Tembo
Tembo is an AI-powered engineering assistant designed to automate routine coding tasks, helping developers focus on innovation. It monitors systems 24/7 to identify and fix production errors automatically, transforming error logs into pull requests while you sleep. Tembo optimizes database performance by diagnosing slow queries and missing indexes, improving efficiency. It integrates seamlessly with tools like GitHub, Jira, Linear, and Datadog to convert tickets and error reports into actionable code changes. The platform also explores codebases to uncover technical debt and security issues for refactoring opportunities. Trusted by teams worldwide, Tembo accelerates development velocity by automating tedious engineering work.
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Gemini Code Assist
Increase software development and delivery velocity using generative AI assistance, with enterprise security and privacy protection.
Gemini Code Assist completes your code as you write, and generates whole code blocks or functions on demand. Code assistance is available in many popular IDEs, such as Visual Studio Code, JetBrains IDEs (IntelliJ, PyCharm, GoLand, WebStorm, and more), Cloud Workstations, Cloud Shell Editor, and supports 20+ programming languages, including Java, JavaScript, Python, C, C++, Go, PHP, and SQL.
Through a natural language chat interface, you can quickly chat with Gemini Code Assist to get answers to your coding questions, or receive guidance on coding best practices. Chat is available in all supported IDEs.
Enterprises can customize Gemini Code Assist using their organization’s private codebases and knowledge sources so that Gemini Code Assist can offer more tailored assistance.
Gemini Code Assist enables large-scale changes to entire codebases.
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Macroscope
Macroscope is an AI-powered analytics and visibility tool for engineering and product teams that connects directly to a company’s codebase, commit history, issue/ticket systems like Linear or Jira, and Slack, in order to automatically generate insights about what is happening in the development workflow. It analyzes changes via code-walking the Abstract Syntax Tree (AST) to understand relationships and dependencies in code, then produces summaries of commits, pull requests (including auto-reviews and PR descriptions), overall codebase changes, and trends in feature development or bug resolution. Stakeholders can ask natural language questions about progress (“What did we ship last week?” etc.), see how engineering time is allocated, detect high-signal bugs with fewer false positives, and track productivity and status without needing to dive into all the individual diffs.
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Infrabase
Infrabase is an AI‑powered DevOps agent that continuously scans GitHub infrastructure-as-code (IaC) in context to detect and flag security vulnerabilities, cost anomalies, and policy violations before they reach production. It integrates with GitHub via an app, securely indexes repositories (without storing raw code), and uses LLMs such as Claude, Gemini, or OpenAI to generate natural-language review checklists. Developers can define custom guardrails using Markdown-based rules instead of complex policy languages. On each pull request, Infrabase provides blast-radius insights, severity scoring, and even merge-blocking triggers for critical issues. It highlights deviations from internal coding patterns and uncovers hidden costs or poorly configured resources.
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