Vibe training for AI agent reliability. Describe what your agent should and should not do — Plurai generates training data, validates it, and deploys a custom model in minutes. It feels like vibe coding, but for evaluation and guardrails. No labeled data. No annotation pipeline. No prompt engineering. Under the hood, small language models deliver sub 100ms latency, 8x lower cost than GPT as judge, and over 43% fewer failures. Always on, not sampled. Built on published research (BARRED).
NovaVoice
If this actually reduces hallucinations or cost + policy violations at scale, thats huge!
That's where most of the pain is for me
Plurai
@redzumi Totally hear you, that’s exactly the pain we built this for.
What we’re seeing in practice is that once you move from generic LLM-as-a-judge to a task-specific SLM trained on synthetic + debate-validated data, you get:
Fewer hallucinations / policy misses (because the model actually learns your failure modes, not generic ones)
Much lower cost + latency (small model, real-time)
And the ability to enforce on every interaction, not just sampled evals
It’s not magic, the key is the data. The paper shows that without proper validation, label noise kills performance, but with debate-based verification you get much cleaner signals and significantly better accuracy If you’re feeling this pain in production, you’re exactly the ICP we’re building for. Curious what kind of failures are hurting you most today?
Plurai
@redzumi That's really validating what we've been hearing and the pain we want to prevent! Let me know if we managed to do it for you!
Plurai
@redzumi We're here if you have any more questions! Let us know what you think once you try it out!
Plurai
@redzumi proof is in the pudding. Try it yourself! plurai.ai/launch
Plurai
@redzumi Indeed, in our research paper we demonstrate how our approach reduces significantly failures hallucinations or cost
Plurai
@redzumi @ilankad23 cool!
RankSpot
Congrats on the launch, does it work with all LLMs that provide fine-tunning capabilities?
Plurai
@danshipit Thank you! Looping @ilan_kadar to answer your question
Plurai
@danshipit On the LLM optimization path we're fully model agnostic. On the SLM path we train the model ourselves on your policies — so either way, no fine-tuning on your end.
Plurai
@danshipit let us know what you thought!
Plurai
@danshipit Yes!
vibe-training as a concept is interesting — how does it handle drift over time once the agent's prompt or tool surface changes? curious if you re-run the eval generation or if it's a one-time thing.
Plurai
@tijogaucher that’s a great question!
Plurai
@tijogaucher looping in @ilankad23 and @reut_v_plurai to answer your question
Plurai
@tijogaucher great question - you're thinking about the extra mile and so did we.
We do allow feedback loops and extended monitoring in our enterprise solution, hit me a note to reutv@plurai.ai if that's interesting, otherwise I would let @ilankad23 respond on best practices for managing this yourself
mailX by mailwarm
Plurai
@karimbenkeroum I already know you have experience from this nuanced question! You are right - the task definition is critical - however we have put this "intent calibration" process in place exactly for this reason - have you tried the product? You start with defining the task, then get "deep research" like refinement questions to really get what you're trying to do and finally we generate sythetic test set with classifications so you can see EXACTLY WITH YOUR OWN EYES the eval/guardrail does what you intended.
If you haven't tried it, go to app.plurai.ai - it's completely free and no credit card is required. If you have- feel free to tell me more about your experience! I love to hear it from PROs ;)
Plurai
We talked to hundreds of AI teams before building this.
The same thing kept coming up: evals are on the roadmap, always. They just never get done. Too slow, too expensive, someone needs to label data, someone needs to set up a pipeline, and suddenly it's a Q3 project that rolls into Q4.
That's the problem we actually solves.
Describe what your agent should and shouldn't do, and you have a custom model running in minutes. Not a prototype. In prod.
Launching today and genuinely excited about it.
Go try it free: app.plurai.ai. Come back and tell me what eval problem you're working on.
Plurai
@omri_sela2 🚀
Plurai
@omri_sela2 can you believe it's finally out??
Plurai
@reut_v_plurai our baby 👶
minimalist phone: reduce your screentime
So does it prevent AI agents from purchasing overpriced courses, right? :D
Plurai
@busmark_w_nika 😅 it can!
Plurai
@busmark_w_nika Yes and more:)
Plurai
@busmark_w_nika did you get a chance to try it out yourself?
minimalist phone: reduce your screentime
@tammy_wolfson2 I only tried one prompt, but at the moment I do not haev any data to train on.
Tested it during the weekend and it’s amazing!!!
Plurai
@eduardo_ordax great to hear!
Plurai
@eduardo_ordax amazing!
Kilo Code
awesome! make sure to leave a review here: https://www.producthunt.com/products/plurai/reviews/new
Plurai
@eduardo_ordax what did you like most?
Plurai
@eduardo_ordax glad you love it!