The short answer: an AI support agent resolves routine tickets end to end by reading your knowledge base and acting in your systems (looking up an order, issuing a refund), and hands everything else to a human. For small and mid-size teams, Quickchat AI7.5 out of 10 (7.5/10, free tier) scores highest. For large enterprises, Decagon7.4 out of 10 (7.4) and Intercom Fin7.3 out of 10 (7.3) lead. The tools differ far more in pricing and implementation effort than in the quality of their answers.
Disclosure: AgentsAI’s team has a working relationship with Quickchat AI. Its score is computed from the same rubric as every other tool; check the sub-scores on its profile7.5 out of 10 against our methodology.
Quick picks
- SMB, no-code, 100+ languages: Quickchat AI7.5 out of 10, 7.5, free tier, paid from $9/month.
- Enterprise, highest automation: Decagon7.4 out of 10, 7.4, custom pricing.
- Outcome-priced, many integrations: Intercom Fin7.3 out of 10, 7.3, $0.99 per resolution plus seats.
- Most capable, hardest to buy: Sierra6.7 out of 10, 6.7, custom pricing (estimated $150K to $350K+ a year).
- Omnichannel at large scale: Ada (AdaCX)6.6 out of 10, 6.6, from about $30K a year.
For a full side-by-side with pricing structures, see our best AI customer support agents ranking.
AI agents vs. traditional chatbots
A traditional chatbot follows a script or decision tree and struggles the moment a customer goes off it. An AI support agent uses a large language model grounded in your own help content to understand free-form questions, ask clarifying ones, and take actions through integrations: routing a ticket, pulling an order status, changing a subscription.
The practical difference is resolution. A chatbot deflects; an agent should complete the task. Agents are designed to complement your human team, not replace it: they absorb the repetitive tier so people can spend time on complex or emotional cases.
What AI support agents actually change
- Availability. Instant answers at any hour and no queue at peak, such as launch days or outages.
- Cost per contact. Routine questions are most of the volume, so automating them lowers cost without a linear rise in headcount.
- Consistency. The same policy applied the same way every time, with a transcript for audit.
- Personalisation. Agents connected to your CRM or order system can reference the customer’s actual order or plan rather than giving generic answers.
- Insight. Conversation analytics show what customers ask about, and where your documentation has gaps.
The caveat: a vendor’s headline number is usually deflection (conversations that did not reach a human), which counts customers who gave up. Ask for resolution rate with the definition attached, CSAT on AI-handled conversations, and escalation rate.
The tools, ranked by score
1. Quickchat AI (7.5): best no-code option
Quickchat AI7.5 out of 10 is a no-code platform for building support agents that deploy on a website or app. It scores 8/10 on both capability and ease of use, supports 100+ languages with automatic detection, and includes human handoff. The free and $9 Starter plans are heavily credit-limited; production use starts around the $29 Basic tier, and AI Actions unlock at $99/month. It runs on OpenAI models only. Best for: SMBs and agencies without engineering resources. See Quickchat’s plans and scores7.5 out of 10.
2. Decagon (7.4): best for enterprise volume
Decagon7.4 out of 10 offers enterprise agents that resolve interactions autonomously across chat, email, voice and SMS, with Agent Operating Procedures that let CX teams change workflows in plain language. It reports 75 to 80% deflection in production. There is no free tier or public pricing, and implementation takes weeks and engineering bandwidth. Best for: large enterprises on Zendesk, Salesforce or Kustomer. See Decagon’s strengths and limits7.4 out of 10.
3. Intercom Fin (7.3): best for outcome pricing
Intercom Fin7.3 out of 10 charges $0.99 per resolution on top of Intercom seats from $29/seat/month (a standalone option starts at $49.50/month), and reports a 67% average resolution rate across customers. Integrations cover Salesforce, Shopify, Stripe, Zendesk and HubSpot. Setup is complex and high volume can mean four-figure monthly bills. Best for: mid-to-large teams that want an agent taking action, not answering FAQs. Compare Fin’s pricing tiers7.3 out of 10.
4. Sierra (6.7): most capable, hardest to buy
Sierra6.7 out of 10 has the highest capability score in this group (9/10): it works across chat, voice, SMS, email and more, can act in your backend systems, and uses outcome-based pricing. But ease of use and value both score 4/10: estimated cost is $150K to $350K+ a year, with no self-serve access. Best for: large enterprises with the budget and timeline for a full implementation. See Sierra’s profile6.7 out of 10.
5. Ada / AdaCX (6.6): omnichannel at scale
AdaCX6.6 out of 10 lets one agent handle web chat, mobile, social DMs, SMS and voice, with resolution analytics and ROI dashboards. Usage-based pricing runs roughly $1 to $3.50 per resolution (shifting toward conversation pricing), with annual contracts from about $30K. It suits companies with 300K+ annual conversations; ease of use is 5/10. See Ada’s pricing and scores6.6 out of 10.
6. Forethought (5.6): triage and agent assist
Forethought5.6 out of 10 pairs autonomous resolution with intelligent triage and agent-assist features such as suggested replies and knowledge-gap detection. It scores 7/10 on capability but 4/10 on both ease of use and value, with custom pricing only. It fits established enterprises handling 2,000+ tickets a month; for most teams the options above score higher. See Forethought’s breakdown5.6 out of 10.
Which should you choose?
- If you have no engineers and want to launch this week, choose Quickchat AI7.5 out of 10 or, for a store, Tidio7.0 out of 10 (7.0, free plan).
- If you run an online store, read AI agents for eCommerce and look at Gorgias7.1 out of 10 (7.1).
- If you want to pay only for resolved conversations, shortlist Intercom Fin7.3 out of 10 and Decagon7.4 out of 10.
- If you have an enterprise budget and omnichannel needs, compare Sierra6.7 out of 10 and AdaCX6.6 out of 10.
- If most customers call, see the voice agents ranking.
How to evaluate any support agent
- Measure a baseline first: resolution rate, cost per contact, CSAT.
- Test on your real, messy tickets, not vendor demo data.
- Check what it can do, not only say: can it write to your order system or only read?
- Make escalation obvious: a customer who cannot reach a person is the fastest way to lose trust.
- Model cost at your real volume, and check who defines “resolved.”
Our guide to choosing an AI agent covers the full framework.
Next step
Open the profiles of the two best fits and compare sub-scores and plan limits: Quickchat AI7.5 out of 10 and Intercom Fin7.3 out of 10 for most teams, Decagon7.4 out of 10 if you are enterprise-scale. Then read the detailed customer support agents ranking for pricing structures, or browse every tool in the customer support category.