AI agents will soon run the world’s data, but when they need to predict, where does the model come from?
Not another data science project. A utility.
Just uploaded a CSV → trained → live prediction endpoint in minutes. Even beat H2O & AutoGluon on live BTC direction.
This is the missing prediction infrastructure for the agent era.
👉 https://t.co/TMEWTFkFpg
#AIAgents #PredictiveAI #MLInfrastructure #BTC #Bitcoin
Just leveled up tabular intelligence ⚡
https://t.co/87vHlsEvG7 now runs a full Model Team — boosted trees + regularized linear + TabM (Yandex neural beast) — intelligently meshed together for stronger, more robust predictions on real messy data.
No more single-model compromises.
The real flex? Full MCP-native. Drop your CSV into Claude, ChatGPT, or Cursor and watch the agent build, evaluate, and deploy a live prediction endpoint in minutes.
The future isn’t just LLMs. It’s LLMs with serious tabular superpowers.
Pro is live - request access! → https://t.co/nVGASuzbXE
Who’s building the next killer agentic workflow? 👀
#AI #AutoML #MCP #Agents
Better AutoML is not just about training more models.
It is about choosing the right ones.
Our platform uses hill-climbing ensemble selection to build stronger ensembles from the models that actually improve validation performance.
Agents will decide. Precision needs the best tools.
#AutoML #AI #MachineLearning #GenAI
We will soon be posting details about a #BTCUSD#Bitcoin price prediction model use case created on our platform, Just-In-Time Models.
All models were created via our #MCP server by an #LLM.
Our 18-model ensembles using different architecture families produce world class predictions. Agents are first class citizens here. #AI #ML #JITM
Access all of your models with Claude Desktop or ChatGPT - simply use our MCP server. Why do #ML and #AI any other way? LLMs can make your predictive models for you on our platform and help you understand the complicated parts. #JITM#ArtificialIntelligence#Predictions
Two quiet upgrades shipped to https://t.co/dSWTvJpamT this week:
→ Phase 2 now trains XGBoost, LightGBM and CatBoost side by side and ensembles the best of each.
→ Time-series data is detected automatically and validated chronologically, so models can't peek at the future during training. The most common silent bug in real-world ML.
Incrementally building a world-class modelling platform. Step by step.
Full write-up ↓
https://t.co/oQO2VT32G8
Next up: deeper reasoning about your data, so JITM engineers features the way a seasoned data scientist would.
#AI #AutoML #Agents