Eagle 8.0
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Eagle 8.0 is an indigenously developed humanoid teaching robot engineered by the Indus Humanoid Lab (part of Indus International Schools in India). Built as a core pillar of the Collaborative Learning Model (CLM)—where human teachers and AI humanoids co-teach—Eagle 8.0 has conducted over 4,000 lessons across international and government schools, directly teaching thousands of students. The platform features full generative AI dialogue, expressive human-like facial emulations, emotion recognition, real-time student engagement analysis, and multilingual content delivery across 30+ languages. It is engineered to function reliably in both high-bandwidth smart campuses and resource-constrained remote classrooms.
Quick Overview & Key Facts
Eagle 8.0 is a humanoid robot made by Indus Humanoid Lab in India, launched in 2024 and built for co-teaching STEM and humanities subjects alongside human educators, personalized student one-on-one tutoring, and foreign language instruction. Its estimated price is $18,000 - $24,000 (Institutional School Package including AI Mentor Platform).
- Dimensions
- 162 cm × 52 cm × 45 cm
- Weight
- 46 kg (101 lbs)
- Top speed
- 0.6 m/s (indoor classroom safe transit)
- Handles
- Classroom flashcards, laser pointers, interactive educational tablets, test papers
- Battery runtime
- 6.0–8.0 hours continuous school day operation
- Charging time
- 2.0 hours via standard 110V/230V AC classroom wall outlet
What Can Eagle 8.0 Do?
Core operational tasks and activities demonstrated or performed by Eagle 8.0.
Real-World Applications of Eagle 8.0
Industries, working environments, and deployment suitability for Eagle 8.0.
Eagle 8.0 Capabilities
Inherent physical, perceptual, and cognitive abilities built into Eagle 8.0.
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Robot Specifications
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Not yet published by Indus Humanoid Lab: warranty terms, safety certifications, EMC compliance, IP rating, noise level, expected lifespan, maintenance schedule, firmware version and 7 more.
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Frequently Asked Questions
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Q1. What is Eagle 8.0, and what problem is it designed to solve?
Eagle 8.0 is a humanoid robot from Indus Humanoid Lab that the company positions for classroom teaching and student interaction, with a focus on supporting teachers.
Q2. What are the main capabilities and key features of Eagle 8.0?
According to the manufacturer, Eagle 8.0 is designed for lesson delivery, content presentation, student questioning, and guided classroom assessment.
Q3. Who is Eagle 8.0 built for, and which industries can benefit from it?
Eagle 8.0 is built primarily for schools and education providers, especially K12 classrooms using collaborative learning models.
Q4. Is Eagle 8.0 a commercial product or still a research prototype?
Indus Humanoid Lab describes Eagle 8.0 as production-ready, indicating it is presented as a commercial education robot rather than a lab prototype.
Q5. Is Eagle 8.0 currently available for purchase, and when is it expected to ship?
The company has publicized sales and inquiry channels, but shipping timelines depend on distributor fulfillment and order status.
Q6. How does Eagle 8.0 actually work in real-world environments?
In classroom use, it is intended to work alongside teachers, deliver content, ask questions, and support assessment within a supervised lesson format.
Q7. When was Eagle 8.0 announced or officially launched?
The company’s website showed Eagle 8.0 in 2026, with public materials dated April 2026 indicating an official announcement period.
Q8. How is Eagle 8.0 different from other robots in the same category?
Indus Humanoid Lab distinguishes Eagle 8.0 by describing it as an education-focused humanoid built for teacher support and classroom collaboration.
Q9. Does Eagle 8.0 require additional development or customization after purchase?
The robot appears to rely on curriculum content and classroom setup, so implementation likely requires configuration and school-specific adaptation.
Q10. What is the future roadmap or planned upgrades for Eagle 8.0?
The company has indicated plans to expand its educational robot lineup and extend collaborative learning use beyond initial deployments.
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