Here are the top AI chatbots and conversational‑AI platforms to consider for customer support — updated as of September 14, 2025. I grouped them by typical use case and included a short pros/cons, best-fit, and an authoritative source for each so you can dig deeper.

Enterprise / full contact‑center & omnichannel

• Intercom (Fin) — Best for fast, conversational self‑service that plugs into product messaging. Pros: GPT‑powered conversational answers, easy ingest of your help content, seamless human handoff; Intercom reports high deflection rates when configured. (intercom.com)

  • Best for: SaaS companies that want in‑product messenger + support automation.

• Zendesk (Answer Bot / Zendesk AI) — Best when you already use Zendesk Support/Guide. Pros: strong knowledge‑base article recommendation, web/mobile SDKs, smooth ticket handoff. Works as a deflection layer to reduce ticket volume. (answerbot.zendesk.com)

  • Best for: Organizations standardized on Zendesk ticketing.

• Freshworks Freddy (Freshdesk) — Strong omnichannel AI agents + agent copilot features (summaries, suggested replies). Vendor claims high deflection and agent productivity improvements. (freshworks.com)

  • Best for: Mid‑market to enterprise teams seeking fast time‑to‑value across chat, email, and messaging.

• LivePerson (Conversational Cloud) — Enterprise conversational platform focused on large scale, voice + messaging orchestration and real‑time agent assist; recognized in Gartner evaluations. (liveperson.com)

  • Best for: Large contact centers and brands needing deep integrations and analytics.

• Salesforce Einstein GPT (Service Cloud) — Deep CRM integration (Customer 360 + Data Cloud) with LLM‑generated service responses, knowledge authoring, and case summaries. Ideal when you want AI fully tied to Salesforce customer data. (salesforce.com)

  • Best for: Enterprises built on Salesforce.

Large enterprise / regulated environments & advanced RAG

• IBM watsonx Assistant — Enterprise‑grade RAG (retrieval‑augmented generation), voice + call‑center integrations, traceable sources and governance features for regulated industries. (ibm.com)
  • Best for: Regulated industries (finance, healthcare) that need on‑prem/controlled deployment and source grounding.

Sales & conversational marketing + live handoff

• Drift — Strong at conversational marketing and qualifying leads while offering support automation; good CRM routing & meeting scheduling. (prnewswire.com)
  • Best for: B2B companies wanting to combine support and sales/lead qualification.

SMB / e‑commerce / quick deploy

• Tidio — Affordable, fast Shopify/WooCommerce integration; live chat + AI bot for FAQs, cart recovery and order lookups. Good for small e‑commerce stores. (apps.shopify.com)
  • Best for: Small online stores and SMBs.

No‑code / omnichannel automation specialists

• Ada — No‑code omnichannel AI agents focused on high containment and multi‑channel messaging (WhatsApp, SMS, web); strong for multilingual deployments. (ada.cx)
  • Best for: Brands that need business‑user control and omnichannel message coverage.

Open‑source / self‑hosted / maximum control

• Rasa — Open‑source conversational framework (and paid enterprise options) for teams that want full control, on‑prem hosting, and custom pipelines. Good when you need privacy/compliance and deep customization. (opensource.rasa.com)
  • Best for: Engineering teams building custom assistants or those with strict data‑sovereignty needs.

General purpose / building custom agents and copilots

• OpenAI (ChatGPT Enterprise / ChatGPT Agents / API) — If you want to build advanced, custom agents or copilots (and/or use GPT‑4o/GPT agents), ChatGPT Enterprise and the API offer enterprise controls and connectors; OpenAI states enterprise data is not used to train public models by default. Useful as a backend LLM for tailored support agents. (openai.com)

Important operational notes (must‑read)

• Try a pilot and measure the right KPIs: ticket deflection, containment rate, average handle time (AHT), CSAT, escalation rate, and cost per contact. Vendors’ “deflection” or “resolution” claims vary by dataset and setup — test with your content and traffic. (See vendor product pages above for vendor claims.) (freshworks.com)
• Data handling & compliance: AI chatbots and LLMs are under increased regulatory and enforcement attention; evaluate data residency, retention, and whether the vendor trains models on customer data. The U.S. FTC has been investigating consumer‑facing chatbots (September 2025), so verify vendor privacy/compliance practices for your industry. (reuters.com)
• Hallucinations & grounding: prefer platforms that support retrieval‑augmented generation (RAG) or explicit knowledge‑base grounding (source links, citations) for support answers (IBM watsonx, many enterprise offerings, and some Intercom/Freddy configurations). (ibm.com)

How to pick (quick checklist)

1. Integrations: does it connect to your CRM, ticketing, order system, and telephony?
2. Channel coverage: web chat, in‑app, WhatsApp, SMS, voice?
3. Control & compliance: do you need on‑prem or private‑cloud hosting? (Choose Rasa, IBM, or enterprise plans that support data residency.)
4. Human handoff & supervision: how easy is escalation and agent assist?
5. Cost model: per‑message, per‑resolution, seat, or usage credits — run a forecast with your volumes.
6. Pilot: run a 4–8 week pilot with real KB content and measure deflection + CSAT.

If you want, I can:

• narrow these to the 3 best options for your company size and tech stack (SMB, mid‑market, enterprise), or
• produce a short pilot plan (objectives, KPIs, 30/60/90‑day rollout) for 2–3 shortlisted vendors.

Which would you like me to do next?