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New for Eye on AI: In the age of vibe coding, trust is the real bottleneck thanks to Itamar Friedman for chatting on this one! https://lnkd.in/eKzyuAfZ
About us
Qodo is the enterprise platform for AI-driven code review, designed to help engineering teams keep pace with the velocity of coding. As AI accelerates development, Qodo ensures quality scales alongside it. Our multi-agent platform integrates deep code base understanding, automated rule enforcement and agentic review intelligence to deliver context-aware code reviews across the SDLC. Its agents handle PR review, in-IDE feedback, background remediation, to ensure issues are caught early, fixes are validated, and standards are consistently enforced.
- Website
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https://www.qodo.ai/
External link for Qodo
- Industry
- Software Development
- Company size
- 51-200 employees
- Headquarters
- New York, NY
- Type
- Privately Held
- Specialties
- AI, ML, code, code integrity, unit test, functional code quality, generative AI, generative code, copilot, and chatgpt
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New York
New York, NY, US
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Looking forward to this one! Excited to join Simon Maple, Kunal Kushwaha, Qodo Ambassador 🧑🏼💻 Brian Vermeer and Qodo Solutions Engineer Nupur Sharma ( 👑 ) to talk about the importance of being able to trust agents in production! If you are in the London area, join us!
AI agents do not break when you expect them to. They break when everything looks fine. On April 8, Nupur Sharma dives into the failure modes that only appear in real-world usage. Not obvious crashes, but subtle issues like silent errors, inconsistent behavior, and gradual loss of reliability that are hard to detect and even harder to fix. This session focuses on what actually happens after deployment, where evaluation falls short and edge cases start to define system behavior. The conversation continues with a panel featuring Simon Maple from Tessl, 🧑🏼💻 Brian V. from Snyk, Nupur Sharma from Qodo, and Kunal Kushwaha from Cast AI, sharing how these challenges show up across different systems and what teams are doing about them. If you are building or working with AI agents in production, this is a perspective you want before things go wrong. April 8 Register: https://luma.com/rkije5di
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AI wrote the bug. AI reviewed it. And it still shipped. The team Qodo built a free tool to show you what's already in your repo: The AntiSlop Scanner runs Qodo's agentic reviewer across your 10 most recent merged PRs. No setup. No account. Takes 5-15 minutes. You get a letter grade, a prioritized list of findings by severity, file paths and line numbers, and a projected annual bug estimate. First 1,000 scans only — scan your repo now → https://lnkd.in/e8v7NKMh
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Yesterday's $70M Series B is not the full story. The story is the shift happening in enterprise software right now, from writing code, to generating it with agents, to the hard part nobody fully solved yet: governing it. Every engineering leader we speak with is asking the same questions. Can I trust what's being shipped? Is it aligned with our standards? Is it tomorrow's technical debt? That's the problem Qodo exists to solve. Hear more from Qodo CEO Itamar Friedman and check out the video below!
We are excited to share that Qodo has raised $70M, led by Qumra Capital ��� But this is not the story. The story is this: Software development has fundamentally changed. But this tectonic transformation is still in its early days, especially for real-world, enterprise-grade systems. Every engineering leader we speak with is asking the same questions: 1. "Can I trust what is being shipped?" 2. "Am I using the right tools and processes for this new AI-native world?" 3. "As PR volume and size continue to grow rapidly, is the code correct, aligned with our standards and intent, and not tomorrow’s technical debt?" This is the shift: From writing code, to agentic code generation, to governing it systematically. At Qodo, we are building the missing layer: A system for code review, quality, and governance in the age of AI-generated software. Not just more output, but trusted output. This is a long-term mission. The tooling, processes, and interfaces will evolve rapidly, and we are just getting started. --- Imagine a world where: > You plan features with AI, and Qodo reviews those plans to optimize them before a single line of code is written. > You execute with coding agents that continuously interact with Qodo to verify correctness, integrity, and alignment with intent. > Every code change comes with a full verification report, backed by hundreds of signals, so you know if it's good to go, or exactly what needs attention. Imagine a world where: > at any moment, you understand the health of your codebase. > Not through guesswork, but through clear, actionable insights into integrity, compliance, maintainability, and security. This is the future Qodo is building, together with our ecosystem and you. --- We are incredibly fortunate to be on this journey with: • Customers pushing the boundaries of modern engineering • A deeply mission-driven team • Partners and investors who think boldly and act with conviction Thank you to everyone building this with us 💜 The transformation of enterprise software development has just begun. Stay tuned for our April product announcements.
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🚀 🚀 Today Qodo is announcing $70M in Series B funding to lead the market in AI code quality and governance. A year ago, AI was suggesting code. Today it's shipping it autonomously. The quality gap we saw coming is now landing in production at scale, and most engineering teams don't have a governance layer built for that reality. Qodo was built for this moment. Review, quality, and governance for the agentic era. "As we expand the use of AI-assisted development across our platforms, Qodo ensures every line of code meets our standards for performance, security, and compliance. The layer of governance Qodo provides is critical to delivering seamless, reliable travel experiences at a global scale. We are innovating faster while maintaining the trust our customers place in us at every stage of their journey." — Christian Rudolph, Head of Platform Services, TUI Group. The future of software is autonomous. But it also has to be wise. Huge thank you to Qumra Capital for leading this round!! 🚀 Read the Full announcement → https://lnkd.in/e9CKs9-R?
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Agents generate code fast. The standards they violate show up later: in review, in production, in postmortems. Nnenna Ndukwe ~ AI and Emerging Tech built PolicyNIM to move that check earlier. Way earlier. Right before the agent starts coding. PolicyNIM is a thin preflight layer: a policy corpus (security, backend, auth standards), semantic retrieval via NVIDIA NIM's embedding and reranking models, and two access points - the CLI and MCP server. The agent fetches the relevant policies for its specific task before generation begins. The result she found: PRs that needed less discovery and more verification. Smaller, cleaner, more useful reviews. For teams that want this behavior without building the retrieval stack themselves, the post covers how Qodo's Rules System handles it; rule discovery from codebase and PR history, scoped enforcement, and a mechanism to load standards before code tasks begin. Full build walkthrough → https://lnkd.in/e67yESUc
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Shipping AI Code faster than you can measure its impact? That's the governance problem and the data backs it up. We ran two live polls during yesterday's Beyond AI Code Review live stream, and the results were eye opening! ❓ Biggest concern about AI-generated code in production: • 38%: tech debt ("AI slop") • 24%: verification is the new bottleneck • 24%: security concerns ❓ Are you measuring the impact of AI on code quality? • 71% said no. 🔎 The majority of teams are shipping AI-generated code, worried about what it's doing to their codebase, and flying blind on whether it's helping or hurting. That's not a tool problem. That's a governance gap.
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The first time most new logic runs is in production. Not in a test. Not in review. In production. That's what AI-assisted development has done to coverage. PRs that used to touch a few files now span API contracts, auth logic, and error handling, written in minutes. Coverage percentages stay the same. The new paths have never run. We wrote about what this actually looks like in a real PR: a "Big update with multiple architectural concerns and breaking changes" that had a test file, passed CI (once a lock file issue was fixed), and still had an entire v2 router with zero execution under tests. Auth success. Auth failure. 404 handling. Environment-dependent error paths. All untested. All headed to production. AI-powered coverage makes this visible at review time; not after merge. The paths are named. The approval becomes conscious. Read the full walkthrough → https://lnkd.in/eaNyRzCj