Large, urgent problem
Teacher scarcity and private tutoring costs create a clear need for affordable, responsive learning support.
AQRIVO · Pre-Seed 2026
AI tutoring built for how students actually learn.
We are building a 24/7 personalized learning platform, starting with Class 8–12 in Bangladesh, that combines NCTB-grounded context, interactive explanations, deterministic tools, targeted practice, and visual learning.
RoundPre-Seed
Target raise$1.5M
Initial focusClass 8–12
ModelCredit-based freemium + B2B2C
01Investment thesis
A local wedge into a regional learning platform.
Four reasons the model can become defensible if product quality and school adoption are proven.
AI-native product
The core experience is a conversation and explanation engine—not a library of prerecorded lessons.
Distribution advantage
The planned school partnership model can acquire cohorts of learners through institutional relationships instead of one ad click at a time.
Expansion architecture
Curriculum, language, and visual layers can be localized market by market after product-market fit is proven.
02Use of funds
Capital goes into proof, not polish.
The round is intended to move AQRIVO from investor narrative to a reliable product and repeatable school-led distribution motion.
Product + AI
Build the production tutoring engine, evaluation pipeline, personalization layer, and visual learning system.
Curriculum + Content
Create and validate NCTB-grounded knowledge, learning flows, assessments, and subject coverage.
School Partnerships
Run structured pilots and build the repeatable B2B2C school partnership motion.
Infrastructure
Optimize inference, caching, observability, reliability, and data safeguards.
Core Team
Build the focused product, AI, curriculum, and go-to-market team needed for the pilot stage.
Regional Expansion
Prepare the curriculum and language architecture for expansion beyond the Bangladesh beachhead after product-market proof.
03 Diligence-ready, not hype-ready
Claims should survive the investor meeting.
01No invented traction metrics on the public site.
02No “100% accurate AI” promise.
03Financial assumptions stay in the private model, where they can be challenged.
04Equity terms can remain in the data room until valuation is defensible.
04 Next milestone
From investor preview to working pilot.
This website is the narrative layer. The next proof is a real tutor flow, measurable learning quality, and school pilot data.