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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Logfire
Pydantic Logfire is an observability platform designed to simplify monitoring for Python applications by transforming logs into actionable insights. It provides performance insights, tracing, and visibility into application behavior, including request headers, body, and the full trace of execution. Pydantic Logfire integrates with popular libraries and is built on top of OpenTelemetry, making it easier to use while retaining the flexibility of OpenTelemetry's features. Developers can instrument their apps with structured data, and query-ready Python objects, and gain real-time insights through visualizations, dashboards, and alerts. Logfire also supports manual tracing, context logging, and exception capturing, providing a modern logging interface. It is tailored for developers seeking a streamlined, effective observability tool with out-of-the-box integrations and ease of use.
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