Harness
Procurement partnerAbout
Harness is an AI-powered software delivery platform that automates the full software development lifecycle, from CI/CD pipelines and deployments to security testing, runtime protection, and cloud cost management. The platform uses AI agents to build, test, secure, and deliver code and AI agents at machine speed while enforcing governance, policy, and audit controls. Harness serves over 1,000 enterprise customers and processes more than 5.7 million deployments per month.
Details
VenSearch Intelligence
Ideal Customer
- Harness primarily targets large enterprises with complex, high-velocity software delivery needs — its 1,000+ named enterprise customers include global financial institutions, airlines, and large SaaS companies such as Workday.
- The platform offers tiered pricing ranging from free/open-source for individual developers to fully customized Enterprise plans with premium support, dedicated account managers, and modular capability selection for large organizations.
Key Differentiators
- Harness positions itself as the industry's first AI-native Software Delivery Platform, differentiating through a unified 'AI Fabric' that spans CI/CD, DevSecOps, API security, cost management, and agentic automation on a single governed platform — a breadth competitors address only through loose integrations.
- Its proprietary Software Delivery Knowledge Graph, combined with runtime data from Traceable and static analysis from Qwiet AI's Code Property Graph, enables precise vulnerability detection claimed to achieve a 97% true positive rate and 90% false positive reduction.
Industries Served
- Harness serves enterprises and startups across financial services, healthcare, retail, technology, and manufacturing.
- Named customer references include financial services firms such as Citibank, JPMorgan Chase, Morningstar, ADP, Experian, and Gentera; healthcare organizations like Siemens Healthineers and Vida Health; retail companies including Keller Williams and Sensormatic; and technology companies such as Workday, Twilio, and DigiCert.
Service Coverage
- Harness operates as a global software company headquartered in San Francisco, CA, with offices spanning 14 locations worldwide.
- As noted in TechCrunch's December 2025 coverage, the company has a significant presence in Europe, the UK, and India, with its largest development center outside the US located in Bengaluru, India, and a corporate office in Gurugram.
Partnerships
- Harness maintains strategic partnerships with all three major cloud hyperscalers — AWS, Microsoft Azure, and Google Cloud — including a 2026 Google Cloud Technology Partner of the Year Award in the Application Development – DevOps category.
- Ecosystem partners include ServiceNow, HashiCorp, and Datadog, while global system integrators such as Accenture, Deloitte, Wipro, Infosys, Cognizant, and Tech Mahindra are part of its 200+ member partner ecosystem.
Company Size & Ownership
- Harness was founded in 2017 by Jyoti Bansal (previously CEO of AppDynamics, acquired by Cisco for $3.7 billion) and Rishi Singh, and has grown to approximately 1,200–1,500 employees across 14 global offices as of 2026.
- The company reached $250M in annual recurring revenue in 2025, up from $80.4M in 2022, representing over 50% year-over-year growth.
Compliance & Certifications
- Harness holds SOC 2 Type II compliance and ISO 27001, ISO 27017, and ISO 27018 certifications, all of which are independently audited and renewed annually.
- The company is also listed on the FedRAMP Marketplace, is GDPR and CCPA compliant, and has achieved CSA STAR, DORA, and NIS2 compliance according to its Trust Center.
Compiled from public sources by VenSearch · Last researched October 14, 2026
Offerings
37 offeringsAgent DLC (Agent Development Lifecycle)
A development lifecycle framework for AI agents that runs agents through the same build, test, store, deploy, operate, and govern stages as software on Harness CI/CD pipelines. It provides artifact versioning for prompts, models, tools, and skills; AI Evals quality gates; governed deployments to Kubernetes and Amazon Bedrock AgentCore; AI Configs for runtime model swaps; AI Cost Management per agent; and an AI Asset Catalog with auto-discovery and audit trails.
AI & Cloud Costs
Bridges the visibility gap between AI and cloud spend with full cost attribution across AWS, Azure, GCP, and Kubernetes, including Kubernetes cost allocation down to individual pods and namespaces. Provides chargeback and showback reporting aligned to the FinOps FOCUS specification and AI-created cost perspectives described in plain language.
AI Code Review
An AI-powered code review tool that reads pull requests in the context of the organization's incident history and delivery context, not just the diff, to flag genuinely risky changes. It collapses mass renames and dependency bumps into summaries so risky changes surface first, and can block merges automatically based on configurable required checks.
AI DLC (AI-Driven Development Lifecycle)
A use case framework based on an AWS-originated methodology for applying AI across the whole software lifecycle beyond just code writing, covering build, test, secure, deliver, and operate phases on one governed platform. Harness provides the platform capabilities — CI, CD, security scanning, runtime protection, cost management, and the Knowledge Graph — to implement the full AI DLC without switching tools.
AI Evals
An evaluation system that scores AI agents and LLM-powered features on metrics including faithfulness, safety, and task completion both pre-deployment and against live production traffic to catch drift. Supports 50+ built-in eval metrics, plain-language test assertions without hand-written test scripts, and custom metrics, and integrates with the Agent DLC to provide quality gates on every agent or model change.
AI Firewall
Blocks AI-specific attacks including prompt injection and unsafe model output inline before they land, and detects multi-step attack chaining techniques that stitch together benign-looking requests into a real attack. Prevents lateral movement by stopping a compromised agent or tool call from reaching unauthorized systems.
AI Posture
Continuously discovers and inventories every AI agent, LLM, MCP, and AI component in the environment, including unregistered ones, and scores each for risk against the OWASP LLM and MCP Top 10. Automatically applies governance policies and runs prompt-injection and data-leakage tests against discovered AI assets.
AI SAST
A static application security testing tool that combines a deterministic code property graph with an AI reasoning layer to identify complex vulnerabilities that pattern-matching scanners miss, including in AI-generated code. It scores every finding for confidence of being a true positive and uses an agentic workflow to triage results and create pull requests with validated fixes.
AI SCA
A software composition analysis tool that uses EPSS scoring and reachability analysis to prioritize open source vulnerabilities to those that are actually reachable and exploitable in the codebase, reducing noise by up to 90%. An agentic workflow triages CVEs and proposes safe version bumps as ready-to-merge pull requests.
AI Test Automation
An AI-powered test automation capability that writes and self-heals functional tests automatically so test coverage keeps pace with AI-generated code. It generates test assertions based on intent rather than requiring hand-written scripts.
API Advanced Protection
Analyzes behavioral patterns across all API traffic to detect and block credential stuffing, abuse, and business-logic attacks in real time while reconstructing complete user sessions end to end for full context. Retains full-fidelity traffic data for deep forensic analysis and proof of policy enforcement.
API Posture
Automatically discovers every API in the environment — internal, external, and third-party — and scores each for exposure, sensitive data handling, and drift to provide complete visibility and prioritize remediation. Routes findings into developer tools so issues are fixed at the source.
Artifact Registry
A single registry for storing, versioning, and scanning container images, ML models, Helm charts, packages, and binaries with governed promotion and automatic provenance tracking. Enforces SLSA policies and blocks builds or deployments that use artifacts with known vulnerabilities.
AutoStopping
Intelligently detects idle non-production VMs and Kubernetes workloads and stops them automatically, restarting them on demand with zero disruption to eliminate waste from dev, staging, and test environments. Operates natively across both virtual machines and Kubernetes without requiring manual intervention.
Cluster Orchestrator
Right-sizes Kubernetes clusters using intelligent node autoscaling with spot instance orchestration and automatic bin packing to eliminate over-provisioned compute. Provides centralized governance across multiple Kubernetes environments.
Code Repository
A source code management system built to handle AI agent-generated code at scale, with indexing, diffing, reviews, and search that keep pace with thousands of concurrent pull requests and branches. Provides scoped RBAC and OPA policies defining exactly what repos and branches an agent can read, write, or merge, and exposes operations via MCP and CLI for agentic automation.
Commitment Orchestrator
Automates the full Reserved Instance and Savings Plan lifecycle across every cloud provider, including purchases, renewals, and coverage gap remediation, to maximize discounts and minimize risk. Goes beyond recommendations to actually execute commitment management automatically.
Continuous Delivery (Deployments)
Out-of-the-box canary and blue-green deployment strategies with AI-powered deployment verification that analyzes logging and monitoring data against baselines to decide if a rollback is needed. Supports GitOps at scale for managing thousands of applications across an Argo estate, and orchestrates releases spanning multiple services, tiers, and teams.
Continuous Integration (Builds)
An autonomous CI system that uses AI Test Intelligence to run only the tests affected by each code change, combined with aggressive caching to return build and test results in minutes. It automatically analyzes failures, traces root causes using pipeline git graph and log outputs, and generates validated code fixes for developer approval.
Cosmos Software Factory Agent
A new AI agent that takes engineering work from ticket to code, automating the process of translating tickets and requirements into working code changes. It represents Harness's most upstream extension into the software development lifecycle.
Cost Management Agent
An AI agent that provides full visibility, automated optimization, and governance over every dollar of cloud and AI spend by attributing costs to teams, workloads, models, and AI agents and detecting anomalies before they hit invoices. It automatically stops idle resources, rightsizes workloads, manages Reserved Instance and Savings Plan coverage, and enforces budget guardrails through natural-language policy generation.
Database DevOps
Automates database schema deployments with AI-generated migrations, OPA policy governance checks, restore point tagging, and lockstep rollout alongside application code in a single pipeline. Supports Flyway and Liquibase migration frameworks and generates rollback scripts for every change.
Developer Portal (IDP)
An internal developer portal that gives developers and AI agents a single source of context for services, prompts, and golden paths in one place. It supports self-service workflows and is listed as one of the Harness platform's additional products.
Engineering Efficiency
A product within the Cost Management Agent that measures team and delivery performance through DORA metrics, custom KPIs, AI-surfaced recommendations, and cost-per-PR and cost-per-ticket unit economics. It provides AI DLC Insights to quantify whether increased AI adoption is actually improving delivery speed.
Incidents
An incident management product offered as part of the Harness platform for tracking and responding to production incidents. It is listed as one of the additional products available beyond the core agent offerings.
Infrastructure Automation
Unifies governance, AI workflows, and infrastructure-as-code tools including Terraform, OpenTofu, Terragrunt, and Ansible to provision, configure, and deploy infrastructure from a single control plane. Provides drift detection, blast-radius risk assessment, and AI-powered remediation within approval guardrails governed by policy as code.
Mythos Readiness
A use case solution that enables security and engineering teams to respond to zero-days, AI-discovered vulnerabilities, and AI-powered attackers at machine speed by connecting zero-day detection, AI-powered SAST, triage and remediation, virtual patching, CI/CD, and runtime protection into a single workflow. It includes a Zero-Day Agent for agentic response workflows and virtual patching via API testing and WAAP to shield detected vulnerabilities in production while permanent fixes are developed.
Resilience Testing
A chaos engineering and resilience testing product that turns real production incidents into stress and chaos tests to prove systems hold up under failure conditions. It measures resilience scores and validates probe results including HTTP health checks, Prometheus metrics, and Kubernetes state.
Runtime Configuration
A runtime configuration management product that allows changing application configurations, including AI model swaps and prompt changes, at runtime without requiring a new code deployment. It is listed as one of the additional products available on the Harness platform.
Runtime Protection Agent
An AI agent that provides a single control plane for API posture management, advanced traffic protection, AI asset security, and an AI firewall to defend APIs, agents, and web applications from exploits, bots, DDoS, and AI-specific attacks. It autonomously discovers every API and AI asset in the environment, scores risk, enforces governance policies, and retains full-fidelity traffic data for 90 days for forensics.
Security Testing Agent
An AI agent that orchestrates application security testing across SAST, SCA, and supply chain security, using AI reasoning to surface true positives and eliminate false positives. It includes Triage, Remediation, and Zero-Day Agents that automatically prioritize findings by exploitability, generate validated fix pull requests, and respond to new zero-days across pipelines and deployed artifacts.
Security Testing Orchestration
Normalizes results from 40+ pre-built security scanner integrations into one governed workflow and unified risk view, enforcing governance by verifying every required security check actually ran. An agentic Remediation Agent triages findings across all checks, prioritizes by risk, and generates validated fixes automatically.
Software Delivery Agent
An AI agent that automates CI/CD and infrastructure-as-code delivery from code commit through production, following organizational policies and golden paths. It creates pipelines in minutes from conversation, performs AI-powered deployment verification with automatic rollback, and manages code, infrastructure, databases, artifacts, and code review in a single governed workflow.
Software Delivery Knowledge Graph
A continuously updated, relationship-aware semantic model of the entire delivery environment that maps pipeline history, deployment topology, security findings, cost signals, and third-party data across an organization. It provides the grounding context for all Harness AI agents, enabling multi-hop reasoning across dependencies, root cause analysis, safe rollback validation, and cost anomaly tracing.
Supply Chain Security
Provides end-to-end software supply chain protection by signing, attesting, and gating every artifact from build to production with SBOM policy enforcement that blocks builds using affected packages across the entire environment. Includes a Zero-Day Agent that identifies exposure to new zero-days across pipelines and deployed artifacts and generates validated fix pull requests.
Tokenomics
Tracks and optimizes AI token consumption across models, providers, and teams at the individual token, request, and workflow level, enabling unit economics analysis including cost-per-token, cost-per-inference, and cost-per-session. Allows teams to set token budgets, track consumption by team or workflow, and optimize spend toward business outcomes rather than raw usage.
Worker Agents
Specialized pipeline step agents that execute specific tasks such as code review, autofix, manifest remediation, feature flag cleanup, code coverage improvement, and Kubernetes manifest remediation as governed steps inside delivery pipelines. Each agent runs in a sandboxed pipeline step with read-only access except for its workspace, inheriting OPA policies, RBAC, and audit trails already protecting the pipelines.
Considering Harness?
Our team will work with you to determine if Harness is the right fit for your organization. From research and assessment through procurement negotiation and ongoing vendor management — we handle the entire process at no cost to you.