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Compliance automation platform that continuously monitors controls and evidence to help companies achieve SOC 2, ISO 27001, and HIPAA.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.
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- ✦Continuous automated compliance monitoring across frameworks
- ✦Automated evidence collection and audit preparation
- ✦Personnel access and permissions management
- ✦Vendor and third-party risk assessment workflows
- ✦Automated security questionnaire responses
- ✦Public-facing trust center for compliance status
- ✦400+ tool integrations and an API for custom workflows
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Spec-driven development (requirements, design, tasks)
- ✦Parallel agents, local or cloud
- ✦Property-based and correctness testing
- ✦Works in IDE, CLI, web and mobile
- ✦Multiple models (Claude, open-weight, Auto)
- ✦Headless CLI for CI/CD
- ✦Context from tools like Figma and Terraform
- →Preparing for and maintaining SOC 2 or ISO 27001 certification
- →Automating responses to customer security questionnaires
- →Managing vendor security reviews at scale
- →Centralizing risk management across a growing company
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Turning prompts into maintainable, spec-matched code
- →Catching bugs unit tests miss
- →Reviewing PRs and fixing bugs in CI/CD