CodeAnt AI

What CodeAnt AI does

CodeAnt AI is an agentic code security platform that integrates defense and offense in a single self-learning engine. It offers AI-powered code reviews, comprehensive code security (SAST, SCA, Secrets, IaC, SBOM), and code quality analysis. The platform also provides AI pentesting with exploit agents and Developer 360 for engineering metrics. CodeAnt AI aims to empower every builder with offensive and defensive security, ensuring code is secure, compliant, and optimized from day one. It integrates with various Git platforms, IDEs, and CI/CD pipelines, supporting over 30 languages. The platform emphasizes zero code storage and enterprise-grade security with SOC 2 Type II and HIPAA compliance.

Products

• AI Code ReviewCuts code review time by 80%, provides natural-language and pattern-based feedback on pull requests, covering code quality, likely bugs, and improvement suggestions.
• Code SecurityOffers SAST, SCA, Secrets, IaC, and SBOM in one scan. Catches real vulnerabilities, IaC misconfigs, and secret leaks with less noise, providing fix suggestions.
• Code QualityRetires SonarQube across 30+ languages, catching bugs, complexity, and duplication with auto-detection and fix suggestions.
• AI PentestingUtilizes 500+ exploit agents to perform autonomous pentesting, mapping attack surfaces and chaining real exploits, with a 48-hour report.
• Developer 360Provides engineering metrics that help ship work.
• Cloud Threat DetectionCatches suspicious activity and live threats in the cloud.
• DASTDynamic testing of running applications and APIs, even behind login.
• Cloud Security (CSPM)Identifies cloud misconfigurations and risks, mapped to real attack paths.
• Third-party packagesProvides known CVEs, SBOM reports, and risky licenses across dependencies.
• Static AnalysisSAST, secrets, and IaC misconfigurations caught before merge.

Key capabilities

• AI agents that reason across code, infrastructure & runtime
• Exploit-based agentic security platform
• AI Code Review integrated into CI/CD pipeline
• SAST, SCA, Secrets, IaC, SBOM in one scan
• Code Quality analysis across 30+ languages
• AI Pentesting with 500+ exploit agents
• Developer 360 engineering metrics
• Cloud threat detection
• DAST (Dynamic Application Security Testing)
• Cloud Security Posture Management (CSPM)
• Third-party package analysis (CVEs, SBOM, licenses)
• Static Analysis (SAST, secrets, IaC misconfigs)
• Integrates with GitHub, GitLab, Bitbucket, Azure DevOps
• Works with every IDE, every CI/CD, every language
• SOC 2 Type II & HIPAA Compliant
• Zero code storage
• Data encryption
• AI reviews every pull request, summarizing changes, spotting bugs, flagging security risks
• Fix suggestions for vulnerabilities, IaC misconfigs, and secret leaks
• Auto-detects issues and suggests fixes for bugs, complexity, and duplication
• Security Gating
• Security Dashboard
• On-Prem / VPC Deployment option
• SSO & Audit Log

Use cases

• Cutting code review time
• Strengthening cybersecurity
• Catching vulnerabilities before they ship
• Enforcing secure-by-default policies
• Streamlining remediation workflows
• Automating repetitive reviews
• Meeting compliance mandates (SOC 2, HIPAA, DO-178C, ARP 4754A)
• Scaling financial engineering teams securely
• Preventing risk in every commit
• Enabling audit readiness
• Speeding up secure delivery
• Reducing review cycles in automotive CI/CD
• Enforcing safety & quality standards (MISRA, AUTOSAR)
• Shipping secure, compliant code in automotive
• Cutting defects in aviation
• Ensuring standards compliance in aviation
• Accelerating secure reviews in aviation
• Detecting common and critical security flaws early
• Finding security issues before code ships

AI approach

CodeAnt AI uses AI agents to reason across code, infrastructure, and runtime to identify exploitable vulnerabilities and suggest fixes. It combines deterministic/rule-based engines for static analysis, secret detection, dependency scanning, and policy enforcement with AI components for natural-language code review, summarization, and suggestion generation. It uses third-party general-purpose AI (GPAI) foundation models, potentially including OpenAI, Anthropic, Azure OpenAI, or self-hosted open-weight models, depending on deployment and customer configuration. The AI-generated content is clearly labeled within the developer interface.

Tech named: AI agents, natural-language processing, pattern-based feedback, third-party general-purpose AI (GPAI) foundation models, OpenAI, Anthropic, Azure OpenAI, self-hosted open-weights models

Industries served

• Software Development
• Startups
• Enterprise
• Automotive
• Finance
• Aviation
• Healthcare

What it says sets it apart

• Combines defense and offense in a single self-learning engine
• AI agents reason across code, infrastructure & runtime to prove what is exploitable and fix it
• Goes deeper than traditional penetration tests
• Replaces 4-5 tools for code reviews, security scanning, coverage, and developer metrics for 50% less cost
• Less than 5% false positives compared to 70-80% with legacy SAST tools
• Scan runtime of < 60 seconds per Pull Request compared to 30-60 min with legacy tools
• SAST + SCA + IaC + Secrets + SBOM in one platform
• Learns from every Pull Request & repo
• Zero code storage, SOC 2 & HIPAA compliant, privacy by design
• Offers free pentest unless a critical vulnerability is found
• AI-generated content is clearly labelled within the developer interface