI content
Plausible but wrong answers harm learners, and AI-generated scenes can fail to render. Explanations had to be grounded in curriculum and learner documents, and learners and teachers needed to approve the plan before generation began.
Student data protection
The platform serves school-age learners, so privacy, encryption, and role-based access were required from day one, with FERPA and COPPA alignment as design goals.
Two audiences and exam-season demand
Direct learners and institutions needed separate tenancy, content management, and live-class operations on shared infrastructure, with scaling for exam and evening peaks.
A multi-agent platform built for trust, control, and scale
Flentas designed a multi-agent AI system on AWS, with Amazon Bedrock providing the reasoning models and Amazon ECS running the agents and the product around them.
Established the AWS foundation
A Control Plane for institutions and a B2C cluster for learners, each capability running as its own ECS service in a private VPC.
Built the seven-agent learning pipeline
Agents that understand documents, retrieve grounding material, plan lessons, generate content, and create practice.
Added grounding, approval, and validation
Lessons are anchored to curriculum and learner documents, approved by the learner before generation, and checked in a browser before delivery.
Secured and automated delivery
Authentication, secrets management, monitoring, and automated releases keep the platform secure and easy to evolve.
More trustworthy. Easier to scale. Faster to evolve.
One platform, two markets
Direct learners and institutions run on shared AWS infrastructure, with separate tenancy for each.
A wider audience
School, college, and career learners are served in 19 languages by a single product.
Trust that protects the brand
Grounded answers and validated lessons lower the risk of wrong or broken content reaching a learner.
Focused AI effort
Plans are approved before generation, and repair attempts are capped, so effort goes to lessons learners actually want.
Faster product evolution
Each capability releases independently through an automated pipeline.
Growth without added operations effort
Services scale with exam-season and evening demand without manual intervention.
Built on the AWS stack
- Amazon Bedrock
- Amazon ECS
- Amazon ECR
- Elastic Load Balancing
- Amazon VPC
- NAT Gateway
- Amazon DocumentDB
- Amazon ElastiCache for Redis
- Amazon Cognito
- AWS Lambda
- Amazon CloudWatch
- AWS Secrets Manager
- AWS CodePipeline
- Cloudflare
What AI platform teams usually ask about building on AWS
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