
Process Street is the Compliance Operations Platform built for teams that need to move fast without breaking standards. It combines document control, workflow automation, and AI-powered oversight in a single system so every policy is followed, every step is tracked, and every audit is effortless.
Unlike legacy GRC tools or static SOP docs, Process Street turns compliance into a living system. Policies are documented in governed, version-controlled Pages. Those policies are executed through dynamic workflows with built-in task assignment, approvals, and forms. Every action is logged, monitored, and optimized in real time by Cora, our AI compliance agent.
Used across industries like financial services, real estate, healthcare, and manufacturing, Process Street helps teams automate employee onboarding, streamline audits, manage policy updates, enforce vendor reviews, and run critical processes at scale.
No code required. No micromanagement. Just proof that work gets done right, every time.
Companies like Salesforce, Colliers, Drift, and Hartford Healthcare trust Process Street to eliminate busywork, improve operational visibility, and reduce compliance risk across the business. With native integrations, role-based access, audit trails, and ISO-aligned workflows, it is the platform that makes compliance a competitive advantage.
From onboarding to audits, Process Street is how high-stakes teams enforce standards, automate execution, and prove compliance by default.
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SciSure is a Scientific Management Platform built to support the full range of laboratory operations for scientific organizations. It combines ELN, LIMS, and Health & Safety functionality, giving teams a single system to document experiments, track sample lineage, manage chemical inventory, and run structured, audit-ready compliance processes.
Instead of relying on disconnected systems, organizations get one governed platform that improves reproducibility, increases visibility into lab operations, and reduces risk as they scale.
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FigCanvas
FigCanvas serves as an AI-driven scientific figure generator, designed for researchers to produce scientific illustrations, flowcharts, and data visualizations all in one platform. By simply describing a desired figure in everyday language, inputting methodological text, or uploading a dataset, users can receive a preliminary draft in less than two minutes. The tool accommodates various workflows including scientific illustration, data visualization, and flowchart creation, enabling researchers to effortlessly create pathway diagrams, figures related to cell biology, molecular mechanisms, lab schematics, bar graphs, scatter plots, heatmaps, volcano plots, and a variety of other research visuals without requiring any design expertise or coding skills. Specifically tailored for effective scientific communication, FigCanvas utilizes visual training that focuses on research-specific standards to ensure that the generated outputs align closely with the expected structure, composition, and style of academic publications. This innovative approach allows researchers to save time and enhance their visual presentations, ultimately contributing to clearer communication of complex scientific concepts.
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Gemini for Science
Gemini for Science enhances the process of scientific discovery by offering AI-driven tools and resources specifically designed to bolster scientific initiatives. By integrating experimental tools found in Google Labs with the science workflows offered through Google Antigravity, it aims to expedite research, improve analytical reasoning, and enable researchers to delve into the future of AI-enhanced scientific exploration. The Literature Insights feature compiles scholarly literature to uncover new research possibilities, produce well-founded research artifacts, and convert paper information into structured tables linked directly to original evidence. Meanwhile, Hypothesis Generation employs a multi-agent approach that emulates the scientific method, allowing it to pinpoint knowledge gaps, suggest viable research avenues, and outline testable research plans that could lead to significant breakthroughs. Additionally, Computational Discovery assists researchers in identifying models and algorithms through an intelligent research engine that creates and evaluates code variations according to user-specified optimization criteria, thereby streamlining the research process even further. Ultimately, these innovative tools collectively aim to revolutionize how scientific research is conducted and understood.
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