Pipedrive
Pipedrive is a powerful CRM and sales pipeline management platform designed to help businesses track and optimize their sales processes. The platform offers automation tools, AI-powered sales insights, and real-time reporting to help businesses close deals faster and more effectively. With customizable workflows, integrations with a wide range of apps, and an intuitive interface, Pipedrive supports sales teams of all sizes in managing leads, automating repetitive tasks, and monitoring performance for smarter, data-driven decisions.
Learn more
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.
Learn more
Molmo
Molmo represents a cutting-edge family of multimodal AI models crafted by the Allen Institute for AI (Ai2). These innovative models are specifically engineered to connect the divide between open-source and proprietary systems, ensuring they perform competitively across numerous academic benchmarks and assessments by humans. In contrast to many existing multimodal systems that depend on synthetic data sourced from proprietary frameworks, Molmo is exclusively trained on openly available data, which promotes transparency and reproducibility in AI research. A significant breakthrough in the development of Molmo is the incorporation of PixMo, a unique dataset filled with intricately detailed image captions gathered from human annotators who utilized speech-based descriptions, along with 2D pointing data that empowers the models to respond to inquiries with both natural language and non-verbal signals. This capability allows Molmo to engage with its surroundings in a more sophisticated manner, such as by pointing to specific objects within images, thereby broadening its potential applications in diverse fields, including robotics, augmented reality, and interactive user interfaces. Furthermore, the advancements made by Molmo set a new standard for future multimodal AI research and application development.
Learn more
Olmo 3
Olmo 3 represents a comprehensive family of open models featuring variations with 7 billion and 32 billion parameters, offering exceptional capabilities in base performance, reasoning, instruction, and reinforcement learning, while also providing transparency throughout the model development process, which includes access to raw training datasets, intermediate checkpoints, training scripts, extended context support (with a window of 65,536 tokens), and provenance tools. The foundation of these models is built upon the Dolma 3 dataset, which comprises approximately 9 trillion tokens and utilizes a careful blend of web content, scientific papers, programming code, and lengthy documents; this thorough pre-training, mid-training, and long-context approach culminates in base models that undergo post-training enhancements through supervised fine-tuning, preference optimization, and reinforcement learning with accountable rewards, resulting in the creation of the Think and Instruct variants. Notably, the 32 billion Think model has been recognized as the most powerful fully open reasoning model to date, demonstrating performance that closely rivals that of proprietary counterparts in areas such as mathematics, programming, and intricate reasoning tasks, thereby marking a significant advancement in open model development. This innovation underscores the potential for open-source models to compete with traditional, closed systems in various complex applications.
Learn more