Best Artificial Intelligence Software for Kiro
View:
Compare the Top Artificial Intelligence Software that integrates with Kiro as of August 2026
Sort By:
This a list of Artificial Intelligence software that integrates with Kiro. Use the filters on the left to add additional filters for products that have integrations with Kiro. View the products that work with Kiro in the table below.
What is Artificial Intelligence Software for Kiro?
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics. Compare and read user reviews of the best Artificial Intelligence software for Kiro currently available using the table below. This list is updated regularly.
-
1
Claude
Anthropic
Claude is a next-generation AI assistant developed by Anthropic to help individuals and teams solve complex problems with safety, accuracy, and reliability at its core. It is designed to support a wide range of tasks, including writing, editing, coding, data analysis, and research. Claude allows users to create and iterate on documents, websites, graphics, and code directly within chat using collaborative tools like Artifacts. The platform supports file uploads, image analysis, and data visualization to enhance productivity and understanding. Claude is available across web, iOS, and Android, making it accessible wherever work happens. With built-in web search and extended reasoning capabilities, Claude helps users find information and think through challenging problems more effectively. Anthropic emphasizes security, privacy, and responsible AI development to ensure Claude can be trusted in professional and personal workflows.Starting Price: Free -
2
AppDeploy
AppDeploy
AppDeploy is chat-native deployment — go from AI chat to deployed app. Tell your current AI chat or agent what to build, AppDeploy.ai makes it real, without leaving the chat or touching infrastructure. Deploy a real, full-stack apps directly from ChatGPT, Claude, Cursor, Gemini, Claude Code, Codex, or any other AI assistant — and get a live URL in seconds, without leaving the chat. No Git, no CLI, no IDE required. Hosting, database, backend services, storage, auth, and AI integrations are handled automatically. Every deploy gives you a live application with a shareable URL — a real deployed app, not a prototype. AppDeploy works for builders of all levels - no setup screens, no technical decisions.Starting Price: $0 -
3
InsForge
InsForge
InsForge is an AI-native backend platform designed specifically for agentic development, providing everything needed to build, manage, and deploy full-stack applications through AI coding agents. It functions as a Backend-as-a-Service with built-in primitives such as a managed PostgreSQL database, authentication with OAuth and JWT, cloud storage, serverless functions, real-time updates, and AI integrations, all accessible through a structured, agent-friendly interface. Unlike traditional backends built for human developers, InsForge exposes its services through a semantic layer and an MCP server that allows AI agents to understand, reason about, and operate backend infrastructure end to end. This enables agents to configure databases, manage schemas, handle authentication flows, deploy logic, and maintain applications with minimal manual intervention.Starting Price: $25 per month -
4
Subspace
Subspace
Subspace is an AI-native agent workspace designed to help developers and teams manage, coordinate, and collaborate with multiple coding agents in a single unified environment while preserving context across sessions. Instead of treating each AI interaction as isolated, the platform builds persistent memory in the background by compressing every conversation into structured observations such as decisions, blockers, and progress, which are continuously synthesized into a clear, evolving project state. This shared memory belongs to the workspace rather than any individual tool, allowing different agents like Claude Code, Codex, or others to seamlessly pick up where previous sessions left off without requiring repeated explanations or manual context transfer. Subspace integrates terminals, files, documentation, browser views, and git workflows into organized workspaces, enabling users to run multiple agents side by side and switch between projects almost instantly.Starting Price: $12 per month -
5
Dock
Dock
Dock is the AI workspace for you, your team, and every agent you run. It gives humans and AI agents the same shared cloud workspace, where everyone can read and write the same state in real time instead of working across scattered chats, files, and one-off outputs. Dock is built around tables with typed columns, rich-text docs, and agents as first-class identities, each with their own API keys, permissions, and audit trail rather than delegated human tokens. Teams can use Dock to plan, research, decide, and ship with humans and AI on the same surface, with use cases across engineering, go-to-market, research, operations, solo work, and agency workflows. Engineering teams can manage sprint planning, spec docs, and incident response; GTM teams can organize content calendars, sales pipelines, and customer success; research teams can track interviews, themes, and competitive intelligence; and operations teams can manage runbooks, recruiting, compliance, and onboarding.Starting Price: $19 per month -
6
Graphify
Graphify
Graphify is an open source knowledge graph engine that turns any input, including code, docs, papers, meetings, images, browser tabs, and commits, into one traversable graph with complete recall. It is built as persistent memory for AI coding assistants, giving tools like Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, Aider, Factory Droid, Kimi Code, Kiro, Pi, and Google Antigravity a queryable understanding of a project instead of making them repeatedly grep through files. Users can point Graphify at any directory, and it builds an initial corpus through AST extraction, semantic analysis, and Leiden clustering, transforming an entire codebase or document corpus into a graph in one pass. Unlike RAG pipelines that re-embed everything on every change, Graphify maintains a living graph that updates only affected nodes and edges when files change, allowing the rest of the corpus to stay intact even at enterprise scale.Starting Price: Free -
7
MemPalace
MemPalace
MemPalace is a local-first storage and retrieval system for AI workflows, built to give AI a memory while keeping the user’s words under their own control. It stores conversations verbatim instead of reducing them to summaries, then organizes that memory into a navigable “palace” structure inspired by the ancient memory palace technique. Conversations can be arranged into wings for people, projects, or topics, with rooms and drawers used to make information easier to locate, narrow, and retrieve later. It is designed for people who believe their words are theirs, with local-first storage, zero telemetry, and a privacy-focused approach that keeps memory on the user’s machine. MemPalace supports AI workflows through MCP tooling, including tools for palace reads and writes, knowledge-graph operations, cross-wing navigation, drawer management, and agent diaries.Starting Price: Free -
8
OpenViking
OpenViking
OpenViking is an open source context database designed specifically for AI agents, built around a file-system paradigm that unifies the management of memories, resources, and skills. Instead of treating context as scattered chunks in a fragmented vector store, OpenViking organizes agent context into a virtual file system under the viking protocol, giving agents a structured way to store, navigate, retrieve, and observe the information they need. It is designed to help developers move beyond the hassle of manual context management by giving agents a minimalist interaction model for context, similar to reading and writing files. OpenViking supports hierarchical context loading, semantic retrieval, recursive retrieval, sessions, metrics, and observability, making it possible for AI agents to access the right level of information without stuffing everything into the prompt.Starting Price: Free -
9
AWS Security Agent
Amazon
AWS Security Agent is a new frontier AI-powered agent that proactively secures your applications throughout the development lifecycle, from design and architecture planning, through code changes, to deployment and penetration testing. It lets security teams define organizational security requirements (for example, approved auth libraries, encryption standards, logging practices, data-access policies) once in the AWS Console; then the agent automatically validates design documents, architectural plans, and code against those standards. Before a single line of code is written, AWS Security Agent can perform a design review, analyzing architectural documents uploaded into the web application (or ingested from storage), and flag potential security risks or non-compliance with custom or Amazon-managed standards, providing remediation guidance. -
10
AWS DevOps Agent
Amazon
AWS DevOps Agent is a software from Amazon Web Services (AWS) designed to act as an autonomous, always-on operations engineer that resolves and proactively prevents incidents across your infrastructure, applications, and deployments. It automatically learns your application resources and their relationships, including infrastructure, code repositories, deployment pipelines, observability tools, and telemetry, then uses that knowledge to correlate logs, metrics, traces, deployment data, and recent code changes. When an alert, error spike, or support ticket arises, DevOps Agent immediately begins automated investigation; it triages incidents 24/7, runs root-cause analysis, and proposes detailed mitigation plans which can be automatically routed through team workflows (e.g., via Slack, ServiceNow, PagerDuty) or directly create support cases with AWS.
- Previous
- You're on page 1
- Next
