AI code detection for engineering teams
AI code detector for developers
Detect AI-generated code from ChatGPT, Claude, and GitHub Copilot in Python, Java, C++, and more. Conservative detection tuned for low false positives.
from pangram import Pangram
# Initialize the client
client = Pangram(api_key="your-api-key")
# Analyze a code snippet
result = client.predict(code_snippet)
print(f"AI fraction: {result['fraction_ai']}")家全球品牌信赖之选
Use cases
Secure your software
supply chain
Gain visibility into AI-generated code across your organization. Validate hiring, protect IP, and mitigate security risks with the most accurate AI code detection engine.
Verify Technical Hiring
Don't hire a prompt engineer for a backend role. Detect AI code in take-home assignments to ensure candidates understand the logic they submit.
Protect Intellectual Property
AI-generated code cannot be copyrighted in many jurisdictions. Audit your repositories to ensure proprietary software isn't built on synthetic, non-licensable foundations.
Mitigate Security Risks
AI-generated snippets often contain subtle logic bugs or security hallucinations. Flag AI-heavy commits for deeper human code review before merging.
Technical approach
Conservative detection
for code
Pangram's code analysis is purpose-built for software — not repurposed from text detection. Our model understands syntax constraints, structural patterns, and the difference between boilerplate and original logic.
Low False Positives
Pangram is tuned to be conservative — it rarely flags human-written logic as AI, ensuring you don't falsely accuse developers for using standard boilerplate.
Syntax-Aware Analysis
Unlike text, code has strict syntax constraints. Our model analyzes structural patterns across 40+ lines of code to distinguish between human logic and LLM predictability.
Multi-Language Support
Accurate detection across high-level languages like Python and Java, as well as lower-level languages like C++ and C. Additional languages added as model coverage expands.
Integration
Automated AI code
detection via API
01
Python 软件开发工具包
Drop-in integration for your backend pipelines. Install pangram-sdk and start scoring code snippets in minutes.
View Docs →
02
Hiring Platforms
Integrate with technical assessment platforms to automatically flag suspicious submissions in coding challenges.
了解更多 →
03
Batch Audits
Scan entire repositories or pull requests to assess the density of AI code detection across your project history.
Get API Key →
Yes. Pangram provides a high-throughput API designed for automated analysis in CI pipelines, pre-merge checks, internal audits, and research workflows. Many teams run detection on pull requests or nightly scans rather than blocking commits outright.
Accuracy depends on language, code length, and complexity. Pangram is most reliable on longer, logic-heavy code and intentionally avoids overconfident claims on low-signal inputs. Results are returned with confidence scores to support human review. For a deeper look at the topic, read our article on whether AI-generated code can be detected.
Yes. Some teams use Pangram to flag AI-generated contributions in open-source projects or to support internal reviews where licensing, attribution, or disclosure requirements apply. See how law firms use Pangram for IP and compliance verification.
Explore more
AI detection for
every organization
For Law Firms
AI detection for law firms and legal professionals. Detect AI-generated briefs, verify legal citations, and ensure authentic authorship in every filing.
Learn more →For Content Moderation
AI content moderation for trust and safety teams. Detect AI-generated reviews, fake comments, and synthetic content at scale via API.
Learn more →For Universities
AI detection for universities and higher education. Verify student assignments, screen research submissions, and protect institutional reputation.
Learn more →Start detecting AI code today
Secure your codebase, validate your hires, and gain full visibility into AI usage across your engineering organization.
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