Best Agentic AI Platforms (2026): Top 9 Compared

Agentforce is Salesforce's platform for building and running AI agents on the Salesforce CRM. Agents are built in Agentforce Builder with Prompt Builder and Agent Script, and they can be customer-facing, as in service and sales chat and voice, or employee-facing, inside the Sales, Service and Field Service applications and Slack.

Salesforce publishes more pricing detail than most vendors on this page, and it sells Agentforce in several ways. Salesforce Foundations gives a free starting point. Flex Credits cost $500 per 100,000 credits; an Agentforce action, such as updating a record, summarising a case or answering a product question, draws 20 credits, which works out at $0.10 an action, and a voice action draws 30. Customer-facing agents can instead be bought at $2 per conversation. For employee use, Agentforce add-ons at $125 per user a month, or $150 for Industries clouds, give unmetered usage to licensed users, and Max Edition starts at $550 per user a month with 2.75 million Flex Credits per org a year. A $5 per user a month Agentforce User License extends agents to employees outside the core CRM licences, with usage metered in Flex Credits.

The pricing page works through examples: a use case of two actions run 20 times a day costs about $120 a month in Flex Credits, and a three-action case run three times a day by 100 users for 20 days costs about $1,800. Usage can be paid as it is consumed or pre-purchased for the contract term. Salesforce notes that the page is provided for information and directs buyers to a sales representative for detailed pricing.

Copilot Studio is Microsoft's agent-building product. Users with a Microsoft 365 Copilot licence, at $30 per user a month paid yearly, can already build internal agents that work within Microsoft 365. The standalone Copilot Studio licence adds the ability to publish agents to external channels such as websites, apps and social platforms, to let users without a Copilot licence use those agents, and to build with the GitHub Copilot harness.

The comparison table on the pricing page lists creating custom agents, prebuilt agents and templates, preconfigured agent workflows, interactive voice response agents, multi-agent systems, co-authoring and reverting agents and flows to earlier versions. Microsoft says agents built in Copilot Studio can draw on Work IQ, which it describes as the intelligence layer behind Microsoft 365 Copilot.

Pricing is based on Copilot Credits, consumed whenever an agent completes an action or produces a response. Microsoft sells credits as tenant-wide capacity packs of 25,000 credits at $200 a month, as a pay-as-you-go meter linked to an Azure subscription, or as prepaid Copilot Credit Commit Units that save up to 20% and fall back to pay-as-you-go when exhausted. Microsoft states there is no feature difference between packs and the meter. New Azure accounts receive a $200 credit.

Google Cloud's agent builder product page now presents the Gemini platform, documented as the Gemini Enterprise Agent Platform. Google describes it as an open platform for technical teams to build, scale, govern and optimise enterprise agents grounded in company data.

Developers build agents with frameworks including Google's Agent Development Kit (ADK) or test models in Agent Studio. Model Garden offers more than 200 Google, third-party and open models, among them Google's latest Gemini models, Anthropic's Claude family and Gemma, with tuning options and a Model Evaluation service. Agents built on the platform can be registered, managed and governed in Gemini Enterprise, Google's employee-facing product, and Google Antigravity is offered as an application for steering and orchestrating multiple agents across a workflow. The platform also carries Google's machine learning tooling: notebooks integrated with BigQuery, training, prediction and MLOps pipelines.

Pricing follows Google Cloud's usage model. Agent infrastructure is metered on agent compute, memory and storage, with model tokens passed through, and Google advises contacting sales for estimates because costs vary by model and scale. Retrieval runs through Agent Search, billed at about $4.00 per 1,000 standard queries plus index storage. New customers receive $300 in credits for 90 days.

IBM watsonx Orchestrate is IBM's platform for building and deploying agents that automate work, connect systems and coordinate other agents. The trial, free for 30 days, includes agent building and orchestration, a chat interface, a tools and integrations catalogue, a control plane and evaluation and observability.

Paid plans are published as starting prices. Essentials, from $530 a month, adds workflow and document processing, an agents and tools catalogue, custom tool creation, core AI models and security and access control, for up to 4,000 monthly active users and 200,000 messages a month. Standard, from $6,360 a month, raises the ceilings to 40,000 monthly active users and 2,000,000 messages and adds ready-to-use domain agents. Premium, quoted by IBM, adds data isolation, a dedicated data space, end-to-end protection and a HIPAA-ready option for regulated environments.

The stated ceilings make watsonx Orchestrate one of the easier products on this page to size for a known user base. IBM states that watsonx Orchestrate was named a Leader in the IDC MarketScape for Worldwide Agentic AI Platform Software.

Sierra builds AI agents for customer experience. Its site positions the product for brands that want to go beyond customer service into revenue growth and customer lifetime value, with one agent deployed across chat, SMS, WhatsApp, email, voice and ChatGPT.

Agents can be built with or without engineering support. Sierra's Ghostwriter takes standard operating procedures, call transcripts, whiteboard photos, audio recordings or a goal written in plain English and builds a multilingual, multichannel agent with built-in guardrails. Updates can be generated from flagged issues and proactive insights, with each change visible for review before release. For improvement after launch, Sierra lists conversation analysis in the style of ChatGPT Deep Research, proactive flagging of conversations that need attention, multivariate tests of conversation design and a trace of every agent action, tool call, knowledge lookup and latency.

Sierra also describes memory that connects conversations and systems, personalised decisions bounded by guardrails, and next-best-action workflows triggered by real-world signals. Pricing is outcome-based, meaning the customer pays for results the agent delivers, and rates are not published.

ServiceNow AI Agents are built into the ServiceNow AI Platform and act on the workflows and data customers already run there across IT, HR, customer service, security and application development. ServiceNow describes agents as defined by a role written in natural language, tools such as flow actions, subflows, scripts and skills, and agentic workflows that state the business objective.

Customers can deploy prebuilt agents, which ServiceNow counts in the thousands, or build their own in natural language in AI Agent Studio. AI Agent Advisor surfaces and ranks candidate use cases and tests them against real data before launch. AI Agent Orchestrator coordinates teams of agents on multi-step goals. Action Fabric connects ServiceNow agents with third-party agents through the Agent2Agent (A2A) protocol and reaches external tools and data through a Model Context Protocol client. ServiceNow Otto routes requests on a user's behalf, and an Autonomous Workforce offering deploys AI specialists for whole jobs.

Governance sits in ServiceNow Super Intelligence Control Tower, which manages and monitors AI from any platform. ServiceNow cites a 2025 Gartner Critical Capabilities report for enterprise low-code application platforms in which it was assessed on the building and managing AI agents use case. Pricing is quoted.

Amazon Bedrock AgentCore is AWS's set of services for deploying and operating agents in production. Each service can be used alone or with the others. Runtime is a serverless environment for agents and tools, offered as microVMs with hardware-enforced isolation or as EC2 instances with a management fee. Browser and Code Interpreter give agents a managed web browser and code sandbox. Gateway gives agents secure access to tools, models and other agents, Identity manages agent access to AWS resources and third-party services, Memory stores short- and long-term context, Policy authorises agent actions, and Observability, Evaluations, Optimization and an Agent Registry cover monitoring, testing and cataloguing.

AWS publishes rates for every service. Runtime microVMs v1 cost $0.0895 per vCPU-hour and $0.00945 per GB-hour, billed per second with a 1-second minimum, and CPU usage scales to zero during I/O waits such as model responses or tool calls. Gateway costs $0.005 per 1,000 invocations, long-term memory $0.75 per 1,000 records a month, and policy checks $0.000025 per request. AWS's own example of one million Runtime v2 sessions comes to $6,703 a month.

There is no upfront commitment or minimum fee, and new AWS customers receive up to $200 in Free Tier credits. The rates listed are for AgentCore services; the pricing page does not list foundation model token prices, so model usage is a separate line in the budget.

WRITER is an enterprise generative AI platform that now positions itself around agentic work. Its interface, WRITER Agent, handles chat and automation in one place, and Playbooks package repeatable workflows that can be scheduled as routines and chained across teams. Agent Builder is listed as a feature on the plans page, and the WRITER Knowledge Graph grounds agents in company data through connectors.

Starter is the self-serve tier, with a 14-day free trial and no credit card. It covers up to 5 users, up to 5 Playbooks, up to 3 scheduled routines, one team Personality profile for brand voice and basic connectors with up to 3 active. It is sold as monthly or annual per-seat plans with fixed credit limits; the plans page does not show the seat price.

Enterprise is quoted and removes those limits: as many users, teams and free collaborators as needed, unrestricted playbooks and cross-team workflows, advanced orchestration with approvals, full Knowledge Graph capability with advanced and industry connectors, departmental brand profiles, interoperability with other systems and models, and granular agent governance, observability and audit. Enterprise also includes full access to an Agent Library of more than 100 prebuilt agents and Lite seats for new users.

UiPath, long known for robotic process automation, now presents itself as a business orchestration and automation platform where AI agents reason, robots act and people make judgment calls under one governed control plane. The platform page describes three layers: orchestration, execution and governance.

Orchestration runs through Maestro. Maestro BPMN handles fixed-path processes, Maestro Flow puts orchestration, agents, APIs and human steps on one canvas usable from VS Code and coding agents, and Maestro Case, in preview, tracks adaptive, exception-heavy work. Durable execution lets processes pause, resume and recover without losing state. The execution layer combines agents with RPA, API automation, intelligent document processing and human-in-the-loop steps, so agents can reach systems that have no API.

Governance includes real-time observability of every process and actor, controls that fix at design time whether a step is agentic, deterministic or human, an agent registry for UiPath and third-party agents, and business-transaction-level audit records. Basic starts at $25 a month for personal automations; agents are part of the quote-based Standard and Enterprise tiers.