Please join our Discord for feedback and discussions -

Demos -> 1. Doge Coin Price Forecasting -> https://t.co/8ZBcuCYXhp 2. Macroeconomics Forecasting -> https://t.co/kONl27b8Mn 3. Hotel Demand Forecasting ->

Accurate forecasting isn’t a single-model problem — it’s a data problem. Across enterprise + B2C customers, we keep seeing the same blocker: good forecasts require stitching together complex real-world signals. • Retail demand depends on promos, marketing, weather, and local

If you ask today’s LLMs, “Generate me an image with 5 apples and 7 bananas,” there’s no guarantee they’ll get it right — here are examples from Gemini and ChatGPT. Synthefy’s time series generative models can adhere to such “hard constraints” with strict guarantees. That’s why

Introducing Synthefy Migas 1.0 — our Mixture-of-Experts model that beats every open-source forecaster on GIFT-Eval. Current Time-Series Foundation models are biased. We turned those biases into an advantage. Migas 1.0 intelligently leverages those biases and delivers

Introducing Synthefy MUSEval — the largest multivariate evaluation benchmark for time-series foundation models. Real systems are multivariate: prices ↔ promos, demand ↔ weather, servers ↔ peer nodes. Yet most time-series foundation models (TSFMs) cannot process this

We’re very excited to open early access to DALL·E for Time Series, our synthetic time series models. Imagine asking: • 🩺 “Expand PPG/ECG across underrepresented cohorts for training.” • 💳 “Simulate interesting fraud patterns to stress-test detection.” • 🏭 “Create

If this mission fits your work, we’re hiring. If your use cases can benefit from a time series foundation model, apply here: https://t.co/75yFuZaM7K.

Positive transfer is one of the key concepts that unlocked foundation models. If you train a model on math, physics, Shakespeare, and coding together, it gets better on each dataset than a model trained on a single task or dataset. Why? Because there is positive transfer —

Imagine asking: 📦 “Forecast delivery demand if I cut shipping fees in half this holiday season.” 🛋️ "Forecast my couch and tables, if I start promoting couches over tables this labor day" …and getting answers in minutes, not months. No messy data pipelines. No Model

For decades, time series modeling was stuck in a narrow paradigm. Most models were univariate - looking at one signal in isolation. They ignored context because the models couldn’t handle it. @synthefyinc is changing that. 🧵

At @synthefyinc , we built something different: - A diffusion model designed for time series - A universal metadata encoder (text, tabular, categorical, continuous) - Native support for dense, noisy, real-world signals

LLMs can’t solve time series. Here’s why: LLMs are powerful, general-purpose tools. But somewhere along the way, we started treating them as the answer to every problem. They’re not. And for time series modeling, they’re the wrong tool entirely. Let’s dig in 👇

AI startup Synthefy is changing that with its multi-modal GenAI platform for time series data. Know more. https://t.co/S5UGtPDpfu

Conventional time series models are restricted to narrow historical data patterns, missing out on product metadata, macroeconomic signals, and evolving market shifts.

Time series data is everywhere – powering decisions in energy, finance/crypto, health, and more. Yet ironically, our most celebrated AI tools stumble on it. LLMs have captured the tech world’s imagination (and for good reason, they’re powerful and flexible). But they’re not a

LLMs are amazing at a lot of things - but time series forecasting isn’t one of them. In Synthefy's latest blog post, we explain why token-based architectures aren’t inherently designed for real-world time series tasks - like forecasting energy demand, retail trends, or medical

Thanks @mariogabriele for highlighting @synthefyinc in your “what to watch in ‘25”

@synthefyinc is excited to be included in the AI for Telecom program launch with @DellTech. At Synthefy, we’re building the world’s first multi-modal GenAI platform for time series data, enabling the next generation of AI solutions for Telecom. Our platform enables