Collect
Organise previous-year questions and relevant learning material with clear provenance.
US$200K+ raisedTeam-confirmed support for AbhyasDhara Intelligence Lab's education AI researchMeet the company
ABHYASDHARA INTELLIGENCE LAB / LEARNING INTELLIGENCEAN INDEPENDENT EDUCATION AI COMPANY ✳ INDIA
THE AI LEARNING OPERATING SYSTEM
Don't just test
what they know.
Understand
how they learn.
AI-powered teaching, assessment and learning intelligence—connecting educators and learners through insight that leads to action.
ONE LEARNING ENGINE.TWO EXPERIENCES.40 DOCUMENTED CAPABILITIES.
FIELD NOTE / 001INTELLIGENCE IN MOTION
ATTEMPT → PATTERN → PRACTICEILLUSTRATIVE SYSTEM MAP
THE ABHYASDHARA INTELLIGENCE LAB ECOSYSTEM
40
documented education-AI capabilities
20 for institutions + 20 for learners
02
product audiences
Students and education organisations
01
Explore all capabilities learning intelligence approach
Assessment → insight → next action
01 / THE IDEAFROM DATA TO DIRECTION
An answer is a data point.
A pattern is a way forward.
Most preparation systems stop after marking a question right or wrong. AbhyasDhara Intelligence Lab connects practice, possible misconceptions and what to do next.
LEARNING DIAGNOSIS / CONCEPT EXAMPLE
LAB 02Choose an example
ILLUSTRATIVE PATTERN
Percentage calculations
A learner gets the answer wrong when the base quantity changes. The pattern suggests revisiting percentage change, not repeating an entire chapter.
Relative example attempts · No actual learner records
NEXT LEARNING ACTION
↗Practice percentage changeTwo guided examples → a five-question check → a later retrieval session.
Educator/learner remains in controlLEARNING INTELLIGENCE / SIGNAL → ACTIONSee the complete learning loop
02 / TWO EXPERIENCESONE INTELLIGENCE LAYER
Built around the people
doing the learning.
Two distinct products, one shared approach to better teaching and preparation.
B2C / LEARNER EXPERIENCE01
S
Every learner deserves a better next step.
AI tutor, doubt solving, adaptive mock tests, revision and personalised plans—connected to how a learner actually performs.
Explore the student experienceB2B / INSTITUTIONS02
E
Give educators their time—and insight—back.
Live-class question intelligence, teacher-reviewed paper drafts, batch analytics and institution tooling, designed for scale.
Explore the institution platform$200K+
Funding reported
Founder-reported backing from an offline educator
75%
App development reported
Team-estimated completion of planned app work
10k
Testing capacity
Maximum programme size reported by team
01 / THE THESIS
More than generating questions. Understanding why.
A test tells you what someone answered. A carefully designed learning system should help explain which concepts need attention and what to do next.
“
The most important information in a test is not always the score. Sometimes, it's the pattern of thinking behind it.
We are researching an evidence-led workflow that connects previous-year papers, assessment design, learner performance and teacher judgement—with humans still responsible for important decisions.
- 01. Recognise question patterns
- 02. Find meaningful learning gaps
- 03. Design a more relevant next step
02 / THE RESEARCH METHODFrom exam history
From exam history
to learning insight.
A learning intelligence workflow. Every important AI-generated test or explanation is designed to be checked against sources and educator review.
Detect
Study topic frequency, question types and recurring conceptual patterns.
Design
Draft question sets, explanations and practice suggestions around the evidence.
Review
Keep educator checks and student feedback inside the improvement loop.
Research direction, not a claim that every workflow is already available in the Android app.
03 / TWO PEOPLE. ONE PURPOSE.
Built around the people who make learning happen.
More signal.
Less noise.
Explore a future teaching copilot for previous-year paper patterns, reviewable question-set drafts and finding genuine doubts in fast-moving live comments.
The educator vision ↗Not more tests.
The right next test.
Researching a way to map weak concepts, suggest focused practice, and shape revision schedules around what a learner actually needs.
↗
The learner vision ↗EXAMPLE NEXT STEPReview fractions → focused test → revisit in 3 days
04 / AREAS OF INVESTIGATION
AI research with a purpose.
These are the capabilities being explored for AbhyasDhara Intelligence Lab AI—not a list of features already released to the public.
Previous-year paper intelligence
Educators / TEAM-DESCRIBED CAPABILITY
Find recurring topics and question styles in historical papers, while preserving links to source material.
Teacher-reviewable test drafts
Educators / TEAM-DESCRIBED CAPABILITY
Propose practice sets and explanation drafts that teachers can verify, edit and approve.
Live doubt signal detection
Educators / TEAM-DESCRIBED CAPABILITY
Distinguish genuine student questions from repetitive or irrelevant live-lecture comments.
Weak-concept mapping
Learners / TEAM-DESCRIBED CAPABILITY
Use answers, error patterns and effort signals to find where a learner may need reinforcement.
Adaptive practice sequences
Learners / TEAM-DESCRIBED CAPABILITY
Recommend targeted tests, a practical study schedule and revision tips based on observed needs.
05 / BUILDING IN THE OPEN
Progress, without pretending it's finished.
APP ROADMAP / TEAM ESTIMATE
75%
Reported completion of the planned Android app work; not a measured release-readiness score.
RESEARCH MILESTONE
First AbhyasDhara Intelligence Lab AI model: 26 January 2027.
A target milestone aligned with India's Republic Day. Model development, validation and release scope remain ongoing; the date is a plan, not a guarantee.
NOWAndroid app on Google Play; AI research and development underway.
NEXTEducator review, targeted evaluation and model milestone preparation.
26 JAN 2027Planned first-model introduction.
ACCESS / APP TESTING
The next chapter starts with real learners.
The Android app is on Google Play. The team describes its testing programme as limited to a maximum of 10,000 participants; eligibility and current availability must be confirmed on Google Play.
View on Google PlayAI model release is a separate, planned milestone.
INSIDE ABHYASDHARA INTELLIGENCE LAB / PRODUCT INTERFACES
See how the intelligence takes shape.
Purpose-built, illustrative interface studies. Select a workflow to explore inputs, reasoning, sample results and human safeguards.
EDUCATOR CAPABILITY / 01
AI Live Class Chat Filter
Separates academic questions from casual messages, likely spam and ambiguous replies. Keeps teachers in control of moderation.
View the detailed workflow ↗
EDUCATOR CAPABILITY / 07
AI Question Paper Generator
Builds paper drafts aligned to syllabus, topic, language, marks and difficulty, with an answer key.
View the detailed workflow ↗
LEARNER CAPABILITY / 21
AI Personal Teacher
Explains a concept at the learner’s level, checks understanding and follows up.
View the detailed workflow ↗
LEARNER CAPABILITY / 26
AI Mistake Analyzer
Distinguishes likely conceptual, calculation, reading and time-pressure errors.
View the detailed workflow ↗LET'S BUILD MORE EFFECTIVE LEARNING
See what AbhyasDhara Intelligence Lab
could mean for your learners.
Are you an educator, coaching institute, or EdTech team? Start a conversation about the right learning workflow.