Amazon vs Harness

Amazon's AI shopping assistant in the Amazon Shopping app and on Amazon.com: answers shopping questions in the search bar, builds shopping guides and product comparisons, shows price history, and automates deal-finding and cart-building from the user's preferences.

Amazon's generative-AI Alexa: a conversational assistant across Echo devices and the Alexa app that handles multi-step requests, remembers context and acts on behalf of the user.

An assistant that provides conversational answers and guidance to procurement teams.

Amazon Connect Decisions provides supply chain planning and intelligence with AI teammates.

Amazon Connect Talent uses AI teammates to assess and interview candidates.

An operations service that uses machine learning to detect abnormal application behavior.

A component that lets users build workflows to automate repetitive tasks.

Business-intelligence part of Amazon Quick: dashboards, charts and embedded analytics over a company's data sources, with natural-language what-if analysis and agent-assisted exploration.

An application for building and training machine learning models without writing code.

An agent that autonomously investigates operational incidents.

Research agent inside Amazon Quick: given a research objective it plans, searches the user's connected company data and the public web, and returns a customised report with citations to its sources.

Agentic AI for healthcare providers and health-tech developers: patient verification, appointment management, ambient clinical documentation, patient insights and medical coding, delivered inside Amazon Connect Customer for patient engagement and via an SDK at the point of care.

An AWS platform for building and running AI agents that automate browser-based UI workflows, billed per agent-hour of active work.

AWS's subscription AI work assistant combining chat-based research, business-intelligence dashboards and workflow automation, positioned as the successor to Amazon Q Business.

An application that creates automations from natural language or documentation using specialized AI agents.

A developer tool that identifies expensive lines of application code through runtime analysis.

An AWS coding assistant that generates, reviews, tests and autonomously modifies code inside IDEs and the CLI.

An AutoML component that automatically creates and selects machine learning models.

A component for preparing data, engineering features, and detecting data quality issues for machine learning.

A machine learning hub for evaluating, comparing, and selecting foundation models.

A serverless service for orchestrating and monitoring repeatable machine learning workflows.

A web interface for developing, training, evaluating, and deploying AI models.

Agentic AI development platform (IDE, CLI, web, mobile) that turns prompts into executable specs, validates code with property-based testing and runs parallel agents across large codebases.

A security platform that discovers, prioritizes, validates, and remediates software security risks.

Agentic-AI enterprise IT transformation workbench that accelerates cloud migration, application modernization (mainframe, Windows, custom code) and continuous tech-debt reduction.

An AI advertising platform that unifies omnichannel advertising and automates campaign execution and optimization.

Production AI-agent operational platform (framework- and model-agnostic) providing security controls, tool integration, debugging and evaluation for deployed agents.

Cloud contact-centre service, formerly simply 'Amazon Connect', now positioned as an agentic-AI customer-experience solution: AI agents and intelligent routing across voice, chat, email, SMS, web and WhatsApp, designed on a no-code canvas, with real-time performance tracking for agents and supervisors.

Amazon Nova Forge is a service for building custom frontier models using Nova and proprietary training data.

AWS's unified platform for building, training and deploying machine learning and generative AI models.

Single browser-based environment for data and AI development: find governed data across an organisation, then query it with SQL, work in serverless notebooks with a built-in AI agent, train models and build generative AI applications in shared projects.

Engineering-intelligence module that tracks DORA metrics, developer productivity and AI coding-tool spend together: which AI tools teams use, token consumption by developer, team, agent and model, AI-authored code and its effect on delivery.

AI Firewall blocks prompt injection, evasion, and malicious payloads targeting AI applications.

AI Posture discovers AI assets and agents and assesses their security posture.

Correlates deployment, feature flag, and infrastructure changes during incidents.

AI and Cloud Costs translates natural-language governance intent into cloud rules and remediates violations automatically.

Detects and blocks API attacks, bots and Layer 7 DDoS with behavioral AI trained on live traffic, covering credential stuffing, account takeover and business-logic abuse such as BOLA and mass assignment.

Tracks cloud and AI spending and automatically fixes waste.

Blocks prompt injection and unsafe model output.

Uses agents to triage and remediate software vulnerabilities.

Automates CI/CD and infrastructure-as-code delivery.

Governed AI agents defined in a committed file that run inside Harness pipelines on events such as CI failures and pull requests, with prebuilt agents for autofix, code review, code coverage, feature-flag cleanup, manifest remediation and IaCM remediation.

Reviews pull requests by grouping diffs by risk so the riskiest changes come first, enforcing required checks that cannot be bypassed, and citing delivery history and the knowledge graph for context.

Scores AI-agent responses for faithfulness, relevance, and task completion.

AI SAST scans agent-generated code and provides AI-generated fix suggestions.

AI SCA applies reachability analysis and EPSS scoring to open-source risk detection.

Monitors AI-agent LLM calls, tool calls, and decisions.

Creates intent-based tests and runs them within CI/CD pipelines with AI-assisted failure analysis.

AI-native software delivery platform: pipelines and canary deployments, AI security testing, runtime API and AI protection, cost management and policy governance, driven by AI agents that recommend while people decide.