# Alternatives to Zendesk AI agents > Source: https://theagentsindex.com/zendesk-ai-agents/alternatives (current datasheets, evidence-ranked) Candidates share the baseline category or are previously researched peers. Requirements, preserved strengths, explicit trade-offs and research coverage decide the order; paid tier does not. ## Shortlist ### 1. Fin Intercom's customer agent that resolves support conversations across chat, email, voice and social channels. **Research coverage:** 35/35 criteria **Where it improves on Zendesk AI agents:** - [MCP server: yes — MCP runs both ways: Fin reaches business tools through MCP connectors, and an Intercom MCP server lets outside AI systems read the conversation data Fin produces.](https://fin.ai/integrations) - [Audit log: yes — Administrative action is recorded and readable over the REST API — logins, permission and role changes, SCIM provisioning, security settings and data exports — though these are workspace admin events rather than a log of Fin's own answers.](https://developers.intercom.com/docs/references/2.6/rest-api/admins/list-all-activity-logs) - [Opt out of training: yes — Fine-tuning on your anonymised data can be switched off at any time with deletion inside 30 days, and workspaces with a BAA or hosted in the EU or AU are excluded automatically.](https://www.intercom.com/security) **Trade-offs against Zendesk AI agents:** - [GPT: partial — OpenAI models are part of the same automatic failover pool as Anthropic and Google, so GPT is used by the platform but is not a model the customer chooses or configures on any tier.](https://fin.ai/trust-reliability) - [API access: partial — A documented Fin Agent API drives Fin from your own stack over webhooks or SSE, but access is granted through a request form and the orchestration endpoints are published only on the Preview API version.](https://developers.intercom.com/docs/guides/fin-agent-api) - [Bring your own key: no — The model that answers is Intercom's own and the providers behind it are swapped automatically, so a buyer brings nothing: no page offers your own API keys, your own model weights or your own cloud, and region choice is the only infrastructure control published.](https://fin.ai/cx-models) [View Fin](https://theagentsindex.com/intercom-fin) ### 2. IrisAgent AI support agents that resolve chat, email, voice and text inside your existing helpdesk. **Research coverage:** 33/35 criteria **Where it improves on Zendesk AI agents:** - [Claude: yes — Anthropic models are scored inside the production IrisAgent stack on its own leaderboard, and the vendor says production routing follows that board.](https://irisagent.com/support-model-arena/) - [Open models: partial — Open models are offered for the private, self-hosted deployment where weights run inside the buyer's own environment; the shared SaaS names only in-house or OpenAI-based models.](https://irisagent.com/on-premise-ai/) - [Model choice: partial — The vendor calls itself model-agnostic but picks the defaults from its own leaderboard and routes on the buyer's behalf, so model selection is a vendor-configured choice rather than a self-serve setting.](https://irisagent.com/support-model-arena/) **Trade-offs against Zendesk AI agents:** - [Agent permissions: partial — Autonomy is configurable per trigger: the same AI answer can be sent straight to the customer or posted as an internal note an agent approves, and enabling deflection everywhere is restricted to admins.](https://docs.irisagent.com/deploying-irisagent/Tickets) - [Seat model: no — The published plans meter query volume rather than agent seats, and the managed line states outright that there are no per-seat fees, so no seat floor or ceiling is published.](https://irisagent.com/managed-resolution/) - [Admin controls: partial — Admins control whether AI answers reach customers at all and scope them with trigger conditions, and role-based access is described for the private deployment; no general policy-engine documentation was found.](https://docs.irisagent.com/deploying-irisagent/Tickets) [View IrisAgent](https://theagentsindex.com/irisagent) ### 3. Maven AGI Enterprise AI agent platform that resolves customer conversations across chat, email, voice and internal tools. **Research coverage:** 33/35 criteria **Where it improves on Zendesk AI agents:** - [Claude: yes — The Master Services Agreement names Anthropic, alongside OpenAI, as one of exactly two LLM providers generating output today, and lists it as a contracted sub-processor rather than an optional integration.](https://www.mavenagi.com/legal/msa) - [Model choice: partial — Maven claims its own architecture is LLM-portable on the platform page, but the contract shows the vendor picks the models and may change them on notice; no buyer-facing model selector is published anywhere.](https://www.mavenagi.com/product/agent-platform) - [MCP server: yes — Maven supports Model Context Protocol as a client: a team pastes an MCP server URL and configures access in the UI, though the vendor routes activation through your assigned CX manager rather than open self-serve setup.](https://www.mavenagi.com/resources/model-context-protocol) **Trade-offs against Zendesk AI agents:** - [How it meters: partial — The vendor names resolution volume as what the price scales with, but publishes no per-resolution rate; the contract meters against a subscription usage allowance with overage priced privately in the order form.](https://aws.amazon.com/marketplace/pp/prodview-l2djyrnxnfffq) - [Free tier: no — Every call to action on the site is a booked demo, and onboarding is described as a dedicated implementation team explicitly instead of self-serve setup, so there is no way in without a sales conversation.](https://www.mavenagi.com/explore/ai-agents-roi-calculator) - [Bring your own key: no — Inference is Maven's to arrange: the contract names the two LLM providers it uses and reserves the right to change them on notice, with no provision for customer-supplied keys, accounts or cloud.](https://www.mavenagi.com/legal/msa) [View Maven AGI](https://theagentsindex.com/maven-agi) ### 4. Sierra Enterprise platform for customer-service AI agents across voice, chat, email and messaging, priced by outcome. **Research coverage:** 32/35 criteria **Where it improves on Zendesk AI agents:** - [Open models: partial — Sierra states it blends open-weight models into its constellation, but the buyer neither picks nor supplies them and no model names are published.](https://sierra.ai/product/trust-and-reliability) - [Opt out of training: yes — Sierra states customer data is never used to train models at all, so there is no opt-out to negotiate per tier.](https://sierra.ai/product/agent-sdk) **Trade-offs against Zendesk AI agents:** - [GPT: partial — OpenAI is listed as an AI-services subprocessor, so GPT models are used under the hood, chosen by Sierra's router rather than by the buyer.](https://trust.sierra.ai/subprocessors) - [Free tier: no — No free tier, trial or self-serve signup: sign-in requires a company deployment that already exists, and every call to action is a contact form.](https://sierra.ai/login) - [Bring your own key: no — Sierra supplies and routes the inference itself through its own model subprocessors; no bring-your-own-key, own-model or own-cloud option is published.](https://sierra.ai/product/trust-and-reliability) [View Sierra](https://theagentsindex.com/sierra) ### 5. Decagon Enterprise platform for building and running AI customer-support agents across chat, voice and email. **Research coverage:** 31/35 criteria **Where it improves on Zendesk AI agents:** - [Self-hosted: partial — Decagon claims headless deployment inside your own infrastructure, but publishes no on-premise or self-hosted edition and runs its platform on its own cloud subprocessors.](https://decagon.ai/vs/sierra) - [Opt out of training: yes — Stronger than an opt-out: zero-day retention is enforced with every AI provider by default, so conversation data is not stored or trained on.](https://decagon.ai/security) **Trade-offs against Zendesk AI agents:** - [GPT: partial — OpenAI is named as an AI provider and appears as an LLM subprocessor on the trust centre, yet no page offers the customer a choice of GPT.](https://decagon.ai/security) - [Free tier: no — Every entry path on the site is a sales demo: there is no signup, no trial and no free plan, and each engagement ships with a forward-deployed team.](https://decagon.ai/vs/sierra) - [API access: partial — Agent logic and tools are Git-backed and written in Python and the platform deploys headlessly, but the API reference sits behind a login so the public surface cannot be checked.](https://decagon.ai/vs/sierra) [View Decagon](https://theagentsindex.com/decagon) ### 6. Ada Enterprise AI customer service agents for voice, messaging and email, with tool-based actions. **Research coverage:** 35/35 criteria **Where it improves on Zendesk AI agents:** - [Claude: yes — Ada's trust FAQ names Anthropic among the model vendors in the portfolio behind its agents; the vendor does not publish which Claude model or version runs, and customers do not select it.](https://www.ada.cx/platform/trust/) - [Open models: partial — Ada internally hosts open-source LLMs for contextual understanding only; reply generation runs on the commercial providers and the customer selects neither.](https://security.ada.cx/) - [Open source: partial — Only the client-side chat UI library is distributed publicly on npm as @ada-cx/lovelace; the platform and Reasoning Engine are hosted with no published source.](https://docs.ada.cx/lovelace/overview) **Trade-offs against Zendesk AI agents:** - [Agent permissions: partial — The agent acts on its own inside a conversation but only through tools an admin has switched on, and Ada tells customers to put an explicit confirmation step in front of anything that writes, so write authority is deliberately gated rather than open.](https://www.ada.cx/platform/ada-computer/) - [Free tier: no — There is no self-serve entry: /pricing redirects to a demo booking form, no plan or sign-up is published, and the pricing FAQ says every end-user conversation is billed. Evaluation runs through a sales conversation.](https://www.ada.cx/platform/) - [Bring your own key: no — Inference runs on Ada's own provider agreements; no bring-your-own-key or own-cloud path exists. You do supply credentials for your own systems when connecting API and MCP tools.](https://www.ada.cx/platform/trust) [View Ada](https://theagentsindex.com/ada) ## Method Unknown data is never treated as a benefit or a trade-off. Featured placement is labelled but cannot alter recommendation order.