Plurai
For AI teams: Plurai generates custom evaluation models and guardrails in minutes without labeled data, reducing agent failures by 43%.
Built by Ilan Kadar · Artificial Intelligence · Developer Tools · API · Freemium
In category: #12 of 2034 · Artificial Intelligence
Plurai is a Product Hunt listing on Launch Llama with 700 total upvotes, founded by Ilan Kadar who joined in May 2026, compared against 4 alternatives.
Product Hunt listing
Listing status
700upvotes
Community score
Ilan Kadar (Joined May 2026)
Founder
Compared against 4 alternatives
Market comparison
Launched on Launch Llama May 1, 2026 · #1 of 19 that day








About
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).
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Launch Llama's Take
Based on Launch Llama data as of
Plurai has 700 upvotes, including the votes it received on Product Hunt, which ranks it #12 of 2,034 Artificial Intelligence tools on Launch Llama by upvotes, in the top 10%. It has been listed on Launch Llama since May 2026. 5 Launch Llama members have upvoted it and it has no reviews yet.
Key Features
- Build real-time evals and guardrails for AI agents
- Generate training data without manual labeling or annotation
- Deploy custom evaluation models in minutes
- Evaluate semantic tasks including conversation and policy compliance
- Run models with sub-100 millisecond response latency
- Deploy on-premises for maximum security and data control
Use Cases
- Teams building AI agents who need to reduce failure rates and deployment costs
- Developers running large-scale production testing requiring continuous validation coverage
Who it is for
- AI teams building and shipping LLM agents who need evals and guardrails.
- Engineering teams that need production-grade agent evaluation at scale while controlling cost.
- Security- and compliance-minded organisations that require on-prem or VPC deployment of AI evaluators.
Pricing
Free plan includes 1M tokens. Pay-as-you-go SLM pricing at $0.15 per 1M tokens. Optimized LLM at $0.3 per 1M tokens. Enterprise plans available with on-prem deployment and custom pricing.
Plurai at a glance
- 01What it is
- Plurai: For AI teams: Plurai generates custom evaluation models and guardrails in minutes without labeled data, reducing agent failures by 43%.
- 02Pricing
- Plurai pricing: Free plan includes 1M tokens.
- 03Best for
- Plurai is best for aI teams building and shipping LLM agents who need evals and guardrails., engineering teams that need production-grade agent evaluation at scale while controlling cost. and security- and compliance-minded organisations that require on-prem or VPC deployment of AI evaluators.
- 04Alternatives
- Top Plurai alternatives on Launch Llama: Vibe Planner, OfoxAI and OpenAI.
FAQ
How do I use the evals and guardrails on my agents?
Information available in the use case catalog.
How is that different from the evals I already have?
Plurai uses a proprietary intent calibration process to deeply understand your task and generate a high-quality testing set and consistent evaluator. This enables production-grade evals and guardrails powered by optimized small language models (SLMs), which are far more cost-efficient and scalable than traditional LLM-as-judge approaches that are expensive and difficult to run at full production coverage.
Can you do this on prem?
Contact us for on-premises deployment options.
What makes your SLMs so accurate and cost-effective?
Plurai's SLMs are optimized through proprietary intent calibration and training processes.
Do you only have SLMs or other models as well?
Information about model offerings is available upon inquiry.
Is Plurai's Proton product only for evals and guardrails?
Information available in the use case catalog.
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Supporters
5 founders
5 founders supported Plurai on Launch Llama.
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