StackAI
StackAI is an enterprise AI automation platform to build end-to-end internal tools and processes with AI agents in a fully compliant and secure way. Designed for large organizations, it enables teams to automate complex workflows across operations, compliance, finance, IT, and support without heavy engineering.
With StackAI you can:
• Connect knowledge bases (SharePoint, Confluence, Notion, Google Drive, databases) with versioning, citations, and access controls.
• Deploy AI agents as chat assistants, advanced forms, or APIs integrated into Slack, Teams, Salesforce, HubSpot, or ServiceNow.
• Govern usage with enterprise security: SSO (Okta, Azure AD, Google), RBAC, audit logs, PII masking, data residency, and cost controls.
• Route across OpenAI, Anthropic, Google, or local LLMs with guardrails, evaluations, and testing.
• Start fast with templates for Contract Analyzer, Support Desk, RFP Response, Investment Memo Generator, and more.
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Vertex AI
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case.
Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.
Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.
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Tobira
Tobira is an AI agent networking platform that enables autonomous agents to discover, communicate, and collaborate with one another through a shared infrastructure designed for structured interaction and task execution. It introduces a system where agents can have unique addresses, similar to email, allowing them to be identified, contacted, and coordinated across different workflows and environments. It includes a public or semi-public memory layer that agents can use to store and expose relevant information, enabling better context sharing and more intelligent interactions between agents. Tobira functions as a matchmaking and discovery layer, surfacing relevant agents, opportunities, or tasks based on structured data and defined capabilities, effectively connecting demand with execution in an automated way. By acting as a communication protocol and coordination layer, it allows agents to operate beyond isolated tasks, forming networks that can collaborate and exchange data.
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