# Almanax

> Almanax is an AI Security Engineer for application security teams. It performs automated vulnerability detection, CI/CD security scanning, and AppSec automation, integrating directly into development pipelines via GitHub and GitLab.

## Product

- AI Security Engineer: https://almanax.ai
- App: https://app.almanax.ai
- Documentation: https://docs.almanax.ai
- Blog: https://almanax.ai/blog
- Trust Center: https://trust.almanax.ai

## Key capabilities

- Automated vulnerability detection across all languages and platforms (Python, JavaScript, Go, Solidity, Move, Rust, and more)
- CI/CD security scanning integrated into GitHub pull requests with contextual feedback
- Custom security rules and detectors defined in plain English
- AI triage of third-party dependency alerts with reachability analysis
- Automatic patching with committable fix suggestions and PR drafts
- Threat modeling that maps system architecture, trust boundaries, and attack surfaces
- Agents that learn from developer interactions, building project-specific long-term memory
- Codebase indexing with internet access for real-time threat intelligence

## Target customers

- Application security teams at startups and enterprises
- Engineering teams shipping code daily who need continuous security review
- Security engineers managing vulnerability backlogs and CI/CD pipelines
- Companies using AI coding assistants who need to secure AI-generated code

## Company

- Founded by Francesco Piccoli (CEO) and Maxwell Watson (CTO)
- Based in San Francisco / New York
- Backed by investors including participation from Coinbase, AnChain.AI alumni
- Contact: support@almanax.ai

## Key content

- How Almanax works: https://almanax.ai
- About the team: https://almanax.ai/about
- Blog covering AI security engineering, vulnerability research, and AppSec automation: https://almanax.ai/blog
- General availability launch: https://almanax.ai/blog/almanax-general-availability-launch
- Building guardrails for AI coding assistants: https://almanax.ai/blog/building-guardrails-for-the-era-of-ai-coding-assistants
- Cybersecurity trends: https://almanax.ai/blog/cybersecurity-trends
- Silencing the noise in LLM security findings: https://almanax.ai/blog/silencing-the-noise-dismissing-llm-security-findings

## Differentiators

- AI-native: uses large language models with full codebase context, not pattern-matching AST rules
- Low false positive rate compared to traditional SAST tools (Semgrep, Snyk, SonarQube)
- Learns from team feedback: dismissed findings and review patterns build project-specific memory
- Supports traditional codebases (Python, JS, Go, Java) and blockchain (Solidity, Move, Rust)
- Enterprise-ready: no AI training on customer data, deployable on customer infrastructure, org/role-based access controls