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High-level system architecture of Nemotron-NeuralGuard, integrating NVIDIA Nemotron-70B for real-time security validation.
Inspiration
Inspiration
As autonomous agentic workflows and decentralized architectures grow exponentially, the need for sub-second, highly deterministic security verification and payload auditing has become mission-critical. Traditional static analyzers lack contextual comprehension, while generic LLMs often struggle with instruction precision and low latency. We built Nemotron-NeuralGuard to solve this bottleneck by combining the advanced reasoning of NVIDIA's open models with the high-throughput, low-latency acceleration of Nebius Token Factory.
What it does
Nemotron-NeuralGuard is an autonomous AI safety and verification agent. It ingests code snippets, smart contracts, and computational transaction payloads to perform real-time security heuristics, vulnerability classification, and risk scoring. By querying nvidia/Llama-3.1-Nemotron-70B-Instruct via Nebius endpoints, the agent delivers structured JSON audit reports and actionable mitigation recommendations in real time.
How we built it
- AI Core & Model Architecture: Powered by
nvidia/Llama-3.1-Nemotron-70B-Instructfor deep logical decomposition and security reasoning. - Compute & Acceleration: Deployed against Nebius Token Factory, leveraging GPU acceleration and OpenAI-compatible API standards for minimal latency.
- Backend & Orchestration: Developed with FastAPI and Pydantic v2 for strict schema validation, asynchronous request handling, and modular agent execution.
Challenges we ran into
Orchestrating high-parameter reasoning models for real-time security auditing required strict prompt engineering and deterministic output formatting. We resolved this by implementing structured JSON enforcement at the agent level and optimizing payload processing pipelines.
Accomplishments that we're proud of
- Successfully creating an autonomous pipeline combining NVIDIA Nemotron reasoning with Nebius infrastructure.
- Achieving structured, low-latency automated security audits with comprehensive scoring metrics.
- Complete modular architecture ready for production scaling.
What we learned
We gained hands-on experience in orchestrating NVIDIA open models via Nebius Token Factory API, optimizing token throughput, and crafting agentic pipelines for mission-critical code verification.
What's next for Nemotron-NeuralGuard
- Expanding support to multi-agent consensus checks using NeMo Guardrails.
- Adding automated patch generation and direct GitHub CI/CD integration.
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