Adaptive learning platform · Early access
Study what you haven’t mastered yet.
Adaptivv builds a study plan from your goal and your own material, then re-plans after every quiz and revision session. Learners stop re-reading what they already know. Instructors see who is drifting while there is still time to help.
- Stage: building, early access open
- For learners, professionals and universities
- Demo runs on sample data
Mastery map
Cloud Fundamentals
Next best step
Virtual networks and subnets · Networking · 41%
Below target: a 35-minute guided session, then an adaptive quiz.
A plan that re-plans
Sessions are ordered by what is least mastered and move when your results change.
Quizzes that adapt
Each answer sets the difficulty of the next question and updates topic mastery.
Revision on a schedule
Spaced review brings topics back just before they fade, not all at once before the exam.
Cohort visibility
Instructors and programme leads see mastery and activity per learner, with suggested actions.
The problem
Most study plans are written once and never adjusted.
A certification candidate spends three weeks on networking videos they already understand, then meets identity and access management for the first time two days before the exam. A lecturer finds out a student was lost in week three when the midterm is marked in week eight.
Today’s workflow
- A fixed syllabus or video playlist treats every learner as starting from zero.
- Time goes on topics already known; weak topics surface in the final week.
- Revision is improvised: a re-read the night before, then forgotten.
- Instructors learn who struggled only after the assessment is marked.
The cost is wasted weeks for learners, retakes and drop-out risk for institutions, and no early signal for the people who could help.
With Adaptivv
- A short diagnostic builds a mastery map per topic, then the plan follows it.
- Weak topics get sessions first; strong topics get light maintenance.
- Revision cards return on a spaced schedule, driven by how well each was recalled.
- Cohort views flag low mastery and inactivity while there is still time to act.
Product
One loop: plan, practise, revise, adjust.
Each capability reads from and writes to the same learner record, so a missed quiz question changes tomorrow’s plan and next week’s revision.
Adaptive study plan
Turns a goal and a date into weekly sessions ordered by what you have least mastered, and re-orders them after each result.
Time goes to the weakest topics first.
Feeds the mastery map
Mastery map
Tracks mastery per topic from quiz answers and revision recall, with a trend for every topic.
You always know what is solid and what is not.
Drives the plan and the cohort view
Adaptive quizzes
Questions get harder after a correct answer and easier after a miss, each with a short explanation.
Practice stays at the edge of what you can do.
Updates the mastery map
Spaced revision queue
Cards return on a schedule based on how well you recalled them, so effort goes to what is about to be forgotten.
Less last-minute cramming.
Fed by quiz misses
Source-grounded explanations
When you add your own notes or PDFs, questions and explanations point back to the passage they came from.
You can check every answer against your own material.
Feeds quizzes and revision
Goal pathways
Breaks an exam or course into milestones with target dates and shows how far along each one is.
A visible route to the exam date.
Structures the study plan
Cohort insights
Shows instructors mastery, activity and suggested next actions for every learner in a programme.
Help arrives before the assessment, not after.
Reads the same signals as learners
Interactive demo
Use the workspace, not a screenshot of it.
Complete a task and re-plan, take an adaptive quiz, rate revision cards, then switch to the instructor cohort view. Everything responds to your actions. All names and figures are sample data.
Amara Okafor
This week
2 of 7 done
Readiness
67%
Exam 28 Nov · 48 days
Time left this week
110 min
Across open sessions
Study plan: Cloud Fundamentals certification
Mon
Tue
Wed
Thu
Fri
Adaptivv insight
- Plan re-ordered after Monday’s quiz: networking moved earlierAdaptivv · 2 days ago
- Quiz finished: Virtual networks, 4 of 6 correctAmara · 2 days ago
- 5 revision cards scheduled for the next 3 daysAdaptivv · 2 days ago
How it works
From goal to adjusted plan in four steps.
Set a goal and add material
Choose an exam, course or skill and a target date. Optionally upload notes, slides or PDFs to use as sources.
GoalCloud Fundamentals · 28 Nov
notes-week-3.pdf · addedRun a short diagnostic
An adaptive check across the syllabus finds where you already are, so nothing starts from zero.
Security68%Networking41%Storage66%Follow the plan, practise, revise
Weakest topics come first. Quizzes adapt as you answer, and revision cards are scheduled by how well you recalled them.
- Mon · Learn · Virtual networks
- Tue · Quiz · Cost allocation
- Fri · Revise · DNS and CDN
Review progress and adjust
Mastery and readiness update after every session. Instructors can see the same signals across a cohort and step in early.
Who it’s for
Built for people with a goal and a deadline.
Self-directed students
- Problem
- Revision for several modules at once, with no clear sense of which one is slipping.
- How they use Adaptivv
- Add module notes, set exam dates, and follow a weekly plan that reorders itself after each quiz.
- Benefit
- Fewer hours re-reading what is already known.
Professionals preparing for certifications
- Problem
- Limited evenings, a broad syllabus, and an exam date that does not move.
- How they use Adaptivv
- Run the diagnostic, work through the weakest domains first, and use short revision cards between meetings.
- Benefit
- A plan that fits fixed time rather than an open-ended course.
Universities and programme leads
- Problem
- Struggling students are visible only after assessments are marked.
- How they use Adaptivv
- Give a cohort the platform and watch mastery, activity and suggested actions per learner.
- Benefit
- Earlier, better-targeted support for students who need it.
Training providers and corporate learning teams
- Problem
- Completion rates say who finished, not who learned.
- How they use Adaptivv
- Assign learning goals, track mastery by topic, and report on readiness instead of attendance.
- Benefit
- Evidence of competence, not only completion.
Technology
How We Use Amazon Web Services
Adaptivv turns a learner’s goal, study material and quiz results into plans, questions and revision schedules. The architecture below follows that loop: material lands in S3 and is parsed asynchronously, Amazon Bedrock drafts questions grounded in the extracted text, and the learner state held in DynamoDB decides what the next plan contains.
01
Learner Access
Who is asking, and for what
Amazon Cognito
Learner and institution sign-in
Amazon API Gateway
Single API for the web app
02
Secure Storage
Material and learner state
Amazon S3
Uploaded notes, slides and PDFs
Amazon DynamoDB
Mastery, plans and review schedules
03
Processing
Parse, queue, score
Amazon Textract
Text from scanned or image-based files
Amazon SQS
Queues document jobs
AWS Lambda
Scoring and scheduling logic
04
AI Intelligence
Questions and explanations
Amazon Bedrock
Drafts grounded questions and explanations
Amazon CloudWatch
Tracks model latency and usage
05
Learner Experience
What the learner receives
Amazon SES
Revision reminders and progress reports
Services and their role in Adaptivv
- Amazon Cognito: Handles sign-up, sign-in and separate learner and institution roles for the web app.
- Amazon API Gateway: Exposes the platform API that the web app calls for plans, quizzes and revision.
- Amazon S3: Provides object storage for uploaded study material such as notes, slides and PDFs, and for exported progress reports.
- Amazon DynamoDB: Stores each learner’s mastery per topic, quiz attempts, study plans and the next due date of every revision item.
- Amazon Textract: Extracts text from scanned documents and image-based PDFs so they can be used as study sources.
- Amazon SQS: Queues document-processing and question-generation jobs so uploads never block the learner.
- AWS Lambda: Runs the plan, scoring and spaced-revision scheduling logic that re-plans after every session.
- Amazon Bedrock: Generates quiz questions and explanations from the learner’s own extracted material, each tied back to its source passage.
- Amazon CloudWatch: Monitors model latency and invocation volume so AI cost per learner stays visible.
- Amazon SES: Sends revision reminders and weekly progress reports.
Scope
This is the platform architecture Adaptivv is designing around. The website and the interactive demo on this page run on sample data and do not call these services.
Using these services does not by itself make Adaptivv compliant with any regulation or certification.
Business progress and early access
Adaptivv is being built in the open. Join the first group.
There are no customer counts or revenue figures to show yet, and we will not invent any. This is where the company stands today.
- Company founded in 2026
- Product loop defined: plan, quiz, revise, adjust
- Interactive prototype of the workspace, on this page (sample data)
- Platform architecture designed for AWS
- Early-access list open to learners, professionals and institutions
Request early access
Tell us how you would use Adaptivv. We reply by email.
Pricing
Three plans for individual learners.
Prices in US dollars per month. Early-access requests are open now; we will confirm start dates and billing details by email.
Starter
One learner with one goal
$10/ month
- One active learning goal
- Adaptive study plan
- Adaptive quizzes
- Spaced revision queue
- Mastery map
Growth
Learners juggling several goals
$20/ month
- Everything in Starter
- Multiple active goals
- Add your own notes and PDFs as sources
- Source-grounded explanations
- Weekly progress reports
Pro
Professionals and heavy users
$30/ month
- Everything in Growth
- Deeper analytics with exports
- Goal pathways with milestones
- Priority email support
- First access to new features
Universities, training providers and teams
Cohort insights, multi-user management and tailored onboarding. Priced on request.
Team
The Team Behind Adaptivv
Adaptivv is a founder-led company building adaptive learning software.
Yusuf Ajay
Founder
Founded Adaptivv in 2026 and leads product direction and company strategy.
Bakre John
Co-founder
Co-founder of Adaptivv, engineering adaptive learning algorithms and cloud systems on AWS.
Contact
Talk to Adaptivv.
Questions about the product, a pilot for your programme, or pricing for a team? Write to us.