Learning and careers decision

AI Math Solver+

A capable developer can build a useful image-to-step math solver (web) in a few weeks, but reproducing the mobile polish, handwriting robustness, proprietary/tuned models, and App Store subscription UX of the paid app is nontrivial.

View on the App Store
You pay

Not priced

No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.

You’d pay instead

$100one-off74 h to build

$50/mo6 h/mo upkeep

No published price to break even against.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • User uploads/takes a photo → OCR extracts math expression → solver computes answer and step-by-step explanation → render solution and optional graph back to user.

What it still won’t have

  • Polished native iOS UX and App Store distribution
  • Producer-tuned proprietary math models and model benchmarks claimed in the app
  • Built-in subscription management and App Store billing
  • Mobile-camera scanning polish and performance optimizations
  • Analytics and ongoing A/B-tuned improvements

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

No published price

AI Math Solver+ does not publish a price we could read, so there is nothing to compare against. What building costs is below.

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal web-based math-solver: backend in Python FastAPI, solver logic in SymPy, optional LLM hooks for nicer wording via OpenAI, OCR via Mathpix (or Tesseract+postprocess) for handwriting, simple React frontend to upload/take photos and display step-by-step solutions and graphs (Plotly). In scope: image upload, OCR integration, parse-to-SymPy, deterministic step generation for algebra/calculus, graphing, basic auth, logging, containerized deployment (Docker) to a single VPS. Out of scope: native iOS app, subscription-billing integration, multi-tenant scaling. Deliverables must include error handling, unit tests for parser/solver, and basic end-to-end tests for the upload→solve flow.
How we checked3 sources · 3/3 runs agreed · evidence score 59

How the score was reached

  • Partly verdict base52
  • 3 cited sources+3
  • 3/3 assessment runs agreed+4
  • Evidence score59

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat recorded