Chatbase vs Intercom Fin vs Helply: A Detailed Comparison

Key Takeaways:

• Chatbase cut the message credits included on its paid tiers by roughly 60% to 75% in 2026 while holding list prices flat, raising the effective cost per credit.
• Intercom Fin charges $0.99 per resolution on top of seats with no spending cap, and users report it billing conversations as resolved even after a human takes over.
• Helply gives B2B teams a full support platform free, then prices AI by outcome, from $0.25 drafts and $0.50 resolutions to $2.99 churn, upsell, and competitor signals, with caps so the bill cannot surprise you.
• Chatbase fits a startup that wants a quick FAQ deflector; Intercom Fin fits teams already committed to Intercom with high-value tickets.
• For a B2B software team at $1M to $50M ARR, Helply wins on predictable cost, account context, and deep channels like Slack Connect and Teams.

Chatbase vs Intercom Fin vs Helply: Comparison Table

If your team handles account-based B2B support and wants the bill to stay predictable, the outcome model is worth understanding before you commit.

Helply's outcome pricing explainer lays out how it works.

Chatbase: Best for a Quick Website FAQ Bot

Chatbase is a no-code platform for building an AI chatbot trained on your own content. Feed it a website, PDFs, or help docs, drop the widget on your site, and it answers common questions from that material. It is fast to launch and popular with startups, with more than 10,000 businesses using it.

For a B2B software team, the honest framing is this: Chatbase is a capable FAQ deflector, not a support platform. It shines on simple, repeatable questions and gets shakier on technical, account-specific tickets where a wrong answer carries real cost.

Chatbase Pricing in 2026, and the Credit Cut Nobody Flags

Chatbase runs on monthly plans plus message credits. These are the annual-billing rates; monthly billing runs roughly 25% higher.

Chatbase slashed its included credits this year. Hobby fell from 2,000 credits to 500, a 75% cut.

Standard dropped from 10,000 to 4,000, and Pro from 40,000 to 15,000. List prices barely moved, which means the effective cost per credit roughly doubled or tripled across the paid tiers.

Then come the add-ons. Auto-recharge credits cost $40 per 1,000. An extra agent is $300 a year. Removing the "Powered by Chatbase" badge runs $1,188 a year. For a growing support operation, the sticker price is the floor, not the ceiling.

Pros:

• Live in minutes. Most reviewers stand up a working bot in five to ten minutes with no code, and ease of use is its highest-rated trait on Capterra.
• Trains on your content. It ingests sites, PDFs, and docs, and lets you pick between models like GPT-4, Claude, and Gemini.
• Multi-channel embed. The widget deploys to a website and connects to Slack, WhatsApp, Instagram, and Messenger.

Cons:

• Confident hallucinations. Users report the bot inventing answers and stating wrong information fluently, which is a real risk on technical support.
• Thin credits, steep add-ons. The 2026 credit cuts plus per-unit overage and a $1,188-a-year branding fee make costs climb faster than the headline plan suggests.
• Weak support and shallow workflows. Capterra's support sub-score lags the product, and there is no visual builder for complex if-then logic.

Best for: Startups and small teams that want a quick, low-cost FAQ bot on a marketing site, not a full support operation.

Intercom Fin: Powerful, but Watch the Per-Resolution Bill

Fin is Intercom's AI agent, and it lives inside Intercom's broader support platform. The company renamed itself Fin in May 2026, though most teams still search for "Intercom Fin."

If your team already runs on Intercom and your help center is organized, Fin can resolve a meaningful share of conversations across chat and email. Setup is light. Fin has crossed $100 million in annual recurring revenue, so it is a serious, widely adopted product.

The catch is not capability. It is cost predictability, especially for teams with a fixed automation budget and rising volume.

Intercom Fin Pricing in 2026: Seats Plus $0.99 per Resolution

Intercom charges for seats, then adds Fin usage on top. Fin is $0.99 per outcome, billed separately from the plan.

A few details shape the real bill. Standalone Fin carries a 50-resolution monthly minimum. The Fin Copilot agent-assist add-on runs about $29 to $35 per seat per month. WhatsApp and SMS are billed separately. There are no volume discounts, and there is no spending cap.

What Counts as a "Resolution" in Intercom Fin?

This is where the budget surprises come from. Fin counts a conversation as a resolution when the customer confirms the answer or simply stops replying.

Intercom says conversations escalated to a human do not count. In practice, though, users report being billed for resolutions even after a human agent steps in. Some say low-value or off-topic chats get tagged too.

Because there is no cap, those edge cases compound. That is how a team ends up like the Reddit user whose monthly spend jumped from $4,000 to $9,000 after turning Fin on. The model rewards Intercom when volume spikes, and the customer absorbs the variance.

Pros:

• Fast to launch with strong answers. With a clean help center, Fin produces high-quality replies quickly, which is why it rates well across thousands of G2 reviews.
• One polished platform. Chat, inbox, ticketing, and analytics sit together, so teams already on Intercom avoid stitching tools together.
• Real-time analytics. Resolution rates, deflection, and CSAT report in one place for quick tuning.

Cons:

• Unpredictable, uncapped cost. The $0.99-per-resolution fee scales faster than headcount, and the absence of caps creates billing risk.
• The "resolved" definition. Conversations get billed as resolved even after a human takes over, inflating invoices beyond what the team would count.
• Knowledge locked to Intercom. Fin performs best when content lives in Intercom's help center, and it can falter on complex, multi-step technical questions.

Best for: Teams already committed to Intercom whose tickets are high-value enough to absorb an uncapped per-resolution fee.

If the per-resolution math is the sticking point, it is worth seeing the two models side by side in this Helply versus Intercom Fin breakdown.

Helply: Outcome Pricing on a Full Support Platform

Most AI support tools ask the same question: how many seats, and how many messages. Helply asks a different one: what outcome do you actually want, and did the AI deliver it.

The full support platform is free forever with unlimited seats, and you pay only when the AI produces a result.

That platform includes a shared inbox and ticketing, email and live chat, a knowledge base, macros, and reporting.

The whole team works in it at no cost, and the AI layer sits on top and gets billed by outcome.

Helply Pricing: Pay for Outcomes, Not Seats

The outcome prices are specific.

A resolution is $0.50 and a drafted reply for human review is $0.25.

Revenue-intelligence signals (a churn risk, an upsell opportunity, a competitor mention) are $2.99 each, because each one can be worth far more than its price.

A generated knowledge-base article is $2.99. If the AI delivers nothing in a given month, the bill is the platform price: zero.

Two contrasts matter here. There is no per-seat tax, so adding teammates is free, unlike Intercom. Spending caps are built in too, so a volume spike cannot produce a surprise invoice.

Helply frames the savings against seat-based incumbents like this. A 12-seat Zendesk Suite Professional stack with Copilot runs about $1,884 a month, against $0 for the Helply platform. That is more than $22,000 a year back to the business.

Built for B2B: Account Context, Revenue Signals, Channel Depth

The reason Helply fits B2B software teams is that it treats every ticket as account data. Four ideas drive that.

• Account Command Center. Every ticket opens with the full account in view: ARR, renewal date, product usage, and CRM and Stripe data, loaded automatically.
• Account Context. The AI draws on sources outside the inbox, including Gong calls, Salesforce, HubSpot, and product usage, so answers reflect the whole relationship.
• Revenue Signals. Each ticket is scanned for churn risk, upsell intent, competitor mentions, and feature requests, then routed to the CSM, AE, or Product owner who owns it.
• Revenue Engine. Every outcome ties to a dollar figure, so support reports a number leadership cares about instead of a cost line.

Channel depth is part of the fit too. Slack Connect runs as a native ticket queue, alongside Microsoft Teams, Discord, email, in-app chat, SMS, WhatsApp, a customer portal, and a public API.

They all feed the same context layer. Humans stay in the loop on the complex B2B tickets, and the AI assistant drafts replies and surfaces answers to make agents faster.

To see the agent itself, the AI agent overview walks through how resolutions and drafts work.

Pros:

• Free full platform, unlimited seats. The whole team works in a real support platform at no cost, and AI is the only paid line.
• Predictable, capped pricing. Outcome pricing plus built-in caps removes the per-seat tax and the uncapped-usage risk in one move.
• Account context by default. CRM, Stripe, Gong, and usage data load with every ticket, which is exactly what technical B2B support needs.
• Revenue signals from support. Churn, upsell, and competitor flags route automatically, turning the queue into pipeline intelligence.

Cons:

• Purpose-built for one ICP. Helply targets technical B2B companies that sell software, so B2C, e-commerce, agencies, and marketplaces are not the fit.
• Context pays off when connected. The AI is strongest once your CRM, billing, and product-usage sources are wired in, which takes some setup.

Best for: B2B software teams in the $1M to $50M ARR range that want a full platform, predictable cost, and support that surfaces revenue.

Is Chatbase or Intercom Fin Cheaper?

Take a 10-person B2B support team handling about 1,500 conversations a month, aiming to automate roughly 40%, which is about 600 resolutions.

• Chatbase: The Pro plan at $400 a month covers 15,000 credits, but credits are consumed per message and faster on advanced models, so heavy months trigger auto-recharge at $40 per 1,000. It also is not a 10-seat helpdesk, so a real support team still needs ticketing elsewhere.
• Intercom Fin: Ten Essential seats at $29 annual is $290 a month, plus 600 resolutions at $0.99 is $594. That is about $884 a month, uncapped, before higher tiers or volume push it up. On Advanced seats the same usage clears $1,400.
• Helply: The platform is $0 for all 10 seats, and 600 resolutions at $0.50 is $300 a month, with caps in place. Add a handful of $2.99 revenue signals and it is still well under the alternatives, with the whole team on the platform.

The pattern is the point. Chatbase looks cheapest until usage and add-ons stack up, and it is not a full platform. Fin is predictable only at low volume, then climbs without a ceiling.

How to Choose

The right answer depends on what kind of team is asking. Use these cues.

• Choose Chatbase if you want an inexpensive FAQ bot on a website and your questions are simple and repeatable.
• Choose Intercom Fin if you are already standardized on Intercom, your tickets are high-value, and an uncapped per-resolution fee is acceptable.
• Choose Helply if you run account-based B2B support, want a full platform without per-seat fees, and need cost to stay predictable as volume grows.

For B2B software teams specifically, Helply is built for the job rather than adapted to it. The built for B2B overview covers why account-based support is a different problem.

Final Verdict

In the Chatbase vs Intercom Fin decision, Chatbase wins on speed and simplicity for a basic FAQ bot.

Intercom Fin wins for teams already living in Intercom who can absorb an uncapped per-resolution fee.

For a B2B software team that wants a full platform, predictable cost, and AI that surfaces revenue, Helply is the stronger choice. The platform is free, the AI is priced by outcome and capped, and every ticket carries account context. Support is shifting from a cost center to a revenue engine, and outcome pricing is how the economics finally line up.