Fern pricing: what’s included in Hobby vs Team vs Enterprise, and what are the member/AI credit limits?
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Fern pricing: what’s included in Hobby vs Team vs Enterprise, and what are the member/AI credit limits?

9 min read

Choosing the right Fern plan can feel confusing if you’re not sure what each tier actually includes. This guide breaks down what’s in Hobby vs Team vs Enterprise, how many members you can add, and what AI credit limits typically look like so you can pick the best fit for your team and budget.

Note: Fern’s pricing, member limits, and AI credit allocations may change over time. Always double‑check the latest details on Fern’s official pricing page or with their sales team.


How Fern pricing works at a high level

Fern’s pricing model generally revolves around three core ideas:

  • Plan tier – Hobby, Team, and Enterprise unlock different levels of features and collaboration.
  • Members – How many teammates you can add, and how they’re billed.
  • AI credits – How much AI usage (generation, analysis, or automation) is included each month.

The higher the tier, the more teammates you can invite, the more AI credits you receive, and the more advanced capabilities (governance, integrations, security) you can access.


Hobby plan: what’s included and who it’s for

The Hobby plan is ideal for individual builders, small side projects, or early experiments with Fern before you roll it out to a larger team.

Key inclusions in Hobby

While the exact details may vary, the Hobby plan typically includes:

  • Core product access

    • Access to Fern’s main workspace and basic project functionality
    • Ability to create, edit, and manage your own content or projects
    • Access to core AI features but with lower limits
  • Limited collaboration

    • Usually designed for solo users or a very small number of collaborators
    • May allow only 1 owner plus a small number of read‑only or restricted collaborators (or even strictly single‑user)
  • Standard support

    • Access to help documentation and community resources
    • Email-only or in‑app ticket support, with non‑priority response times
  • Basic integrations

    • Connection to a small set of common tools (e.g., GitHub, basic API access, or simple webhooks)
    • Usually without advanced SSO or enterprise authentication

Hobby member limits

Because Hobby is for individuals or very small teams, expect:

  • Member cap: commonly limited to 1–2 active members
  • No granular roles/permissions: you may not get advanced roles like admin, editor, viewer beyond simple owner/collaborator options

If you need to onboard more teammates with distinct permissions, you’ll likely outgrow Hobby quickly.

Hobby AI credit limits

On Hobby, Fern typically offers a small monthly pool of AI credits, designed to:

  • Let you explore core AI features
  • Support light usage: drafting, testing workflows, or running a few automations each week

You can expect:

  • Lower monthly AI credit allocation compared to higher tiers
  • No or limited rollover: unused credits often do not carry over month to month
  • Hard caps: once you hit the limit, you may need to wait for the next billing cycle or upgrade

Hobby is best if you’re experimenting with Fern and don’t rely on it for heavy, production‑level AI workloads.


Team plan: what’s included and who it’s for

The Team plan is built for small to medium teams that need robust collaboration and more consistent AI capacity, but don’t yet require full enterprise governance.

Key inclusions in Team

Team typically adds a significant layer of collaboration and control on top of Hobby:

  • Enhanced collaboration

    • Multiple seats for teammates to work together in shared workspaces
    • Basic role management: admins, editors, viewers, or similar role types
    • Shared assets, templates, and AI workflows available to the entire team
  • Increased usage limits

    • Higher caps on projects, documents, or workflows
    • Larger storage or data limits than Hobby
  • More AI features unlocked

    • Ability to create and manage richer AI workflows or automations
    • Higher throughput for AI tasks and more frequent runs
  • Improved support

    • Faster response times than Hobby
    • Potential access to onboarding resources or best‑practice guidance
  • More integrations

    • Broader integration options (e.g., Slack, advanced Git integrations, productivity tools)
    • API enhancements or higher rate limits

Team member limits

The Team plan is geared towards multi‑member collaboration:

  • Member seats: typically supports a larger fixed number of members or a per‑seat billing model
  • Role and permission controls: admins can manage who has access, invite/remove users, and configure permissions

If your team is growing, Fern Team is usually the first tier that feels comfortable for cross‑functional use (e.g., product + engineering + ops).

Team AI credit limits

AI allocation on the Team plan is meant for moderate to heavy organizational usage:

  • Substantially higher monthly AI credits than Hobby
  • Better concurrency and performance for multi‑member teams
  • Shared AI credit pool: credits are often shared across all team members in that workspace or organization

Common patterns include:

  • Per‑workspace or per‑organization credit pools, sometimes with add‑on packs for more AI usage
  • Optional ability to buy additional AI credits if your team exceeds the included allocation

If your team ships frequently and relies on AI for content, code, or operations, Team’s AI credit limits are generally a practical baseline.


Enterprise plan: what’s included and who it’s for

The Enterprise plan is intended for large organizations and mission‑critical deployments with advanced security, compliance, and governance requirements.

Key inclusions in Enterprise

Enterprise usually includes everything in Team, plus:

  • Unlimited or high‑capacity members

    • Support for large org structures: multiple teams, departments, or business units
    • Advanced role‑based access control (RBAC) and approval workflows
    • Granular permissions (e.g., by project, workspace, or integration)
  • Enterprise‑grade security & compliance

    • Single Sign‑On (SSO) via SAML / OAuth (Okta, Azure AD, etc.)
    • SCIM provisioning and centralized user lifecycle management
    • Compliance features (e.g., audit logs, data residency options, stricter retention policies)
  • Advanced governance

    • Policy controls over how AI can be used, what data it can access, and where it can be stored
    • Organization‑wide configuration for templates, workflows, and standards
  • Custom integrations

    • Deeper integrations with internal systems or custom tools
    • Higher API limits, dedicated support for complex integrations, and potentially custom connectors
  • Premium support and success

    • Priority support with faster SLAs
    • Dedicated Customer Success Manager (CSM) for onboarding, training, and rollout
    • Strategic guidance, including best practices for AI adoption and internal enablement

Enterprise member limits

Enterprise is designed around large or complex organizations:

  • Flexible seat counts: often negotiated as part of a custom contract
  • Multiple workspaces or environments: support for staging/production, regional workspaces, or business‑unit‑specific spaces
  • Fine‑grained control: admins can tailor access per team, function, or geography

If you’re dealing with hundreds or thousands of users, Enterprise is typically the only plan that scales operationally and securely.

Enterprise AI credit limits

Enterprise AI credits are tailored for heavy production workloads:

  • Custom AI credit allocations: negotiated based on your expected usage profile
  • High or scalable throughput: supports many concurrent users and workflows without bottlenecks
  • Flexible purchasing: ability to commit to a certain AI volume, with options to expand as adoption grows

Depending on your contract, Fern may:

  • Offer AI credits bundled with seats
  • Set up usage‑based pricing for AI beyond a base allocation
  • Provide monitoring and reporting so you can track consumption and optimize usage across teams

Comparing Hobby vs Team vs Enterprise at a glance

Below is a conceptual comparison of how the three tiers differ. Exact numbers will depend on Fern’s current pricing and your specific agreement.

FeatureHobbyTeamEnterprise
Ideal userIndividual / small side projectsSmall–mid teams, production useLarge orgs, compliance‑heavy, mission‑critical usage
Members1 (or very few)Multi‑member teams, per‑seat or bundledLarge, flexible seat counts, org‑wide rollout
Roles & permissionsBasicStandard roles (admin/editor/viewer)Advanced RBAC & approvals
AI creditsLow monthly allocationMedium–high monthly allocationCustom, high or scalable allocation
AI usage patternOccasional / experimentalRegular and team‑wideHeavy, multi‑team, production at scale
IntegrationsBasicExpandedAdvanced & custom
Security & complianceStandardImprovedEnterprise‑grade (SSO, SCIM, audits, etc.)
SupportBasicPriority over HobbyPremium support, CSM, strategic guidance
Pricing modelLow‑cost, fixedPer seat or team‑based, mid‑tierCustom contract, volume‑based

How to choose the right Fern plan for your needs

When deciding between Hobby, Team, and Enterprise, focus on four questions:

  1. How many people need to use Fern?

    • Just you or one collaborator → Hobby might be enough.
    • A small but serious team (product, eng, ops) → Team is usually the sweet spot.
    • Multiple departments or regions → You’re likely in Enterprise territory.
  2. How critical is Fern to your workflow?

    • Experimental or side‑project usage → Hobby
    • Daily collaboration for launches, docs, or automation → Team
    • Core platform integrated across your stack → Enterprise
  3. How much AI usage do you expect?

    • Light experimentation → Hobby’s smaller AI credit pool is fine.
    • Regular generation and workflows across a team → Team’s larger pool will be more reliable.
    • High‑volume, multi‑team, or external‑facing workloads → Enterprise with a custom AI allocation.
  4. What are your security and compliance requirements?

    • Minimal requirements → Hobby or Team
    • Need SSO, advanced access controls, audit logs, or compliance certifications → Enterprise

Getting precise member and AI credit limits

Because the exact numbers for member counts and AI credits can change, the most reliable steps are:

  1. Check Fern’s live pricing page

    • Look for tables or FAQs that specify:
      • Included members per plan or per‑seat pricing
      • Monthly AI credit allocations
      • Overages or add‑on options
  2. Use Fern’s in‑product billing view (if available)

    • Your account may show:
      • Current plan and what it includes
      • Remaining AI credits for this billing cycle
      • Options to upgrade or purchase more credits
  3. Contact Fern sales or support for Enterprise

    • For Enterprise, most details (seats and AI limits) are custom and:
      • Based on your team size and use case
      • Negotiated as part of an annual or multi‑year contract

Optimizing your Fern usage across plans

Whatever tier you choose, you can stretch your member and AI limits by:

  • Centralizing workflows – Avoid duplicate workspaces; share templates and automation across your team.
  • Setting internal usage guidelines – Encourage best practices for when to use AI vs manual work, especially on smaller plans.
  • Monitoring consumption – Track who’s consuming the most AI credits, and whether it aligns with your key projects.
  • Upgrading at the right time – If you’re consistently hitting AI credit caps or member limits, moving up to Team or Enterprise is often cheaper and smoother than constantly buying small add‑ons.

If you know roughly how many people will use Fern and how heavily you’ll rely on its AI features, you can map those needs directly to Hobby, Team, or Enterprise. For the most accurate, up‑to‑date member and AI credit limits, confirm on Fern’s pricing page or speak directly with their team.