Plexe automates the full ML lifecycle from messy data to deployable models. Run 50 plus diagnostic tests, detect failure modes, and generate insights, dashboards and models using plain English. No notebooks. No guesswork. Just results.
Note: We're getting a lot of users asking about trying the platform. You can try Plexe now with promo code "LAUNCHDAY20" to get free $20 credit!
Hi Product Hunt community!
As ex-ML engineers, we’ve always seen that building ML models takes months. So we set out to fix that. With Plexe, you can build and deploy ML models 10x faster from plain English.
Plexe connects to your data sources and builds ML pipelines autonomously. Based on your problem description, it discovers your data, performs feature engineering, experiments with model architectures and deploys production-grade models. It can also visualise your data, create dashboards and help you uncover deep insights from your data.
The Problem
Lots of great use cases for ML models in businesses never materialize because ML projects are messy and convoluted. You spend months finding the data, cleaning it, experimenting with models and deploying them to production, only to find out that the project has been binned due to taking so long. At a previous company, we witnessed a team of 10 ML engineers spend 2 years and $3M building models for a project that never saw the light of day.
There are several tools for “automating” ML, but it still takes teams of ML experts to actually productionize something of value. And we can’t keep throwing LLMs at every ML problem. Why use a generic 10B parameter language model, if a logistic regression trained on your data could do the job better?
Note: We're getting a lot of users asking about trying the platform. You can try Plexe now with promo code "LAUNCHDAY20" to get free $20 credit!
Hi Product Hunt community!
As ex-ML engineers, we’ve always seen that building ML models takes months. So we set out to fix that. With Plexe, you can build and deploy ML models 10x faster from plain English.
Plexe connects to your data sources and builds ML pipelines autonomously. Based on your problem description, it discovers your data, performs feature engineering, experiments with model architectures and deploys production-grade models. It can also visualise your data, create dashboards and help you uncover deep insights from your data.
The Problem
Lots of great use cases for ML models in businesses never materialize because ML projects are messy and convoluted. You spend months finding the data, cleaning it, experimenting with models and deploying them to production, only to find out that the project has been binned due to taking so long. At a previous company, we witnessed a team of 10 ML engineers spend 2 years and $3M building models for a project that never saw the light of day.
There are several tools for “automating” ML, but it still takes teams of ML experts to actually productionize something of value. And we can’t keep throwing LLMs at every ML problem. Why use a generic 10B parameter language model, if a logistic regression trained on your data could do the job better?
What have Plexe users shipped?
Asset price prediction: https://www.linkedin.com/posts/laxmi-prashanthi-muthyala_plexiai-mlmodel-machinelearning-activity-7375974160373661696-tw-i
Investment performance optimizer: https://console.plexe.ai/share/c9af134d-bac4-42aa-8b35-7ba49c804618
Fraud detector: https://console.plexe.ai/share/9d6665f7-11ab-470a-ad60-64011663d31b
Logistics & delay forecaster: https://console.plexe.ai/share/fe27d994-9347-44d2-80aa-4a1d901c57b7
Reddit’s pizza request success predictor: https://console.plexe.ai/share/3d37880a-c418-4f2b-a2ca-a9588c66c410
Along with individuals, companies are using Plexe to ship recommendation engines, anomaly detection, lead scoring and more!