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From technical deep-dives to real-world case studies, discover how teams put Synthefy's foundation models for structured data into production.
Better Cold-Start Forecasting with Nori: New and Short-History SKUs
Forecasting a product that has no sales history of its own, by borrowing demand patterns from the SKUs it resembles.
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Introducing Nori Flash: Nori's Accuracy, Now in Microseconds on CPU
Nori Flash distills our tabular foundation model into a compact MLP — keep Nori's zero-training accuracy, but run inference on CPUs in microseconds, thousands of times faster and cheaper than a foundation-model forward pass.
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Introducing Nori Embeddings: Representations That Know What You Care About
We're releasing programmatic access to Nori's embeddings: target- and context-aware vectors for tabular rows, pulled straight from the pretrained foundation model. They unlock search, retrieval, interpretability, and more, far beyond regression.
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Synthefy-Nori: The Foundation Model That Replaces XGBoost
Train nothing, predict anything. Synthefy-Nori-V1 is the only fully open-source tabular foundation model — 6M parameters, zero training, and #1 mean R² across a 96-dataset regression benchmark.
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Introducing Synthefy Migas 1.0: State-of-the-Art Forecasting on Your Unique Data, in Minutes
Synthefy's Migas 1.0 Mixture-of-Experts time series forecasting model achieves top rankings on GIFT-Eval benchmark and delivers state-of-the-art results on unseen datasets.
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Synthefy MUSEval: The Largest Multivariate Evaluation Benchmark for Time Series Foundation Models
MUSEval is the first large-scale benchmark (45 datasets, 19B points, 16 domains) built to measure multivariate gain — how much better models get when given related signals.
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Why LLMs Can't Solve Time Series
Discover why Large Language Models struggle with time series forecasting and what the industry needs instead.
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"DALL-E" for Timeseries: Scaling Time Series ML with Synthetic Data Generation
Learn how synthetic data generation is revolutionizing time series machine learning, just like "DALL-E" transformed image generation.
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Introducing Synthefy API: State-of-the-Art Time Series Forecasting for Everyone
Discover how Synthefy API brings cutting-edge time series forecasting capabilities to developers and businesses of all sizes.
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Data Enrichment: The Missing Ingredient in Time Series Modeling
Explore why data enrichment is crucial for improving time series model accuracy and how to implement it effectively.
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Recognition & milestones
One of the best on leading time series benchmarks for univariate forecasting
Best performer on multivariate and multimodal time series benchmarks (Coming Soon)
US Army Phase 2 SBIR award recipient
Advancing time series AI for defense and national security applications