NetBrain
AI Agents can’t manage your network without context. NetBrain delivers it.
NetBrain provides a proven, safe path to Agentic NetOps, backed by an AI-powered platform informed by network context, real customer outcomes, and enterprise network expertise.
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Checksum.ai
Engineering teams shipping with AI have a new bottleneck: validation. Code output has accelerated. Quality hasn't. Checksum closes the gap.
Checksum is a continuous quality platform with a suite of AI agents that handle testing end-to-end, at every stage of the development lifecycle. Where most tools wait for a human to trigger them, Checksum runs autonomously in the background, generating tests, executing them, and repairing failures without manual intervention. Seventy percent of test failures are resolved automatically through real-time auto-recovery.
The platform covers every layer: end-to-end UI flows via Playwright, API endpoint chains, and targeted CI tests scoped to exactly what changed in a PR. All tests land as real code in your repository and are delivered as standard Playwright, owned by your team.
Checksum is fine-tuned on 1.5+ million test runs and integrates natively with Cursor, Claude Code, and 100+ AI coding agents. Type /checksum and your coding agent's output gets tested before it ever reaches review. Generation and healing happen on Checksum's cloud infrastructure which means no LLM tokens consumed, no local resources required.
The result: test suites that stay green as the product evolves, fewer regressions reaching production, and release confidence that scales alongside AI output.
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Wayve
Wayve stands out as a pioneering platform for autonomous driving technology, leveraging AI foundation models to fuel the development of future self-driving vehicles with its innovative Embodied AI strategy. The centerpiece of Wayve's advancement is a self-learning “AI driver” that empowers vehicles to interpret, anticipate, and maneuver through intricate real-world scenarios by acquiring knowledge through experience instead of depending on pre-programmed rules or detailed maps. By utilizing primarily camera inputs and deep learning techniques, this system cultivates a versatile driving intelligence capable of adjusting to new roads, urban landscapes, and various vehicle types with minimal need for retraining. Wayve's approach features a mapless and hardware-agnostic framework that allows automobile manufacturers to introduce sophisticated driver assistance and autonomous functions via software updates, accommodating automation levels ranging from L2+ to L4. This innovative design is intended to perpetually learn from both real-world experiences and simulated environments, fostering safe and instinctive driving behavior while enhancing the vehicle's response to unforeseen circumstances. With its focus on adaptability and continuous improvement, Wayve aims to redefine how self-driving technology integrates into everyday transportation.
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NVIDIA Alpamayo
NVIDIA Alpamayo represents a comprehensive platform of AI models, simulation resources, and datasets aimed at enhancing the evolution of self-driving vehicles equipped with human-like reasoning abilities. At its core lies a suite of Vision-Language-Action (VLA) models that merge visual analysis, language-based logic, and action strategies, empowering vehicles to navigate intricate driving situations and execute decisions incrementally. In contrast to conventional systems that primarily depend on pattern recognition, Alpamayo incorporates chain-of-thought reasoning, enabling autonomous vehicles to comprehend rare or unexpected "long-tail" events while providing explanations for their actions, thereby fostering increased safety and transparency. Furthermore, it seamlessly integrates with NVIDIA’s complete autonomous driving framework, encompassing aspects of training, simulation, and deployment, allowing developers to create sophisticated systems without the need to build foundational infrastructure from the ground up. With these capabilities, Alpamayo not only enhances the functionality of autonomous vehicles but also contributes to the broader goal of making intelligent transportation solutions more accessible.
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