Extract full product DNA from any live URL. Brand voice, UX patterns, content strategy, visual design, accessibility, SEO, performance, tech stack detection, CRO audit, design system maturity, PLG detection, enterprise readiness. 64 extraction passes. 20 intelligence engines. 138 tests.

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AI UX Audit - Upload a screenshot of your AI product design. Get a graded report on what's working, what's missing, and what to ship next — scored against 36 research-backed AI UX patterns.

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Design 'EfficientDenseNet' — a DenseNet variant under 10M params that incorporates VoVNet-style one-shot aggregation (OSA), depthwise separable bottlenecks, squeeze-and-excitation attention, LayerNorm pre-activation, and aggressive compound scaling. The goal is to train 2-3× faster than DenseNet-121 while maintaining or improving accuracy on ImageN

Design and build a privacy-preserving hate speech detection (HSD) system that operates agnostically to author identity. The model uses a Transformer backbone (e.g., BERT/RoBERTa) with differentially private training (DP-SGD/DP-Adam) and adversarial identity disentanglement to decouple hate-signal from author-specific stylistic fingerprints, maximiz

StackMyAI.com is a blog that breaks down complex AI tools and SaaS platforms into simple, actionable insights. This repo includes scripts and data used to power our guides and comparisons — ensuring accuracy and transparency.

Design a multi-class classification and interpretability pipeline that distinguishes rheumatoid arthritis (RA), psoriatic arthritis (PsA), and osteoarthritis (OA) from hand/feet X-ray images. The architecture combines a CNN backbone (e.g., DenseNet or EfficientNet) for disease classification with an attention-based or Grad-CAM explanation module to

Design a neuro-symbolic memory architecture for autonomous agricultural agents, inspired by the brain's Complementary Learning Systems (CLS). The architecture decouples memory into a fast-learning episodic Knowledge Graph for temporal/spatial sequences (crop cycles, disease spread) and a slow-learning semantic ML layer that compresses mature data i

Design a hybrid ML architecture that uses a GBDT ensemble as a hard-routed geometry extractor (producing one-hot leaf embeddings for Q/K), discards default leaf scores, and replaces them with a KRR or MLP-learned value representation (V). The final prediction is a dot-product Q·K·V aggregation mimicking a zero-temperature attention head, front-load

Design an ML-enhanced receiver chain for IoT-to-LEO-satellite communication, where conventional signal-processing algorithms (e.g., channel estimation, synchronization, detection) are augmented or replaced by learned models under low-SNR, high-Doppler, and resource-constrained IoT conditions.

Design a family of SOTA CNN architectures (ConvNeXt/ResNeXt-style) for ESC-50 audio spectrogram classification, parameterized across 5M, 10M, 20M, and 30M sizes. The design uses mel-spectrogram inputs, depthwise separable convolutions, squeeze-and-excitation blocks, and proper regularization (SpecAugment, Mixup, Label Smoothing) to achieve strong g

Design a multi-shopper, multi-product autonomous checkout vision system that generalises a gesture-based prototype. The system integrates hand-item association (shopper-ID to item-ID), temporal cart-state modelling via a state machine or transformer, and robustness to occlusions, put-backs, and hand-offs. Evaluation targets on-device latency and pr

Design a diffusion-based LLM architecture that replaces autoregressive next-token prediction with iterative denoising over discrete token sequences. The architecture uses a bidirectional transformer as the denoising backbone, a continuous or discrete diffusion process over token embeddings, classifier-free guidance for conditioning, and accelerated

Design a reinforcement learning architecture for autonomous vulnerability discovery in security capture-the-flag (CTF) challenges, building on the Agent Web Model's hierarchical abstraction layers. The system will model CTF environments as Markov decision processes and develop RL algorithms (e.g., deep Q-learning or PPO with hierarchical extensions

Design ModernBERT-Pro, an enhanced encoder-only transformer incorporating Multi-head Latent Attention (MLA) for global layers, fine-grained Mixture-of-Experts FFN layers, Mamba-2 hybrid blocks for linear-complexity local mixing, and a multi-stage curriculum pretraining pipeline. The target is a ~350M-param model (with ~2.5x effective FLOPs via spar

Design a CNN architecture augmented with L1 (Lasso) regularization that applies sparsity-inducing penalties on convolutional and fully-connected weights, producing a sparse feature hierarchy. The design covers integration via weight decay, structured sparsity variants (group lasso on filters), and a forward-pass formulation where lasso-proximal ste

Build an ML model that operates as an advanced multi-modal geospatial system designed to identify, classify, and forecast agricultural irrigation patterns by ingesting a fused dataset of spatio-temporal Sentinel-1 Synthetic Aperture Radar (SAR) backscatter sequences, Sentinel-2 multispectral imagery