CodeAnt AI Reviews

1. Amartya

   · Working at CodeAnt AI · 8 months ago

Supermemory Reviews

CodeAnt AI mentions (9)

• How to Use Snyk in CI/CD: Jenkins, GitHub Actions, More

  CodeAnt AI takes a different approach by bundling SAST security scanning with AI-powered code review in a single platform. Starting at $24 per user per month for the Growth plan and $40 per user per month for the Enterprise plan, CodeAnt AI provides static analysis, security vulnerability detection, and automated code quality review in one CI pipeline step. This can be more cost-effective than running separate... - Source: dev.to / 5 months ago

• How to Write Custom Semgrep Rules: Complete Tutorial

  CodeAnt AI provides a managed code review and security platform priced at $24 to $40 per user per month that includes built-in security rules covering OWASP Top 10 vulnerabilities, code quality checks, and automated PR reviews. CodeAnt AI is a strong option for teams that want comprehensive coverage out of the box without writing or maintaining custom rules. - Source: dev.to / 5 months ago

• DeepSource for JavaScript/TypeScript Projects

  CodeAnt AI is a modern code quality platform priced at $24-40/user/month that offers AI-powered analysis for JavaScript and TypeScript projects. Unlike DeepSource's primarily rule-based approach, CodeAnt AI uses AI models to detect code quality issues, security vulnerabilities, and anti-patterns - including context-dependent problems that deterministic rules miss. - Source: dev.to / 5 months ago

• Codacy Security Scanning: Find Vulnerabilities in Your Code

  If you are evaluating Codacy's security scanning, CodeAnt AI is worth putting in the comparison set. It is a Y Combinator-backed platform priced at $24-40/user/month that bundles several capabilities that Codacy either lacks or offers only on higher-tier plans. - Source: dev.to / 5 months ago

• How LLMs Are Transforming Code Review in 2026

  CodeAnt AI brings together LLM-powered analysis, deep code graph understanding, and automatic sequence diagram generation for every pull request. See why leading teams are making CodeAnt their standard for AI-assisted code review. - Source: dev.to / 5 months ago

Supermemory mentions (4)

• AI Agentic Memory for beginners.

  This is usually a challenge that any developer has to take care of when building an AI agent. In fact, managing the context is one of the hardest problems when working with AI agents and there are many companies like SuperMemory, Mem0 which have invested both resources and time to solve this problem. - Source: dev.to / 14 days ago

• Building an autonomous Slack agent with OpenCode

  Memory. I use Supermemory for this. Before, Pipa loaded context files and knew to update them. A memory tool adds teammate-like recall: goals, preferences, latest business state, and small details that should carry across runs. Good memory tools also know how to supersede and delete memories, which matters once the agent has more autonomy. - Source: dev.to / about 2 months ago

• Build a Real-Time Voice RAG Agent for Your Documentation

  We wire everything up with Vision Agents as the voice agent framework, Stream for WebRTC audio and video, OpenAI Realtime for speech in and speech out, Anam so the agent shows up as a face on the video, and Supermemory so answers come from search over your uploaded documents instead of guesswork. The code stays small and most of the behavior lives in one registered function that asks the memory store for relevant... - Source: dev.to / 3 months ago

• Ask HN: What are you working on (August 2024)?

  My friends and I are working on https://supermemory.ai, an AI second brain to help you remember content from saved webpages and notes. - Source: Hacker News / almost 2 years ago