Provides a single MCP endpoint that lets AI coding agents search AWS docs, run sandboxed Python scripts, and make authenticated AWS API calls with enterprise guardrails like IAM condition keys, CloudWatch metrics, and CloudTrail auditing.
Provides an end-to-end platform to evaluate, observe, protect, and optimize LLM and AI agent deployments. Integrates OpenTelemetry tracing, 50+ evaluation metrics, agent simulations, an OpenAI‑compatible gateway, and guardrails; self‑hostable under Apache 2.0.
Generates page-scale UI designs and audits for Claude Code, Cursor, and Codex using a 57-gate “anti-AI-slop” rule set — produces distinct, non-template HTML+CSS outputs and supports audit, redesign, and study verbs with a built-in pre-emit self-critique.
Builds a semantic context layer for enterprise data that helps agents interpret metrics, entities, and relationships consistently. It validates generated queries against certified definitions and lineage, and returns provenance with answers.
Audits deployed AI agents for governance and operational misalignment, running up to 60 inspections that detect deception, manipulation, fabrication, unpredictability and opacity; outputs JSON/Markdown scorecards, a graded A–F score, and optional Pro reports and dashboards.
Self-hosted sales CRM that runs native AI agents (RAG per tenant) to handle WhatsApp conversations, qualify leads, trigger automations and move deals through configurable pipelines. Multi-tenant with LGPD-minded controls and a one-command VPS installer for full data ownership.
Lets developers build stateful, tool-enabled Python AI agents that run on Google's Antigravity runtime. Includes built-in tools (file I/O, shell, image generation), a declarative policy/hook system, multimodal input, and MCP integration.
Turns ongoing goals into delegated work, coordinating built-in specialists and local CLI agents across a persistent project. Conversations, files, and project memory stay on your computer by default.
Performs agent-driven security scans of codebases using LLM coding agents to find and triage vulnerabilities. Combines fast regex discovery, per-file AI investigation and revalidation, with optional sandboxed parallel execution and Vercel AI Gateway integration for large monorepos.
Self-hosted visual CMS that runs as a single Bun server, combining a canvas editor, content engine, media, auth, forms, plugins, and a publisher. Emits semantic HTML and compact CSS and includes a provider-agnostic AI agent that edits pages as real, editable nodes. Best for teams that want full control and simple deployments.
Converts technical books and document collections into an on-demand agent “skill” that Claude Code, GitHub Copilot CLI, and Amp can load to answer questions from the original content. Produces a compact SKILL.md plus per-chapter files so agents load only the needed sections, cutting token use and reducing hallucination risk.
Ingests and normalizes security telemetry, runs multi-model AI agents to produce replayable investigations and automated triage/response; key features include a step-by-step Investigation Ledger, CI-gated eval harness, and self-hostable deployments.