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Intent Ledger is an offline hybrid facet-graph shopping copilot that remembers changing needs, narrows exact constraints, and protects recall with progressive search.
Making every GPU cycle count
Vettage is a robust AI-image detector designed for the real world, identifying AI-generated images even after compression, resizing, cropping, blurring, and other common online transformations.
Stop scrolling through filters. Just tell our AI what you're looking for, and it asks the right questions to find your perfect product in minutes, not hours.
A deterministic, multi-turn shopping agent, 'Your Shopping Bestie' that remembers active preferences, handles changed intent and rejected recommendations.
Robust Detection of AI‑Generated Images Under Real‑World Transformations
A Transformer layer that picks its own kernel — 1.32× average, nothing slower than baseline.
Your smart shopping companion who truly understands your desires.
Meet SCOPE—your offline shopping mind-reader. It remembers what you want, asks the right questions, and finds your perfect match among 50,000 products in under three turns.
A compact ViT detector that identifies AI-generated images and remains robust after real-world transformations, with confidence scores and fully offline inference.
A robust AI-image detector designed to withstand real-world transformations and cross-domain shifts, with reproducible evaluation and an interactive demo.
automate evaluate
“Anything you mean, conversationally found.”
naruto or cappuccino assassino? AI image detection that works in the real world — 98.14% accuracy across 15 transforms (JPEG, blur, noise, resize, crop, jitter) with a frozen threshold.
An AI that does the deciding, not just the coding.
A Transformer bottlenecks differently at every input shape. We time the candidates at runtime and cache the winner per shape: ~10x geomean speedup, 13/13 correct, on a laptop GPU.
We built a hybrid detector (CLIP + frequency analysis) that catches AI-generated images even after blur, compression, resizing, or noise -- the stuff real images actually go through.
You can’t trust everything you see, but with us, you can. 💖 InvariantTrace checks the facts.
A detector is only worth its accuracy on generators it has never seen. 0.958–0.989 balanced accuracy on an unseen generator across five transforms — and we found the 2026 models it still misses.
Comparing how small multimodal models (SigLIP) and Vision Language Models (Qwen) perform on detecting AIGC
Akinator for commerce: 50,000 suspects, 10 questions. MIRA asks the question that most collapses its belief over the catalog. TechnicalScore 0.9805 vs the 0.1067 baseline. Zero API calls, $0.00.
bbq sauce has designed a shopping copilot to find the perfect product for you in a Top 10 list in roughly 3 turns, with no LLM API, fully offline, with every design decision backed by data.
are you ai?
Meet Pip, your AI shopping companion. Simply tell Pip what you’re looking for, even if you’re unsure of your budget, brand, or specs, and Pip will adapt and find the right products for you.
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