Best Gemini Enterprise Alternatives in 2026: 13 AI Agent Platforms for Teams Outside the Google Stack

Updated August 2026

If you're evaluating Gemini Enterprise, the read is usually the same: it's one of the most credible agent platforms available if your org is standardized on Google Workspace, BigQuery, and Google Cloud IAM, and a much harder sell if it isn't. This guide ranks 13 real alternatives, direct enterprise rivals grounded in Microsoft 365 or Salesforce, search-first platforms built for app sprawl, and open-source frameworks with no seat price at all, ordered by how directly each answers why teams actually go shopping.

Every price below comes from a vendor's own pricing or docs page, checked in August 2026, with monthly and annual rates called out separately since that's where most "wrong price" complaints start. Where a vendor doesn't publish a number, that's stated plainly and labeled reported, not guessed at. To be fair to Google upfront: Gemini Enterprise's grounding across Drive, Gmail, Calendar, and the open Google Search index is genuinely deep for a Workspace-native org, deeper than most of this list can manage outside its own ecosystem. What sends people shopping is everything wrapped around that grounding, not the grounding itself.

Key Facts

• Enterprises buying ready-made AI agent solutions instead of building their own rose from 53% in 2024 to 76% in 2025, per Menlo Ventures' State of Generative AI in the Enterprise.
• Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027, citing unclear business value and inadequate risk controls as the leading causes.
• 57% of organizations now have AI agents running in production, rising to 67% among enterprises with 10,000 or more employees, per LangChain's State of Agent Engineering survey of 1,340 practitioners.
• The average enterprise runs 897 applications and only 29% are integrated with each other, per MuleSoft's Connectivity Benchmark Report, one reason a platform's connector catalog often matters as much as its model.
• More than six trillion tokens are now processed monthly on Gemini models through the Agent Development Kit, according to Google Cloud's own Gemini Enterprise Agent Platform announcement.

Why Teams Look Past Gemini Enterprise

Google's pitch is fair on its own terms: one subscription spanning a chat front end, enterprise search, and a code-first Agent Development Kit (ADK), grounded in data most Workspace shops already trust. The four walls that send people elsewhere are less about capability and more about fit and cost predictability.

1. The organization isn't actually Google-standardized. Gemini Enterprise's value proposition runs through Workspace, BigQuery, and Google Cloud IAM grounding. If your CRM lives in Salesforce and your files live in SharePoint, that grounding is worth a lot less than the price assumes.
2. Per-seat licensing charges the same for light and heavy use. A provisioned seat costs the same whether someone opens the agent once a month or fifty times a day.
3. Pricing isn't reliably published. Google's dedicated pricing URL, cloud.google.com/gemini-enterprise/pricing, returns a 404 as of this writing.
4. Custom ADK agents bill separately on top. Building past no-code Agent Designer into the code-first ADK adds a second cost dimension beyond the seat.

What Gemini Enterprise's Own Editions Page Actually Shows

Source: Google's Gemini Enterprise editions documentation, verified August 2026. Every row routes to a sales conversation, not a number.

Google bills seat-based editions as subscriptions with quotas pooled per project and location, then layers on overage charges past that: storage and indexing overages run $5 per GiB per month, and other overages (Assistant queries, media generation, Deep Research, AI dev tools) follow separate Agent Platform rates, per Google's quotas-and-overages documentation. Custom ADK agents bill on top of whichever edition seat you're already paying for, a second meter most platforms here fold into one number.

The figures commonly cited, Business around $21/seat/month and Standard around $30/seat/month, both annual, trace to third-party reporting on Google's October 9, 2025 launch, not a live vendor page. Plus is reported as higher still and undisclosed. Treat all three as a starting point for a sales call, not a budget number. For the fuller head-to-head, see Copilot Studio vs Gemini Enterprise.

Quick Comparison Table

Sizing and Stage Fit

Platform fit changes with the organization's ability to support retrieval, technical orchestration, ecosystem-specific grounding, infrastructure control, and global governance.

1. Microsoft Copilot Studio: Metered Credits Instead of a Flat Seat for Everyone

Copilot Studio is the most direct inversion of Gemini Enterprise's pricing logic here: it meters what an agent does in Copilot Credits, pooled at the tenant level, instead of charging a flat rate per person. For an org with many employees touching an agent occasionally, that's the opposite of paying for idle seats. Grounding runs through SharePoint, Dataverse, and Microsoft Graph, with a low-code canvas where a maker mixes visual Topics and Power Fx expressions in one product.

Pricing: Copilot Studio user license is free. Prepaid Copilot Credit packs run $200 per 25,000 credits per month on an annual commitment (about $0.008 per credit), or pay-as-you-go through Azure at roughly $0.01 per credit with no commitment. Microsoft 365 Copilot, a separate seat license that unlocks Copilot Chat and the Standard harness in Copilot Studio, runs $30/user/month billed annually. Source: Microsoft's own Copilot Studio pricing page, verified August 2026.

Best for: Microsoft 365 and Azure-standardized organizations that want agents grounded in data they already store there, with a public rate card they can model before talking to sales. See best Copilot Studio alternatives for the full field this platform competes in.

2. Salesforce Agentforce: Deepest Grounding in Live CRM Data

Agentforce reasons directly over live Salesforce records, accounts, cases, opportunities, through its Atlas Reasoning Engine, with no integration layer between the agent and the data. For a Salesforce-standardized org, that's the same argument Gemini Enterprise makes for Workspace data, just pointed at CRM. The pricing story is messier than Copilot Studio's: Flex Credits are a published, working mechanism, but the Conversations and per-user paths that used to carry a flat number now route through a custom quote.

Pricing: Flex Credits cost $500 per 100,000 credits (one standard action equals 20 credits, about $0.10), confirmed via Salesforce's own pricing documentation. Enterprise Edition orgs get 100,000 free Flex Credits through Salesforce Foundations. Per-user editions and the Conversations model exist, but the current self-serve flow directs both to a sales conversation rather than a published rate, so treat any per-conversation figure elsewhere as unconfirmed for 2026.

Best for: Salesforce-standardized sales and service orgs automating work that already lives inside CRM records. See Agentforce vs Copilot Studio for the closest head-to-head, and best Agentforce alternatives for the full field.

3. ServiceNow AI Agents: Workflow and CMDB Grounding, Now With Moveworks Built In

ServiceNow's agentic stack, Agent Studio for building, an AI Agent Orchestrator for coordinating agents, and an AI Control Tower for governance, grounds agents in the CMDB and case data the Now Platform already holds. ServiceNow completed its Moveworks acquisition on December 15, 2025, folding that employee-facing search layer in, the rare entry here that absorbed a former competitor rather than just adding features.

Pricing: No public price list; ServiceNow directs buyers to a custom quote. Since April 2026, ServiceNow replaced its older ITSM tiers with three AI-native tiers, Foundation, Advanced, and Prime, with Prime the only tier carrying fully autonomous agents. Third-party estimates put core tiers around $90 to $200-plus per user per month (reported, unconfirmed by ServiceNow directly).

Best for: Enterprises already running ServiceNow for ITSM, HR, or customer service that want agents grounded in that workflow data. See AI agent compliance for weighing a still-maturing governance layer before rollout.

4. IBM watsonx Orchestrate: A Prebuilt Catalog With On-Premises as a Real Option

watsonx Orchestrate combines agent building, multi-agent orchestration, and a catalog of prebuilt agents for HR, procurement, sales, and IT, deployable on IBM Cloud, AWS, or fully on-premises. That last option is the real differentiator against Gemini Enterprise: if your org needs agent logic on infrastructure it controls outright, not a region selection inside someone else's cloud, IBM is one of the only names here that offers it.

Pricing: IBM's own watsonx pricing page returned a blocked response during verification, so treat the following as reported. Third-party reporting cites an Essentials plan from around $500 to $530/month and a Standard plan (adding workflow automation, document processing, and the prebuilt agent catalog) around $6,360/month (reported, unconfirmed by IBM directly).

Best for: IBM-standardized enterprises, or ones with strict deployment sovereignty needs a cloud-only platform can't satisfy.

5. Amazon Bedrock AgentCore: No Seat Price at All, Just Consumption

Bedrock AgentCore is AWS's managed agent infrastructure layer, Runtime, Gateway, Memory, and Identity, on top of Amazon Bedrock's model catalog: Anthropic, Meta, Amazon's own models, and others. It's the most complete answer here to the per-seat complaint, because there's no seat concept anywhere in it. Every component meters its own consumption, transparent in a way a flat per-seat number never is, but the total bill isn't a single line you can quote from memory.

Pricing: No flat agent fee. Runtime runs $0.0895/vCPU-hour plus $0.00945/GB-hour (or EC2 cost plus a 12% management fee, 7.8% for GPU). Gateway runs $0.005 per 1,000 API invocations, $0.025 per 1,000 search invocations, and $0.02 per 100 tools indexed monthly. Memory runs $0.25 per 1,000 short-term events, $0.75 per 1,000 long-term records stored (or $0.25 self-managed), and $0.50 per 1,000 retrievals. Identity runs $0.010 per 1,000 token or API key requests, free via Runtime or Gateway. Source: AWS's Bedrock AgentCore pricing page, verified August 2026.

Best for: AWS-standardized engineering teams wanting full model choice and infrastructure control over a configured builder. See AI agent cost optimization for modeling that before committing.

6. Glean: Permission-Aware Search Across Every App, Not Just Google's

Glean's pitch is the closest thing to Gemini Enterprise's search-grounding argument turned vendor-agnostic: instead of grounding agents in one ecosystem, Glean indexes across every connected app an enterprise runs, then builds Glean Agents on that same permission-aware index. For an org whose data doesn't live mostly in Google, or mostly anywhere in particular, that cross-app index does the job Workspace-plus-Search grounding can't.

Pricing: No self-serve pricing is published; Glean's own pricing page confirms this and routes every visitor to a demo request. Third-party reporting cites a base seat fee around $45 to $50/user/month plus an AI add-on around $15/user/month, with enterprise contracts commonly carrying a roughly 100-seat (about $60,000/year) minimum (reported, unconfirmed by Glean directly).

Best for: Enterprises with real app sprawl that want one search and agent layer spanning everything, rather than one ecosystem's native option.

7. Moveworks (a ServiceNow Company): The Employee-Facing Assistant Google Doesn't Quite Match

Moveworks built its name on front-end AI assistance and enterprise search for employee IT, HR, and facilities questions, powered by what it calls a Reasoning Engine, well before ServiceNow's acquisition closed on December 15, 2025. If what your team wanted from Gemini Enterprise was a chat-style assistant employees ask questions in, not a build platform, Moveworks was purpose-built for that narrower job, now inside the broader ServiceNow AI Platform.

Pricing: No public price list; quote-only, billed per employee per year. Reported figures range from roughly $50,000 to $100,000/year at 500 to 1,000 employees up to $200,000-plus/year above 5,000 employees, median around $130,000/year (reported, aggregated third-party data, unconfirmed by Moveworks directly).

Best for: Enterprises wanting a dedicated employee IT/HR assistant, especially ones already moving toward ServiceNow as their broader AI platform of record.

8. Writer: A Model-Agnostic Governance Layer for Regulated Content

Writer pairs its own Palmyra models with third-party model choice, wrapped in brand, style, and compliance guardrails aimed at regulated industries, financial services, healthcare, insurance, where generated content and agent output both need a governed layer, not just a capable model. That's a different argument from Gemini Enterprise's ecosystem grounding: Writer competes on control over what an agent is allowed to say and cite, not which suite it's grounded in.

Pricing: Writer's own pricing pages returned a bot-protection block on every verification attempt, so nothing below is vendor-confirmed. Per Vendr's aggregated buyer data, the Starter tier is reported at $39/seat/month billed monthly or $29/seat/month billed annually, capped around five seats, with Enterprise custom-quoted and mid-market contracts commonly landing between $75,000 and $250,000 a year (all reported, not confirmed by Writer).

Best for: Regulated enterprises that want model flexibility alongside built-in compliance guardrails for both content and agent output, more than they want ecosystem grounding specifically.

9. Stack AI: A Retrieval-Native Builder for Internal Knowledge Work

Stack AI's core strength is grounding agents in a company's own documents and data through native retrieval-augmented generation, aimed at internal knowledge work rather than general task delegation or CRM automation. Its pricing page is unusually blunt about where the self-serve option ends: there's a free tier, and then there's Enterprise, with nothing published in between.

Pricing: Free ($0, 500 runs/month, 2 projects, 1 seat, community Discord support). Enterprise custom (dedicated infrastructure, dedicated solution engineers, on-premises and VPC deployment options, access control, SSO, SOC 2/HIPAA/GDPR compliance). Source: Stack AI's own pricing page, verified August 2026.

Best for: Teams whose actual use case is internal knowledge retrieval, and who are prepared to go straight to an Enterprise conversation once the free tier is outgrown.

10. Dust: Seat-Bundled Credits for Company-Wide Knowledge Agents

Dust's model is seat-based rather than employee-based in the Gemini Enterprise sense: every person gets a seat with a bundled monthly credit budget, drawing on 20-plus models from OpenAI, Anthropic, Google, Mistral, and DeepSeek. The pitch is giving a whole company access to grounded agents, not delegating one job to one bot, with a credit meter that at least tells you what you're spending, unlike a flat seat.

Pricing: Free ($0, 500 credits, lifetime allotment). Pro $30/month, or $24/month billed annually (8,000 credits/month). Max $150/month, or $120/month billed annually (40,000 credits/month). The self-serve Business plan caps at 100 seats, 3 connectors, and 5 Spaces; past that, it's Enterprise custom. Source: dust.tt/home/pricing, cross-checked against third-party trackers citing the same figures in 2026.

Best for: Companies that want every employee equipped with grounded agents drawing on the same knowledge base, with credit usage that's at least visible instead of a flat, opaque seat charge. See best Lindy alternatives for a wider field of comparably framed platforms.

11. Zapier Agents: The Widest App Catalog to Hand an Agent as Tools

Zapier's bet is that the fastest way to a working agent is giving it access to the automation platform teams already run. Zapier Agents sits atop core Zapier, letting an agent reason over a task and call any of its 9,000-plus app integrations as a tool, rather than follow one fixed sequence. Where Gemini Enterprise lists about 135 third-party connectors in Google's own connector documentation, 18 generally available and 117 still in public preview, this is a different order of magnitude, at a fraction of an enterprise seat price.

Pricing: Zapier Agents: Free (400 agent activities/month). Pro $400/year, about $33/month (1,500 activities/month). Enterprise custom. Core Zapier, which Agents runs on top of: Free (100 tasks/month), Professional from $19.99/month annual, Team from $69/month annual. Source: zapier.com/pricing, verified August 2026.

Best for: Teams already automating on Zapier that need an agent to reach into an app catalog wider than any ecosystem platform here. See Lindy vs Zapier Agents for how it stacks up against a similarly framed builder.

12. n8n: Self-Hosted Control With Unlimited Free Executions

n8n's philosophy is that automation infrastructure should be something you own outright, not rent indefinitely. Every plan, including the free self-hosted Community edition, ships the same AI Agent node, built on LangChain primitives, wired up visually or extended with raw JavaScript. For a team leaving Gemini Enterprise over data residency or wanting infrastructure it fully controls, n8n is usually the first stop, and the only entry here where the free tier has no execution cap at all.

Pricing: Community edition free, self-hosted, unlimited executions. Cloud Starter about €20/month annual (roughly $22 USD; 2,500 executions/month, 2,300 AI credits/month, 5 concurrent executions). Cloud Pro about €50/month annual (roughly $54 USD; 10,000 executions/month, up to 13,700 AI credits/month, 20 concurrent executions). Business about €667/month annual (roughly $720 USD), 40,000 executions/month, self-hosted option available with SSO/SAML. Enterprise custom. Source: n8n.io/pricing, verified August 2026.

Best for: Technical teams and regulated industries that want agent workflows running on infrastructure they fully own, without a per-seat charge anywhere in the model.

13. LangGraph: Zero Seat Price, Full Engineering Control

LangGraph is the pure escape hatch here: a free, open-source graph-based framework from LangChain for building stateful, multi-agent workflows in Python or JavaScript. There's no seat price, no credit pool, and no vendor relationship required to run it, only the engineering time to build and the model API calls the code makes. For a team that concluded a managed, per-seat platform like Gemini Enterprise was never going to fit its actual build, this is where that conclusion leads.

Pricing: The LangGraph framework itself is free and open source, no license fee. Managed deployment and observability run through LangSmith: Developer tier free ($0/seat, up to 5,000 base traces/month, 1 seat). Plus tier $39/seat/month (unlimited seats, up to 10,000 base traces/month, one free small serverless deployment included). Enterprise custom, with self-hosted and hybrid options, SSO, and RBAC. Node executions beyond the included allowance are billed separately, reported around $0.001 each. Source: LangChain's own pricing page, verified August 2026.

Best for: Engineering teams that have ruled out a managed, per-seat platform and want to own the model choice and cost, with no credit meter anywhere. See best open-source AI agent frameworks and best AI agent observability tools for LangSmith-style tracing.

How to Choose: Decision Framework

For a broader checklist beyond just Gemini Enterprise switches, see how to choose an AI agent platform.

What to Do Next

Start with your actual system of record, not a preference: if most of the data an agent needs already lives in Microsoft 365 or Salesforce, Copilot Studio or Agentforce beats a Google-grounded platform on integration speed alone, whatever the price difference works out to. If nothing dominates and your apps are genuinely scattered, weigh Glean's cross-app search against building on Bedrock AgentCore or LangGraph instead of forcing a fit that isn't there. For every quote-only vendor here, ServiceNow, watsonx Orchestrate, Glean, Moveworks, and Writer, get the real number in writing before budgeting against a reported figure, then run a two-week pilot on one bounded job with your top two picks and measure whether it finishes correctly without a human rescuing it at every step.