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?
Yooo, Plexe looks super promising! 🔥 Ngl, building ML models in plain English is a game changer. I'm curious, what kind of ML tasks do you think it handles best? Congrats on the launch! 🎉
Congratulations Vaibhav for the launch, This is amazing. Building ML models is tough and in the higher usage of AI, its important to have small specific models for specific purpose.
Hey team, congrats on the launch here. Huge fan of Plexe AI. The simplicity that the platform provides without losing flexibility is impressive, and I can already see this speeding up the model deployment in production for teams.
As someone who’s spent way too many cycles watching ML projects stall in experimentation hell, I love how Plexe flips the workflow: diagnose → explain → deploy, all in plain English. The evaluation transparency (feature importance, bias checks, robustness) is the real differentiator, not just faster ML, but auditable ML.
Curious how you’re thinking about governance over time? For example, automated retraining thresholds or drift detection tied to real business outcomes. Either way, this looks like one of those “inevitable” products that make it easier for smaller teams to ship serious intelligence. 👏
Great product, highly recommends for easy ML iteration! We used it with Petsy and it saves us a ton of time!
this will simply become more and more valuable as AI bros forget how to actually train and build classical ML models
Super interesting! How would you suggest using it for our business? We're making a client management platform for SMEs - handling all inbound and outbound. We have data from 30,000+ interactions across platforms, and we're now helping log, answer and direct calls for SMEs.
I'm a non-technical builder, and tools like @Plexe are a godsend. But because of my non-technical background, I often don't realise or know how to spot gaps/issues. So I have a few questions:
When someone uses Plexe to create a task-specific AI solution, how do you help them understand when the model is good enough to deploy versus when it needs iteration or human-in-the-loop oversight? What safeguards are in place so something subtle doesn’t go wrong in production?”
As Plexe allows rapid deployment of custom ML models, how do you think about the balance between speed/automation and transparency/interpretability? For example: if a user doesn’t understand how the model is making decisions, how does Plexe help them trust and monitor its outputs over time?
Thank you!
Love how Plexe cuts out the ML busywork, feels like the future of data science, but actually usable.
How customizable is the visual editor when using imported templates from MJML?
How does Plexe handle edge cases during model validation? Congrats on the launch!
I've seen so many projects get stuck on messy data; how does Plexe specifically tackle those datasets?
This is a game changer. Is there a way to try the product without the initial top-up?
This is a game changer. Is there a way to try the product without the initial top-up?
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!