About
We built a check for what your AI tool writes.
MegaLens is for developers who code with AI agents and want a check before AI mistakes reach their git history. Reviewers from different AI companies check the code on their own. A judge marks a finding verified only when it can quote the code that proves it.
The problem we kept hitting
We run a digital agency. We review code, audit websites, and ship SaaS products. Like everyone, we started using AI to speed up the work. Claude for one task, ChatGPT for another, Gemini when we needed web grounding.
The answers were not bad, but they were confidently incomplete. One model would miss something that a model from another family pointed out.
We got into the habit of running every important question through three models by hand. We would paste it into Claude, then ChatGPT, then Gemini. Then we would spend a long time comparing the three answers and checking which claims the code actually supported.
That manual process kept finding problems one model alone had missed. So we automated it.
The insight
“Models from the same AI family can share the same training biases. Asking one model to find its own blind spots is like asking a fish if the water is wet.”
What helped was using reviewers from different companies (such as Anthropic, OpenAI and Google). Each is trained differently and has different blind spots. A bug that one of them sees and the others miss can be the one that matters most.
“A finding counts only when the code backs it.”
A reviewer can be wrong and still sound sure. So a separate judge checks each finding against the code. It marks a finding verified only when it can quote code that is really in what you sent. Otherwise the finding is marked unverified or disputed.
What we built
Structured findings, not summaries
MegaLens returns each finding with file, line, severity, and a proposed fix. Compressed enough that your primary IDE can read and act on them without re-reasoning through the whole analysis.
Review kept separate from your IDE
Planning and audit run on MegaLens, through the models it selects. Your IDE reads the findings and decides what to fix.
Not a linter
MegaLens ignores formatting and syntax. It looks for logic, security and behaviour bugs. Keep your linter for style.
Multi-scope audit framework
Code review, security audit, research, planning and diff audit run in your IDE.
MCP on every plan
Works with Claude Code, Codex CLI, Cursor, Gemini CLI and Lovable, and with any tool that supports OAuth MCP connectors, such as ChatGPT and Claude.ai. GitHub Copilot is coming soon. Included on every plan, with no separate charge.
Honest boundary
Claude Code, Codex CLI, Cursor, Gemini CLI, Lovable and Claude.ai get full review findings. ChatGPT connects the same way, through its developer mode. GitHub Copilot is coming soon. We only claim what works on each editor. MegaLens runs when you or your tool ask for a review. It does not yet gate pull requests automatically.
Built by practitioners
MegaLens is built by SERPreach, an SEO and outreach agency. Its founder has worked in SEO since 2009. We built MegaLens because we needed it for our own work. When we realized it caught things we kept missing, we turned it into a product.
We are not a research lab building benchmarks. We audit code, review security, and ship SaaS products, and we built MegaLens for that same daily work.
AI agents make mistakes. Check them before they reach your git history.
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