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?
Along with individuals, companies are using Plexe to ship recommendation engines, anomaly detection, lead scoring and more!
About Plexe on Product Hunt
“Build and deploy ML models in English”
Plexe launched on Product Hunt on October 23rd, 2025 and earned 267 upvotes and 89 comments, placing #5 on the daily leaderboard. 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.
On the analytics side, Plexe competes within Analytics, Developer Tools and Artificial Intelligence — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Plexe performed against the three products that launched closest to it on the same day.
Who hunted Plexe?
Plexe was hunted by Garry Tan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Garry Tan
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!