AI and Security Benchmarks for the New Era! We provide an overview of AI and Security Benchmarks that guide our research and product development at Pervaziv AI 🚀. We have ensured our products have comprehensive coverage with industry standard offerings 📊.
Benchmarks are vital as they turn AI development from intuition-driven experimentation into measurable engineering 🔬. They prevent drift, regression, risk accumulation, and wasted capital, helping us make informed decisions and ensuring we deliver the best solutions.
Categories
We look at a plethora of metrics across AI, Coding, Cybersecurity, Hardware platforms, and business context to make sure our research and products are top-tier ⭐:
- On the AI front 🤖 – accuracy, F1, recall, precision, inference latency, training cost, model size, quantization impact, inference cost, number of tokens, context length, throughput, hallucination rate, perplexity. Scores such as METEOR, BERT, BLEU, ROUGE, MRR, Cosine similarity, nearest neighbor, Top-k etc. 📈
- On the code front 💻 – correctness, syntax and semantic adherence, number of lines of code analyzed, programming language coverage, vulnerability probability, code quality, fuzzing rate, test-suite coverage, debuggability etc.
- On the security front 🔐 – OWASP top ten, CVSS, EPSS, severity, impact, probability of exploitation 🛡️.
- On the hardware side 🖥️ – GPU/CPU sizing, utilization, cost, availability, local vs hosted models, cloud vendor selection, independent compute providers etc.
- Finally on the business front 📊 – product licensing, cost structure, service timeline, security adherence, competitive benchmarking against incumbent AI and security companies 💼.
P.S: This is not a comprehensive list of everything we consider. Each of our lead areas – AI, Cybersecurity, and Developer Tools – have comprehensive evaluation criteria 📚.
A few benchmarks
We have analyzed over 20 benchmarks that deal with various aspects of AI/ML/Cybersecurity tools, Databases, LLMs, Embedding Models, RAG, security tools, and third-party integrations 🔎. Benchmarks such as Purplellama, HumanEval, MRQA, BEIR ranks, MTEB, MMLU, and custom tools that we developed 🛠️. We have also submitted patches for tools and benchmarks to open source projects 🌍.
Our Work
We have spent over 2.5 years understanding a wide variety of metrics, benchmarks, tools, and software ecosystem support available to us ⏳. At times, we have used popular open source projects; at other times, we have integrated existing closed source offerings to bring you the best possible outcomes. In cases where nothing met our standards, we developed our own utilities and internal tools to ensure production-grade reliability ⚙️.
Outcome
We have upheld our customers’ needs as a top priority and have spent several months creating all of our 8 products – Cortex, Enterprise AI, Developer Productivity, AI Code Review, DevSecOps Console, Risk Assessment, Package Analyzer, and Vulnerability Management 🏗️. Although we have expanded horizontally, all the products are vertically integrated under two product lines – Cortex with Enterprise AI and DevSecOps 🔗.
As you can tell, our products are truly engineering-driven platforms built for scale and security ✨. We have a Corporate Campaign for Spring ‘26 🌸 with free trial and exciting referral bonuses 🎉. Sign up for our products today. 🚀
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