2.9->3.6+0.7
AskSia walked through every Strang style problem on my 18.06 problem set with the row column space visualization drawn. Eigenvectors finally felt geometric instead of algebraic.
AskSia for Linear Algebra2000+ universities
Linear Algebra AI: Eigenvectors that
point where they should.
AskSia walks row reduction, derives eigendecomposition, and runs SVD with the geometry shown. Built for MIT 18.06 (Strang), Berkeley Math 54, Stanford Math 51, AP Calc BC linear algebra, and the LA-for-ML track. Web, mobile, LMS extension, desktop.
+0.6 GPA in one term
average among weekly active users - 92% report better grades within 30 days
4.9 / 5 - 2M+ college students - 2000+ universities worldwide
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Quick Answer
Can AI help with Linear Algebra?
AskSia is the Linear Algebra AI for university students taking linear algebra. Members report an average +0.6 GPA increase in one term. AskSia handles linear algebra lecture transcription, multi-document Q&A across Linear Algebra, Strang style Linear Algebra, Numerical Linear Algebra, Matrix Computations, a 98%-accurate linear algebra homework solver with worked diagrams, study guides built on the AskSia-Method, visual concept maps, FSRS flashcards calibrated for linear algebra, adaptive Mock Exam quizzes, an AI essay writer with citations, and an AI-text detector. Surfaced across web, mobile (iOS/Android), browser extension (Canvas, Blackboard, Brightspace, Moodle, Everytime), and a native desktop agent for Mac and Windows. Used at 2000+ universities globally. Free for college students.
+0.6
avg GPA lift in one term
2M+
college students worldwide
2000+
universities covered
4x
surfaces - everywhere you study
Real outcomes
It's not the matrix.
It's the grade.
LA students lose points for one transposed matrix, the wrong eigenvalue, or a basis change that flipped orientation. AskSia walks every step with the geometry visualized.
3.2->3.8+0.6
For SVD I dropped my problem set into AskSia. Got the decomposition derived with each matrix piece labeled. Stopped second guessing what the singular values meant.
3.0->3.7+0.7
The visual map of fundamental subspaces became my study sheet for the final. Walked in already knowing where rank, nullity, and dimension fit together cleanly.
Why AskSia
Lecture, problem set, MATLAB, exam review.
Phone in section for a quick rank check. Laptop on the 18.06 problem set. Extension pulling Strang's syllabus. Desktop agent over MATLAB at midnight. One LA library, four surfaces.
Web App
Where matrices have geometry, not just algebra
Drag Strang, Axler, your problem sets, and your professor's slides in. AskSia row-reduces with each operation explained, derives eigendecomposition, runs SVD, and shows the geometric picture alongside the algebra.
Multi-doc Q&A across linear algebra readings with page-level citations
Convert any linear algebra source to Note, Map, Cards, Quiz
Real-time collaboration on shared linear algebra maps
Mobile App
Eigenvectors on the bus
iOS and Android. Photograph a matrix, an eigenvalue problem, or your handwritten basis change. AskSia returns the worked solution with operations justified and the geometric interpretation in seconds.
Snap-and-solve any linear algebra problem
Live linear algebra lecture record, transcribe, translate
Daily linear algebra spaced-repetition review queue
Browser Extension
Linear algebra syllabus, auto-synced
The Chrome extension adds a Sync button on Canvas, Blackboard, Brightspace, Moodle, and Everytime. Your LA syllabus, problem sets, lecture slides, and TA solutions pull into one library.
Works with all 5 major university LMSs
Read-only, never writes to your LMS
Linear Algebra module structure preserved, folders auto-built
Desktop Study Agent
Cmd+Space over MATLAB, Mathematica, or your textbook
Native macOS and Windows. AskSia summons over MATLAB, Mathematica, Python (NumPy), your Strang PDF, or your problem set. Reads your selection and returns the worked steps with geometric interpretation.
Global hotkey while studying linear algebra
Reads your linear algebra selection, screenshot, clipboard
Works offline after first launch
Everything in one place
12 study tools built for
college linear algebra.
Stop juggling Symbolab for row reduction, 3Blue1Brown for geometry, ChatGPT for proofs (where it confuses column space with null space), and your TA's office hours. AskSia is one workspace grounded in real LA coursework.
LA lecture transcription
Record your linear algebra lecture (Strang's 18.06, Berkeley Math 54). 40+ languages, sub-100ms latency, matrix notation and LaTeX-ready output preserved.
OpenMulti-textbook LA Q&A
Drop Strang, Axler, your problem sets, and 80 PDFs. Ask 'why is the singular value decomposition unique' and AskSia answers with page-cited proof.
OpenRow reduction and eigendecomposition walker
Walks Gaussian elimination with each operation explained, derives characteristic polynomial, finds eigenvalues and eigenvectors, and visualizes the geometry of the transformation.
OpenYouTube to LA notes
Paste any 3Blue1Brown Essence of Linear Algebra, MIT 18.06 lecture, or Khan Academy LA URL. AskSia transcribes, chapterizes, and pulls the worked examples into a clean note.
OpenLA Mock Exam mode
Adaptive practice across 18.06, Berkeley Math 54, and PhD-prep abstract LA patterns. Auto-graded with rationale and geometric interpretation.
OpenSia Note for LA chapters
Turns Strang chapter 6 (eigenvalues) into one note: key theorem, geometric picture, worked example, common error, exam-style problem.
OpenLA proof writer
Drafts proofs in the structure your grader wants. Justifies every line of induction, basis arguments, dimension theorem applications, and orthogonality claims.
OpenLA flashcards · FSRS
Auto-built decks: subspaces, transformation rules, matrix factorizations (LU, QR, SVD, eigendecomposition), key theorems. FSRS spacing tuned to your final.
OpenLA concept map
The whole curriculum as a navigable tree from systems of equations through abstract vector spaces. Each concept linked back to its Strang page and lecture.
OpenAI tutor for linear algebra
Voice-first or text. Walk through SVD three different ways, drill rank-nullity theorem applications, or explain why every symmetric matrix has real eigenvalues.
OpenAskSia Library
Trained on real coursework at
the world's top universities.
Browse by university, subject, or course. Every entry maps to curated study patterns for that program.
Showing 16 of 2000+ universitiesBrowse all universities
Showing 12 of 500+ popular courses
Compare
AskSia vs. ChatGPT, Quizlet,
Khan, Course Hero.
Other tools solve one slice of college. AskSia is the integrated workspace built specifically for your GPA.
| Feature | AskSia | ChatGPT | Quizlet | Course Hero / Khan |
|---|---|---|---|---|
| Built specifically for college coursework | Yes - 2000+ universities | General-purpose | User decks only | Crowd uploads / K-12 |
| Lecture transcribe + translate | Yes - Real-time, 40+ languages | No | No | No |
| 98%-accurate homework solver with diagrams | Yes - Step-by-step + visual | ~70-85%, hallucinates | No | Manual hints |
| Multi-document Q&A | Yes - 100 files, page-cited answers | ~10-20 files | No | No |
| FSRS spaced-repetition flashcards | Yes - Auto-built, 6 types | No | Manual | No |
| Adaptive Mock Exam | Yes - Auto-graded FRQ | No | No | SAT only |
| Browser extension for LMS pages | Yes - Canvas, Blackboard, Moodle | No | No | No |
| Native desktop agent | Yes - Global hotkey | Web wrapper | No | No |
| iOS & Android mobile apps | Yes - Snap-and-solve | Yes | Yes | Yes |
| Reported GPA improvement | Yes - +0.6 avg in one term | Not measured | Not measured | Not measured |
| Free for college students | Yes - No card required | Limited | Limited | Paid unlocks |
FAQ
Frequently asked
questions.
Can AskSia walk row reduction with the geometry shown?
Yes. AskSia row-reduces with each elementary operation justified (R1 ↔ R2, kR1 → R1, R1 + kR2 → R1) and shows the geometric meaning (basis change, projection). Strong on Strang 18.06 and Berkeley Math 54 problem set patterns.
Does AskSia derive eigendecomposition and SVD step by step?
Yes. AskSia derives the characteristic polynomial, finds eigenvalues and eigenvectors, and runs SVD with the geometric interpretation shown (rotation, scaling, rotation). Strong on MIT 18.06 Strang-style problem sets.
Will AskSia help with LA proofs?
Yes. AskSia walks proofs of rank-nullity, dimension theorem, spectral theorem, and the fundamental theorem of linear algebra in the structure your grader wants. Strong on Axler-track abstract LA courses.
Can AskSia help with LA-for-ML applications?
Yes. AskSia connects LA concepts to ML applications: SVD for PCA, matrix factorization for recommender systems, eigendecomposition for graph neural networks. Strong on Stanford CS229, MIT 6.867, CMU 10-701 ML prerequisites.
Is AskSia free for linear algebra students?
Yes, AskSia is free for linear algebra students to start, no credit card required. Free includes daily generation across all tools, unlimited library access, and the browser extension. AskSia Pro and Super unlock unlimited generation, full Mock Exam mode, free-response auto-grading at scale, priority models, and unlimited transcription minutes.
Which platforms does AskSia run on?
Four surfaces, all syncing in real time: (1) Web app at asksia.ai, (2) iOS and Android mobile apps, (3) Browser extension for Chrome, Edge, Brave, and other Chromium browsers, which adds Sync to AskSia on Canvas, Blackboard, Brightspace, Moodle, and Everytime, (4) Native desktop agent for macOS and Windows.
Does AskSia handle abstract vector spaces (Axler-track)?
Yes. AskSia handles abstract vector spaces, linear transformations, and inner product spaces in the Axler tradition. Walks proofs of operator theorems with proper rigor. Strong on Princeton MAT 217, Harvard MATH 121, and PhD-prep LA.
Can AskSia help with MATLAB or Python (NumPy) for LA?
Yes. AskSia reviews your MATLAB or NumPy code for LA operations, flags off-by-one indexing errors, explains why your matrix multiplication shape mismatch happened, and suggests fixes.
Is AskSia OK for LA coursework?
Yes. AskSia is built as a study aid that shows derivations step by step. Used the way you'd use 3Blue1Brown or office hours, it falls within most departments' AI policies. The AI detector verifies proof writeups read as your own work.
Start Today
Eigenvectors. Subspaces. Decompositions. Grades.
Join the LA students at MIT, Berkeley, Stanford, Cambridge, Princeton, and 1500+ programs walking row reduction with AskSia. Free to start.
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