StackAI is an enterprise AI automation platform that allows organizations to build end-to-end internal tools and processes with AI agents. It ensures every workflow is secure, compliant, and governed, so teams can automate complex processes without heavy engineering.
With a visual workflow builder and multi-agent orchestration, StackAI enables full automation from knowledge retrieval to approvals and reporting. Enterprise data sources like SharePoint, Confluence, Notion, Google Drive, and internal databases can be connected with versioning, citations, and access controls to protect sensitive information.
AI agents can be deployed as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, ServiceNow, or custom apps.
Security is built in with SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, and data residency. Analytics and cost governance let teams track performance, while evaluations and guardrails ensure reliability before production.
StackAI also offers model flexibility, routing tasks across OpenAI, Anthropic, Google, or local LLMs with fine-grained controls for accuracy.
A template library accelerates adoption with ready-to-use workflows like Contract Analyzer, Support Desk AI Assistant, RFP Response Builder, and Investment Memo Generator.
By consolidating fragmented processes into secure, AI-powered workflows, StackAI reduces manual work, speeds decision-making, and empowers teams to build trusted automation at scale.
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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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GPT-Rosalind
GPT-Rosalind is an advanced reasoning model created by OpenAI, aimed at enhancing scientific exploration in fields like biology, drug development, and translational medicine. Tailored for workflows in life sciences, it assists researchers in managing extensive literature, experimental findings, and specialized databases to formulate and test innovative concepts. By integrating a profound understanding of disciplines such as chemistry, genomics, protein engineering, and disease biology with sophisticated tool-usage capabilities, it effectively interacts with scientific databases, examines experimental results, and facilitates intricate, multi-stage reasoning tasks. Its functionalities span evidence synthesis, hypothesis formulation, literature assessment, sequence analysis, and experimental design, empowering scientists to transition more swiftly from raw data to meaningful insights. Furthermore, GPT-Rosalind revolutionizes cumbersome, time-consuming research methodologies into streamlined, AI-enhanced workflows, ultimately fostering a more productive scientific environment. This model exemplifies the fusion of artificial intelligence with scientific inquiry, paving the way for groundbreaking discoveries.
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CoVigilAI
CoVigilAI is a cutting-edge solution for monitoring medical literature that leverages artificial intelligence and sophisticated data analysis to identify and manage adverse drug reactions proactively, thereby safeguarding patient well-being and adhering to regulatory standards in real time. This platform simplifies the tracking of scientific and medical literature by sourcing information from major global databases like PubMed and Embase, offering customizable search parameters that enhance the pharmacovigilance literature review process. Additionally, it systematically reviews scientific articles and publications from various local journals, ensuring comprehensive global and localized literature oversight. Utilizing advanced algorithms, the system classifies Individual Case Safety Reports (ICSRs) into three categories: valid, potential, and invalid cases, while its automated key entity recognition capability adeptly identifies essential elements such as patients, medications, adverse reactions, and relevant medical events. This holistic approach not only streamlines the monitoring process but also significantly enhances the accuracy and efficiency of drug safety assessments.
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