Agentic AI moved from research labs to production lines, and enterprise software is being rebuilt around the architecture. The agentic AI companies actually shipping at enterprise scale today are the ones combining foundational model access with deep workflow integration, and Gartner predicts that 40% of enterprise applications will embed task-specific AI agents by the end of 2026, up from less than 5% in 2025. We've tested most of the platforms below across client deployments at RZLT and shortlisted the twelve doing the most defensible work in the category.

Anthropic: Foundational model layer powering production agents

Anthropic builds Claude, the foundation model powering an outsized share of production agent systems, and the company's push into agentic infrastructure through Claude Code, Skills, and MCP has made it the default choice for enterprises building custom agents. Claude is now the engine behind agent products from Cursor, Vercel, and most of the AEO platform stack. Anthropic's edge is owning both the model and the agent tooling layer, which lets enterprises build deeply integrated systems without stitching together six vendors.

OpenAI: The default consumer interface for agentic capabilities

OpenAI ships ChatGPT, GPT-4, and an expanding agent platform that includes the Responses API, Agents SDK, and a custom GPT marketplace where enterprises deploy task-specific agents. The reach is unmatched at 900 million weekly users, and the platform underpins agent products across most enterprise stacks. OpenAI's edge is platform breadth: most third-party agent builders default to GPT-4 first, and enterprise customers tend to follow.

Salesforce Agentforce: Embedded agents inside the CRM stack

Salesforce's Agentforce platform lets enterprises build and deploy AI agents directly inside the CRM stack, with prebuilt agents for sales, service, marketing, and commerce. The platform crossed thousands of production deployments through 2025, with companies like FedEx and Wiley running customer service agents that resolve cases without escalation. Agentforce sits inside the data layer most enterprises already trust, which lowers the integration friction that kills standalone agent rollouts.

ServiceNow: Operational scale across IT, HR, and customer service

ServiceNow embeds agents directly into the IT, HR, and customer service workflows enterprises already run on the platform. Nearly 1,000 organizations have deployed agentic AI with ServiceNow, with AstraZeneca saving 30,000 hours annually on research workflows and Bell Canada optimizing over 2 million service jobs through AI-driven scheduling. The strength is operational scale: agents inherit the system's existing data, permissions, and approval flows rather than requiring a separate orchestration layer.

Microsoft Copilot Studio: Agents inside the Microsoft 365 workflow

Microsoft Copilot Studio lets enterprises build, customize, and deploy agents across Microsoft 365, Teams, and Dynamics, with underlying flexibility across GPT-4, Claude (via Azure), and Microsoft's own models. The reach is structural, since most enterprise knowledge workers already operate in Office and Teams, so Copilot agents land inside the existing workflow without forcing users to switch tools. Microsoft's edge is distribution paired with deep enterprise governance.

Sierra: Customer service agents built for brand depth

Sierra builds agents purpose-designed for customer service, focused on the long-context conversational fidelity beyond what traditional chatbots can sustain. The company emphasizes brand-specific agents that hold context across multi-turn conversations and integrate deeply with existing CRM and helpdesk systems. Sierra's customer list (including ADT, SiriusXM, and OluKai) reflects a deliberate focus on consumer brands where conversation quality directly affects retention and CSAT.

Aisera: Multi-agent orchestration for enterprise IT and HR

Aisera focuses on enterprise IT, HR, and customer service automation through a multi-agent orchestration platform that handles ticket resolution, employee self-service, and back-office workflows. The company has been named a Gartner Visionary in the Magic Quadrant for AI Applications in ITSM and a Leader in the IDC MarketScape for Conversational AI. Production deployments at NJ Transit, OmniTRAX, and Big 5 Sporting Goods demonstrate the platform's ability to handle high-volume, governed workflows at scale.

Cursor: The default agentic IDE for engineering teams

Cursor is the coding agent that's become the default IDE for AI-native developers, with autonomous code generation, multi-file editing, and integrated agent loops that ship working code from natural language prompts. Anysphere (Cursor's parent company) is one of the fastest-growing developer tools in history, with adoption spreading rapidly across both startups and enterprise engineering orgs. The product reshapes how engineering teams work, and the same pattern is showing up across marketing, ops, and finance tooling.

Glean: Agents on top of a unified enterprise knowledge graph

Glean is the AI-for-work platform that unifies enterprise knowledge across emails, docs, chats, and apps, then layers agents on top of that unified knowledge layer. The platform handles cross-system search, summarization, and task automation, with an enterprise customer list that includes Pinterest, Sony, Reddit, and Confluent. The differentiator is the underlying knowledge graph, which gives Glean's agents context that standalone agents typically lack.

Gong: Revenue AI agents for sales and GTM teams

Gong's Revenue AI platform expanded to 18 specialized agents purpose-built for sales and revenue teams, analyzing call recordings, emails, and meetings to surface deal risk, flag competitive threats, and recommend next steps. The upcoming Orchestrate product lets revenue leaders define sales plays once and automatically guide teams through execution, measuring adherence in real time. Gong's strength is the proprietary conversation data set, which gives its agents context that no foundation model alone can match.

Jasper: The agent workspace built for marketing teams

Jasper is the agent workspace built specifically for marketing teams, with 100+ specialized agents and connected content pipelines that turn campaign briefs into live, on-brand assets. The platform handles content production, brand governance, localization, and channel-specific optimization without requiring custom prompt engineering. Jasper's edge is depth in the marketing workflow, which makes it a different category of tool than the standalone LLMs marketers were using two years ago.

Kore.ai: Multi-agent orchestration with enterprise-grade governance

Kore.ai delivers a multi-agent orchestration platform that's been a Gartner Magic Quadrant Leader for Conversational AI for three consecutive years, with cloud and model-agnostic architecture and a strong AI governance dashboard. The platform lets enterprises deploy thousands of governed agents across customer service, employee experience, and search workflows, with full observability and role-based access controls. Kore.ai is the go-to for enterprises that need scale, governance, and audit trails alongside agent capabilities.

Where to Start

If you're starting from scratch and need a foundational model with deep agent tooling, Anthropic and OpenAI are the obvious entry points. If your priority is operationalizing agents inside an existing enterprise stack, Salesforce, ServiceNow, or Microsoft will absorb the most workflow without forcing a re-platforming. For function-specific lifts, the vertical specialists (Sierra for CS, Gong for revenue, Jasper for marketing, Cursor for engineering) deliver faster ROI than horizontal platforms. OurAgentic SEO Playbook covers how the same agentic architecture applies to the SEO and content workflow specifically.