Fin AI pricing and plans explained (2025)

AI Agents are transforming customer support by resolving queries instantly, deflecting tickets, and giving customers the fast, reliable answers they expect. Powered by Large Language Models (LLMs), they’re becoming a must-have for businesses that want to scale support without scaling headcount.

But with so many AI platforms available, pricing transparency is just as important as features. Companies need to know whether they’ll face predictable monthly costs—or unpredictable bills tied to usage.

Fin AI, Intercom’s flagship AI Agent, has made waves with its outcome-based pricing model, where businesses pay only when the bot successfully resolves a query. While this sounds fair, it can also create budgeting challenges.

In this blog, we’ll break down Fin AI’s outcome-based pricing, highlight its features, discuss the pros and cons, and compare it directly with pagergpt, a platform known for its flexible and predictable pricing.

Fin AI is Intercom’s flagship AI Agent, designed to automate customer support by resolving common questions instantly and handing off complex issues to human agents. It’s powered by advanced large language models (LLMs) and Intercom’s proprietary Fin AI Engine, which combines natural language understanding, workflow logic, and integrations to deliver accurate, conversational responses.

Unlike traditional chatbots that rely on scripted rules, Fin AI learns from your company’s knowledge base and adapts to customer intent in real time. Businesses only pay when Fin successfully resolves a customer issue, thanks to its outcome-based pricing model.

Key highlights of Fin AI

• AI-powered answers – Delivers natural, context-aware responses to customer queries.

• Fin AI engine – Orchestrates queries across different models to optimize for accuracy, cost, and speed.

• Knowledge base integration – Pulls content directly from the Intercom Help Center and connected resources.

• Smooth human handoff – Transfers conversations seamlessly to live agents when needed, preserving context.

• Native Intercom integration – Works inside the Intercom platform, fitting into the inbox, workflows, and analytics.

• Outcome-based pricing – Charges only for successful resolutions, aligning cost with delivered value.

Fin AI is Intercom’s answer to next-gen AI customer service: a tool that blends advanced research, practical automation, and business-friendly pricing to help support teams scale without overwhelming agents.

Fin AI keeps its pricing simple yet distinct, offering two core ways to use the agent depending on whether you want to stick with your existing helpdesk or adopt Intercom’s full suite. On top of that, there’s an optional Copilot add-on and a startup program for early-stage companies.

Fin with your current helpdesk

$0.99 per resolution (50 resolution minimum per month)

If you’re already using a helpdesk like Zendesk, Salesforce, HubSpot, Freshworks, or others, Fin can plug directly into your stack. This plan gives you AI resolution capabilities without forcing you to migrate to Intercom.

Features included:

• Works seamlessly with top helpdesks: Zendesk, Salesforce, HubSpot, Freshworks, Dixa, Zoho, Gorgias, and more.

• Set up in under an hour with minimal configuration.

• Supports tickets, email, live chat, WhatsApp, SMS, and social channels.

• Customizable tone and answer length to match your brand.

• Ability to take actions and update external systems.

• Direct agent transfer into your preferred inbox when escalation is needed.

Fin with Intercom’s helpdesk

$0.99 per resolution + $29 per helpdesk seat/month

This package is designed for companies that are ready to adopt Intercom as their primary customer service hub. You get the same outcome-based Fin AI pricing plus access to the complete Intercom platform.

Features included:

• Complete Intercom customer service suite.

• Configurable inbox and ticketing system.

• Multi-channel support across email, live chat, phone, SMS, and more.

• Workflow automations to streamline repetitive processes.

• Prebuilt reporting dashboards.

• Public Help Center & Knowledge Hub for customers.

• Proactive outbound messaging suite to engage customers before they raise issues.

Add-on: Copilot

$35 per user/month

Fin Copilot serves as an AI sidekick for your human agents, directly embedded in their inbox. It helps agents respond faster and learn quicker.

Features included:

• Personal AI assistant offering instant suggestions and advice.

• Pulls answers from trusted sources (your docs, FAQs, knowledge base).

• AI-powered global translations for multilingual support.

• Accelerates agent onboarding and improves resolution speed.

Startup program

For early-stage companies, Intercom offers 90% off its platform plus 1 year of Fin free. This makes it easier for startups to test AI support at scale without incurring upfront costs.

The real cost driver

At first glance, Fin AI’s $0.99 per resolution looks simple, but the true cost scales with:

• Number of successful resolutions – every resolved query counts, and high volumes multiply costs quickly.

• Agent seats – $29 per Intercom helpdesk seat, plus $35 per Copilot user, add recurring per-agent costs.

• Add-ons – extra features like Copilot are charged separately per user.

This makes Fin less predictable for fast-growing teams handling thousands of customer conversations each month.

Hidden costs to keep in mind

Beyond the published rates, companies should also be aware of:

• Third-party helpdesk subscriptions – If using Zendesk, Salesforce, or others, you’ll pay their licensing fees in addition to Fin’s per-resolution charges.

• Migration costs – Moving into Intercom’s helpdesk suite may require time, training, or external support.

• Scaling risk – As teams add more seats or adopt Copilot broadly, costs increase significantly.

• Variable bills – Because charges depend on resolutions, monthly costs fluctuate and may be harder to budget compared to flat subscription models.

• Fin AI Engine – Proprietary architecture optimized for accuracy, speed, and reliability, purpose-built for customer service.

• Multi-source generative answers – Pulls knowledge from multiple sources (helpdesk, docs, policies) to craft precise, context-aware replies.

• Knowledge management – Tools to train Fin with tone of voice, company policies, and targeted content.

• Multilingual + real-time translation – Supports over 45 languages with instant translation.

• Fin Tasks – Executes actions, updates external systems, or completes workflows directly from a conversation.

• Testing & optimization – Batch testing, answer inspection, unresolved question reports, and performance dashboards to continuously improve accuracy.

• Human handoff – Escalates smoothly to agents in your preferred inbox while preserving conversation history.

• Omnichannel deployment – Works across email, live chat, phone, SMS, WhatsApp, social, Slack, and APIs.

• Insights & analytics – Fin performance reports, customer experience scoring, unresolved questions analysis, and holistic reporting.

• Security & compliance – Enterprise-grade with SOC 2 and GDPR compliance.

Fin AI’s outcome-based pricing is unique in the AI Agent space. Instead of paying for every message or interaction, you’re only billed when Fin successfully resolves a customer issue. While this aligns cost with value, it comes with trade-offs that businesses should weigh carefully.

Pros

• Aligned incentives – You only pay when Fin delivers a resolution, making the pricing feel fair and performance-driven.

• Fair for low-volume teams – If your AI agent fails to solve a query, you don’t get charged, which can benefit smaller teams or businesses testing automation.

• Perceived value for outcomes – Costs map directly to measurable results rather than generic usage metrics like tokens or message counts.

Cons

• Unpredictable bills at scale – Monthly spend fluctuates based on resolution volume, making it harder for IT and finance teams to forecast budgets.

• Ecosystem lock-in – Fin is deeply tied to the Intercom platform; you can’t use it as a standalone AI agent.

• Resolution definition controlled by Intercom – Whether a query is considered “resolved” depends on Intercom’s system logic (confirmation or inferred closure), not the customer’s own reporting.

• Extra costs stack up – Add-ons like Copilot and helpdesk seat fees increase total cost beyond the headline $0.99/resolution.

Fin AI’s outcome-based model charges $0.99 per resolution, with costs fluctuating based on the number of queries the bot resolves. While fair in theory, it makes monthly bills harder to predict—something that finance and IT leaders often struggle with.

pagergpt, on the other hand, uses session-based pricing. Each session allows a customer to complete a full conversation with the AI Agent — whether that takes one exchange or ten — without worrying about being left hanging midway. This makes the experience smoother for end users and more cost-predictable for businesses.

pagergpt pricing plans

• Magic plan ($0/month) – For startups and SMBs testing AI Agents, includes 100+ sessions, training from website/files, app integrations, and live chat inbox.

• Business plan ($349/month) – The most popular plan with 1,000 sessions, 50M characters for training, multiple AI agents, advanced integrations, and 5 admin/agent seats.

• Enterprise plan (custom pricing) – Designed for large organizations, offering higher session volumes, dedicated compliance (ISO 27001, SOC 2, HIPAA), RBAC, MFA, and premium support.

Why session-based pricing matters

• Predictable IT budgeting – Sessions are easier to forecast than unpredictable resolution-based charges, giving finance teams stable monthly expenses.

• Better user experience – Customers can complete their queries in one conversation session, instead of being cut off or charged multiple times mid-way.

• No hidden costs – Unlike Fin AI’s extra charges for seats and Copilot add-ons, Pagergpt bundles training, omnichannel support, analytics, and compliance into each plan.

• Smooth scalability – Businesses can move to higher session tiers as usage grows, without worrying about spiky bills tied to unpredictable query volumes.

pagergpt’s session-based, transparent pricing gives companies both budget control and a better customer experience, making it a more reliable alternative to Fin AI’s fluctuating, outcome-based model.

Fin AI vs pagergpt: Pricing at a glance

While Fin AI is built tightly into the Intercom ecosystem, pagergpt is designed as a flexible, standalone AI Agent platform that works across multiple tools and workflows. The difference shows up clearly when comparing features and long-term value.

Integrations

pagergpt is built to integrate widely, supporting platforms like Zendesk, Freshdesk, Slack, Microsoft Teams, WhatsApp, and Messenger. This flexibility makes it a strong fit for businesses that run support operations across multiple tools and channels. Fin AI, in contrast, is tied primarily to the Intercom ecosystem. While it can connect with external helpdesks, its strongest use case remains within Intercom’s own suite.

Customization

When it comes to customization, pagergpt provides far more control. Companies can create multi-persona agents, set guardrails to enforce compliance or tone, and automate workflows to match unique processes. This level of flexibility allows Pagergpt to adapt across industries and use cases. Fin AI, by design, is optimized for Intercom’s workspace, which limits customization options to what the platform natively supports.

Analytics

pagergpt offers advanced analytics dashboards that track sentiment, resolution rates, CSAT, and conversation trends in detail. These insights help teams refine both customer experience and agent performance. Fin AI does include reporting around resolutions and deflections, but the depth of analysis is relatively basic compared to Pagergpt’s AI-driven insights.

Security

Security is another area where pagergpt goes beyond the standard. It meets enterprise compliance requirements with ISO 27001, SOC 2, GDPR, and HIPAA certifications, making it suitable for industries with strict regulations like healthcare and finance. Fin AI also meets SOC 2 and GDPR standards, which are strong for general enterprise use, but it lacks the broader compliance coverage that larger organizations may demand.

pagergpt delivers broader integrations, deeper customization, richer analytics, and stronger compliance when compared to Fin AI. For businesses that want predictable pricing, enterprise-ready features, and the flexibility to scale beyond a single ecosystem, pagergpt provides a more comprehensive long-term solution.

Fin AI and pagergpt take very different approaches to pricing and deployment. Fin AI’s outcome-based model works well for enterprises already embedded in Intercom’s ecosystem, while pagergpt’s session-based tiers offer predictability and flexibility that smaller teams and fast-growing businesses need.

Ultimately, the right choice depends on whether you value tight Intercom integration with variable costs, or broad integrations with predictable pricing. Both platforms are capable, but aligning pricing structure with your business model will ensure you get the most value from your AI investment.

If you’re looking for cost predictability, scalable integrations, and enterprise-grade compliance in one platform, explore what pagergpt can do for your business.

Book a demo today and see how session-based pricing gives you more control and better ROI than outcome-based models.