Customer Support

Combining LLMs with deterministic decisioning to reduce hallucinations

Use deterministic decision engines for specific actions (instead of letting the LLM freestyle) to improve reliability and prevent incorrect automated steps during support interactions.

Why the human is still essential here

Humans decide which actions can be automated, validate outcomes, and set safe-guards and fallback paths when confidence is low.

How people use this

Rule-gated refund authorization

The assistant only triggers a refund workflow when policy rules (eligibility, time window, order status) deterministically pass — the LLM cannot override them.

Zowie AI

Structured dialogue flows for account changes

A deterministic flow collects required fields and validates them before calling backend systems, while an LLM handles free-text explanations.

Ada

Tool-calling with allowlisted actions

An LLM can answer questions but can only execute predefined, permissioned actions via an orchestrator that enforces schemas and safeguards.

Microsoft Copilot Studio / Power Automate

Policy-checked returns and shipping exceptions

The bot confirms return eligibility via deterministic rules (order date, item type, shipping exceptions) and only then triggers a return/refund workflow in backend systems.

Zowie AI

Safe API actions via approved workflow steps

The assistant can only execute pre-approved actions (e.g., update shipping address, cancel subscription) by calling named workflows with strict input validation.

Workato / Zendesk

Deterministic identity verification before account changes

Automation gates any sensitive action behind a scripted verification flow (OTP, last 4 digits, order ID) and escalates if verification fails.

ServiceNow Flow Designer / ServiceNow CSM

Community stories (1)

Reddit

Best AIs for customer support? Tested a bunch. Some thoughts…

I know how these posts usually go, so I'll just say upfront I'm going to be pretty rough and honest about all of these, including the ones I liked. I feel like each of them deserves a praise and comment as they have totally different approaches.

For context: I test AI tools constantly. Coding assistants, generative media stuff, random B2B SaaS. Usually I enjoy the crowded categories. But AI customer support platforms might be the most crowded AI category right now. Everyone claims to automate support, every demo looks amazing, and every sales rep makes it sound like you've just found the solution. The differences really only become obvious once you're inside the product.


So after way too many trials and sales calls, here's where I landed. Happy to hear from you I'm wrong.


Zendesk AI


If you're already on Zendesk, this is might bd the easiest move. AI triage, suggests responses from past cases, good routing. Very much a copilot approach,making agents faster rather than replacing them. Not flashy, but sometimes boring and reliable wins. The flip side is it feels like AI bolted onto a legacy product, not built from the ground up. You'll hit the ceiling eventually.


Zowie AI


The one I didn't see coming. Hadn't heard of them before the eval, then realized companies like Payoneer, Monos, and InPost are already running it, so apparently I was just late Implementation seemed faster than expected for enterprise setups, and they pair you with a pretty involved TAM during rollout.They use a deterministic decision engine for certain actions instead of letting the LLM freestyle, which helps avoid hallucinations. Also some interesting system-to-system automation (A2A) and visual troubleshooting aids inside conversations. But the orange logo made me smile haha looks a bit like some morse code.


Intercom Fin


Probably the most stable conversational quality I tested, unfortunately kinda blunt. Learns from agent edits, personalizes well, polished product. But it really wants you inside the Intercom ecosystem. If you're stitching together outside tools, expect friction. And pricing gets steep at volume, seriously, model your costs before you fall in love with zthe demon.


Ada


Probably one of the easiest for non-technical teams to get running. The flow builder is intuitive and handles common use cases well. But "common use cases" is doing a lot of work in that sentence. For anything involving complex backend integrations, order systems, billing, expect custom effort and longer timelines.


Freshworks Freddy AI


Best value pick for smaller teams but I mean small. Ticket classification, sentiment analysis, works out of the box with Freshdesk. If you need ab 80% of the capability at a fraction of the price, worth a look. Just don't expect it to keep up if your support operation gets complex.


LivePerson


The old veteran pick for some less regulated industries.More of a platform than a product though, you'll want a dedicated team to manage it, and the onboarding isn't cheap.


Kore.ai


Enterprise voice and complex IVR. Solid multilingual NLU and good templates. But this is not a self-serve deployment. I would think about hiring a technical team or paying them extra to get it done but it seemed kinda costly


Curious what’s others are running in production and what's still working at month 3. Thought about sharing a bit wit you the community up there although still feel kinda shy ahahah

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Far_Character4888AI tools evaluator (customer support platforms)
Mar 4, 2026
Combining LLMs with deterministic decisioning to reduce hallucinations - People Use AI