Lune Synth™

The anti-slop learning app

Lune Synth app icon

Do the work. Scan it in. Get feedback that actually helps. From the Pre-K through the PhD level.

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Limited-time offer for the first 100 users: 2 months free & a lifetime 50% off Lune Synth™ Pro.

A quick look at Lune Synth in action.

Lost in the Cosmos

Learning is broken.

Focus scatters. Learning apps dazzle, then fail. AI does the thinking instead of the student.

1. Scattered focus 2. Flash over function 3. AI slop that cheats

Lune Synth fixes all three.

Think Duolingo, expanded beyond languages: learn almost any subject, practice real skills, and build momentum—all through a playful, space-themed interface.

Scroll down to see how

Platform Components

Handwrite. Get clear feedback.

Students solve on paper, scan their work, and get step-level guidance across a growing range of subjects. Handwriting is one of the best ways to build the neural pathways that support deeper learning and recall.

You have to actually use your brain

Write First

Keep students thinking on paper, not wrestling with a prompt box.

See Every Step

Lune Synth™ reads the work, finds the break, and shows what to fix next.

Keep Momentum

Smart practice, streaks, and feedback loops turn corrections into progress.

Luna

Luna waves hello

A tutor that won't do it for you.

Reads your exact work. Small nudges only. Never the answer.

Stuck? One precise hint for your exact step—then you finish it.

One nudge at a time No copyable solution Built for your question

Words not enough? A quick diagram from your exact problem.

Diagrams from the question Visual next-step guidance Still no final answer

Key terms surface in context exactly when they matter.

Definitions in context Subject vocabulary Quick, no distraction

Ask while working. Prompts and checks that keep you thinking.

Socratic guidance Grounded in your attempt Refuses direct answers

How grading works

01 Capture

Scan the work

Scan Work

One photo sends handwritten thinking straight into the grading flow.

02 Process

Turn work into steps

Grading Work
Grading Work 76%
Reading handwriting Turning work into clear steps
Step 1 recognized
Checking algebra
Scoring reasoning

Lune Synth™ reads the page, checks the reasoning, and shows progress while it grades.

03 Feedback

Know what to fix

Scores come with the exact mistake and a clear next practice loop.

Don't want to handwrite?

Problem Solver

Homework help that builds understanding.

Add a question or assignment. Lune Synth organizes the work and walks you through each step.

Problem Solver input screen for adding a question or assignment
01

Bring it in

Type, photograph, or attach your work.

Take One Quick Mission

Fast study mode

One clear goal. A few focused minutes.

Quick Missions are ideal when you have a bite-sized goal. They narrow the next few minutes to one fact to recall, one method to practice, or one mistake to fix.

2–6 minutes One skill at a time Immediate next step

Turn a Big Study Goal Into a Constellation

Step 01

Explore Your Learning Worlds

Start by navigating your personalized study universe. Choose from over 50 visual Worlds, then decide which existing Constellation to continue or whether to create a new one.

Select World

Earn 100+ Cosmic Medals

Two Weeks

Build a daily learning habit to keep your study streak active.

Unlock Milestone Practice on 10 consecutive days

Engine

Built to fight slop.

Lune Synth is engineered with anti-slop software design so you get feedback you can actually trust. In rubric benchmark evaluations, over 95% of multimodal responses deliver sound, defect-free evaluations down to every step—backed by explicit confidence thresholds and one-tap correction checks.

96.3%
Perfect Grading Accuracy Spot-on step evaluations on real handwritten & typed work.
95.8%
Perfect Question Quality Flawless practice sets across college & test-prep subjects.
Statistical Audit Technical Diligence, Statistical Methodology & Benchmark Suite (Wilson 95% CI)
TL;DR Executive Summary & Key Findings

Observed Soundness: 96.3% of multimodal grading evaluations (233/242 live trials across 74 distinct prompts; 95% Wilson CI: [93.1%, 98.0%]) avoided materially incorrect guidance, spanning Pre-K through graduate work in mathematics, natural science, social science, language arts, foreign language, computer science, philosophy, law, and translation studies. Curriculum question quality holds at 95.8% (115/120 items; 95% Wilson CI: [90.6%, 98.2%]) across 12 graduate generation contexts.
Conservative Prompt-Cluster View: At the distinct-prompt level, 91.9% of prompts (68/74) were sound across every input mode tested (95% Wilson CI: [83.4%, 96.2%]).
Honest Distribution: Across 242 grading trials, 90.1% (218/242) were completely clean, 6.2% (15/242) had minor non-material phrasing nuances, and 3.7% (9/242) had flagged conceptual errors—all transparently audited below.
Adjudication Caveat: Every soundness figure reflects single-reviewer, non-blind adjudication (the two evaluation halves judged by different reviewers), not double-scored consensus. These measure the soundness of the guidance, not the displayed numeric score.
Anti-Slop Mechanism: Lune Synth eliminates unanchored scores via explicit confidence gates (τ = 0.85), deterministic rubric penalty catalogs, step deduction conflict checks, and 1-tap student verification to inspect and challenge every step.
Pipeline Execution: 100% transport and execution success across all 266 evaluated API and grading calls.

01 · Empirical Benchmark Summary (Side-by-Side Audit)

Evaluation Dimension Sample Size (N) Clean (Zero Defect) Minor Nuance / Imprecision Material Failure 95% Wilson Confidence Interval
Multimodal Feedback Soundness 242 live responses (74 prompts, Pre-K–grad) 90.1% (218 / 242) 6.2% (15 / 242) 3.7% (9 / 242) [93.1%, 98.0%] (Overall Soundness: 96.3%)
Prompt-Cluster Safety 74 distinct prompts (Pre-K–grad) 91.9% (68 / 74 sound) 8.1% (6 / 74) [83.4%, 96.2%]
Curriculum Item Quality (graduate-only) 120 items (60 free, 60 choice) 91.7% (110 / 120) 4.2% (5 / 120) 4.2% (5 / 120) [90.6%, 98.2%] (Defect-Free: 95.8%)
Complete 5-Item Set Soundness (graduate-only) 24 full practice sets 79.2% (19 / 24 pristine) 20.8% (5 / 24) [59.5%, 90.8%]
Pipeline Runtime Reliability 266 evaluation API calls 100.0% (266 / 266) 0.0% drops 0.0% fatal exceptions [98.6%, 100.0%]

02 · Modality Stratification & High-Friction Stress Testing

Typed Digital Inputs (3 / 81 Material · 96.3% sound; 95% CI [89.7%, 98.7%]): Tested across dense mathematical proofs, symbolic equations, code blocks, and multi-paragraph essays, from Pre-K arithmetic through graduate coursework.
Voice Audio Transcripts (2 / 81 Material · 97.5% sound; 95% CI [91.4%, 99.3%]): Evaluated on conversational derivations, spoken step-by-step problem-solving, and spoken answers with natural pauses, revisions, and colloquial phrasing.
Handwriting & Scans (4 / 80 Material · 95.0% sound; 95% CI [87.8%, 98.0%]): No modality effect is established: the Pre-K–high-school run recorded 0 material failures across 39 handwriting responses, and the combined handwriting interval overlaps both other modes. Caveat: 14 of those 39 trials ran as OCR-simulated text—fixtures quarantined by a 0.85 transcription-fidelity gate, including all five Pre-K cases—while 25 were genuine scanned images.
Distinct Prompt-Cluster Safety Rate (91.9%): 68 of 74 distinct prompt contexts avoided any material evaluation error across all student submissions in the cluster (95% Wilson CI: 83.4%–96.2%).

03 · Compound Set Quality & Defect Independence Model

Compounding Set Mathematics: A question-level defect-free rate of p = 0.9583 (115/120) compounds across an independent 5-item mission set as:
P(Clean 5-Item Set) = p⁵ = (0.9583)⁵ ≈ 80.59%
This is consistent with the empirical benchmark result of 79.17% (19/24 full sets; 95% Wilson CI: [59.5%, 90.8%]), though with only 24 sets that interval spans a wide range of dependence structures and does not by itself establish independence. The observed 19/24 is the primary figure; the p⁵ value is a secondary projection.

04 · Evaluated Domains — Generation Contexts & Grading Coverage

Question-Generation Contexts (12 graduate disciplines): The question-generation suite was benchmarked across 12 graduate-level academic and professional disciplines:
Complex Analysis Immunology & Virology Administrative Law Compiler Optimization Psychometrics (IRT) Narratology & Literary Theory Algebraic Topology Quantum Information Causal Inference DSGE Macroeconomics Historical Linguistics Applied Cryptography
Grading Coverage (Pre-K through graduate): The 74 graded prompts spanned a broader set—mathematics, natural science, social science, language arts, foreign language, computer science, philosophy, law, literary analysis, translation studies, and qualitative methods—not limited to the 12 generation disciplines above.

05 · Anti-Slop Architecture & Deterministic Thresholds

Explicit Confidence Gates (τ = 0.85 Cutoff): When optical character recognition or symbolic semantic parsing falls below strict certainty thresholds (τ < 0.85), confidence is immediately lowered and provisional review flags are surfaced.
Rubric Evidence Grounding: Evaluations match against deterministic rubric criteria and explicit penalty catalogs rather than unconstrained holistic text generation, eliminating score drift.
Step-Level Conflict Checking: Deduction arithmetic is programmatically reconciled against rubric point weights prior to finalizing step guidance, ensuring feedback and scores remain mathematically consistent.
1-Tap Student Agency & Verification Chain: Students can inspect the full chain of evidence, contest ambiguous step deductions, challenge false negative classifications, and focus on the immediate corrective step.

06 · Defect Taxonomy & Full Failure Audit

Logged Failure Breakdown & Root Cause Analysis: All 9 material grading errors (6 in the graduate tranche across 3 distinct prompts, plus 3 in the Pre-K–high-school run) and 5 question-generation defects were formally logged and cataloged:
  • Grading failures — graduate tranche (6 responses across 3 distinct prompts): Four responses came from a single graduate astrophysics prompt on stellar fusion, where feedback endorsed thermal kinetic energy as classically overcoming the Coulomb barrier and treated quantum tunneling as optional detail; the same misconception recurred across typed, voice, and handwriting renderings of that one prompt. One response, on a philosophy-of-science scan, missed a polished but false conclusion that sufficient evidence yields a logically unique theory. One response, on a translation-studies scan, praised an incorrect tense/aspect analysis of the French imperfective retrouvais.
  • Grading failures — Pre-K–high-school run (3 responses): Three material failures were logged in the 2026-08-19 evaluation and retained in the permanent corpus; per-case root-cause detail is tracked internally rather than on this page.
  • Generation Defects (5 total): Contradictory Item Response Theory distractor rationale; non-unique option in Narratology; false-premise prompt in non-Hausdorff topology; underidentified fiscal shock equation in DSGE macroeconomics; and 1 ambiguous prompt boundary in Administrative Law.

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