For teams on Gladly weighing the budget and the AI

Gladly is excellent. That is not why teams shop for alternatives.

Gladly's people-centered, no-tickets model is one of the most loved experiences in premium retail. It organizes support around the customer and one lifelong conversation, not a disposable ticket number, and brands like Nordstrom, HOKA, UGG, and Ulta run on it. So the reason teams go looking for an alternative is rarely the experience. It is the budget and the AI: quote-based pricing positioned at the premium end, and an AI agent that sits on a hybrid helpdesk-plus-AI core rather than a platform rebuilt around the agent. This guide defines six operational criteria before scoring anyone, runs a matrix across Richpanel, Kustomer, Zendesk, Gorgias, and Gladly itself, names the situation where each one is the better choice than Richpanel, and ends with a decision tree instead of a verdict.

By Amit RG, Founder, Richpanel Published 2026-06-18 Updated 2026-06-18 ~11 min read
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Amit RG is the founder of Richpanel, the AI-native helpdesk serving 2,000+ brands. He sits in vendor bake-offs against most of the platforms compared here, including Gladly, and the criteria below are the ones his own team uses when prospects ask "how are you different." Source data: 69 recorded buyer demos (April to May 2026) and production telemetry from live Richpanel deployments. On X: @realamitrg.
Start by giving Gladly its due

A people-centered model that premium retail genuinely loves.

Ask a luxury or premium retail CX leader what platform feels closest to how they actually want to treat customers, and Gladly comes up more than almost anything. That is not an accident of marketing. Gladly's no-tickets, customer-at-the-center model is one of the strongest experiences in the category, and any honest "alternatives" guide has to start there.

Gladly was built on a contrarian idea: organize support around the person, not the ticket. Instead of a customer generating a fresh ticket number every time they reach out, each customer has one lifelong conversation timeline that follows them across channels, so an agent always sees the full relationship.[1] For brands where the relationship is the product, that is exactly right. It is why Gladly has won marquee retail names like Nordstrom, HOKA, UGG, and Ulta, and why its customers tend to be loud advocates. When a premium brand wants high-touch, deeply personalized service that feels seamless, Gladly is a genuinely defensible answer, and we have lost deals to exactly that preference.[3]

So this guide is not "why Gladly is bad." It is not. The honest question is narrower: if the Gladly experience is so good, why do so many teams end up shopping for an alternative? In our buyer conversations the answer is almost never the experience. It is two structural things that have little to do with how good the customer timeline feels. The first is the price and how you find out what it is. The second is how AI-native the platform really is when your goal is to automate volume, not just personalize it.

One disclosure before the criteria. Richpanel is one of the five platforms compared below, so I am a participant, not a referee. I will not claim we win every column, because we do not. I will define every criterion before the matrix appears, name a specific situation where each of the other four (Gladly included) is the better choice, link each vendor's own pricing and product pages so you can check my reading, and publish a correction address at the bottom. Read it as a more useful starting point than a vendor listicle, not as a neutral analyst report.

The reason teams actually shop

The price is gated, and the AI is an add-on, not the core.

Two facts about Gladly sit underneath most of the alternative-shopping we see, and neither is a knock on the customer experience.

First, the pricing. Gladly does not publish a per-seat number. Pricing is quote-based and sales-gated, and the platform is positioned at the premium, enterprise end of the market alongside its marquee retail customers.[2] For a brand that wants white-glove service and has the budget for it, that is fine. The catch is twofold: you cannot model your bill without a sales conversation, and the floor tends to be high relative to mid-market alternatives. A growing DTC team that wants to know what a platform costs before it commits, and that is watching its support spend, often finds Gladly out of range before the relationship even starts. Quote-based premium pricing is the opposite of the cost predictability they were hoping to buy.

There is a subtler issue too. Gladly recently rebranded to gladly.ai as an AI-native pivot, and its AI agent, Gladly Sidekick, is real and capable. But the platform underneath is a hybrid: a mature people-centered helpdesk with an AI core added, rather than a system rebuilt around the agent from the ground up. That distinction does not matter for a team whose goal is human-led, relationship-heavy service. It matters a lot for a team whose goal is to automate a high volume of repetitive order-status, returns, and subscription questions, because the further AI is from the center of the architecture, the more it tends to assist rather than resolve.

Second, the fit mismatch. Gladly's model is built for high-touch relationship work, and it is at its best when a human is in the loop on a valued customer. That is a strength if your support is a luxury concierge experience. It is a cost if your queue is dominated by repeat transactional questions, because the model optimizes for the wrong thing: it makes every conversation feel personal, when what a high-volume DTC brand actually needs is for most of those conversations to resolve themselves. Choosing a platform is choosing what your support is for.

Hold onto one more distinction before the criteria, because it reorders every published ranking: the difference between deflection and resolution. Deflection counts a ticket as handled when the customer stops asking, which includes the customer giving up and leaving. Resolution counts a ticket as handled only when the customer's actual problem is solved, validated, and confirmed. We wrote the full breakdown in AI chatbot vs. AI agent; for this guide it matters because an AI agent is only worth its keep if "resolution" means the strict thing, not the loose one.

Defined before the comparison

Six criteria, weighted for a team watching its margins.

These are operational, not vibes. Each is defined so two evaluators would score a vendor the same way. The weights reflect the target reader for this guide: a CX or ops lead who admires the Gladly experience but is feeling the premium price or wants the AI to carry more of the load, at any volume from a few hundred to 100,000+ conversations a month.

01

Resolution model (weight: high)

Does the agent resolve end to end autonomously, draft replies for a human to approve, or only assist a person who is still doing the work? Operational test: of 100 inbound tickets, how many are closed with no human touch and a confirmed outcome, not just a customer who stopped replying?

02

Pricing transparency and alignment (weight: high)

Can you model the bill before a sales call, and does the model match your incentives? Quote-based premium pricing, per-seat, per-resolution, per-conversation, or flat workspace? The question is not "cheapest sticker price" but "do I know what this costs, and does the bill grow with my volume or stay predictable?" This is the criterion that sends most Gladly shoppers looking, so it carries top weight here.

03

Pre-launch validation on your data (weight: high)

Will the vendor run the agent against a sample of your historical tickets and show per-response accuracy before go-live, against a published threshold? A demo on the vendor's curated example proves nothing about your catalog and your policies, and an aggregate resolution rate from a marketing page proves even less.

04

Action execution depth (weight: medium)

Can it execute real operations (refunds, cancellations, order edits, subscription changes) as validated, policy-bounded actions, or does it only generate text and hand off? For ecommerce, this is the line between a help-desk reply and an actual resolution.

05

AI-native architecture (weight: medium)

Is the platform rebuilt around the AI agent, or is AI a layer added to an existing helpdesk? An agent bolted onto a people-centered ticketing model behaves differently from one that is the center of the system. This is the criterion that distinguishes Gladly's hybrid core most sharply from an AI-native platform.

06

Multichannel and ecommerce fit (weight: medium)

Does one unified customer context follow the person across email, chat, social, SMS, and voice, and is the agent tuned for the ticket mix you actually have? True omnichannel support means the communication channels share one timeline, not five disconnected inboxes. Gladly is strongest in high-touch retail and voice; an ecommerce queue dominated by order-status, returns, and subscriptions has different needs. For the channel cut, see our multichannel AI support comparison.

Criteria 1 through 3 carry the most weight because resolution quality, pricing transparency, and proof-on-your-data are what a Gladly shopper is actually weighing. Criteria 4 through 6 decide fit once the economics work. The matrix below shows the five most comparable axes; AI-native architecture does not tabulate into a one-line cell cleanly, so the per-vendor notes carry it.

The comparison, as of June 2026

Five platforms, five comparable axes.

Cells reflect each vendor's public product and pricing pages as of June 2026. Each platform name links to the page used to source its row. Where a capability is real but not separately documented, the cell says so rather than guessing.

Platform Resolution model Primary pricing model Pre-launch eval on your tickets Action execution AI-native architecture
Richpanel Autonomous resolution, or collaborative draft mode Per-conversation / flat workspace, ~$0.30 per AI-resolved conversation Yes, per-customer threshold (95–99% on your historical tickets before go-live) Typed, policy-bounded actions (refunds, cancellations, order and subscription edits) Yes: helpdesk rebuilt around the AI, plus a CX Manager AI that configures the agents
Gladly AI assist plus autonomous Sidekick over a people-centered timeline Quote-based, premium / enterprise (no public per-seat price) Not publicly documented; enterprise onboarding rather than a published per-customer eval Actions via Sidekick and integrations Hybrid: people-centered helpdesk with an AI core added (gladly.ai pivot)
Kustomer AI supports reps; agentic features layered on Per-seat, plus AI and channel add-ons (voice, SMS, HIPAA gated) Not publicly documented Actions via workflows on a CRM-first data model Hybrid: CRM-first helpdesk with bundled AI
Zendesk AI Agentic resolution plus automations Per-agent seats, plus AI add-on and per-resolution fees Not publicly documented; QA via separately-priced Zendesk QA Actions via triggers; AI-generated text less constrained Bolt-on: AI added to a 2007-era helpdesk
Gorgias AI Agent resolution plus macros and automations Per-ticket plans, plus ~$0.90 per AI resolution on top Not publicly documented Shopify-native actions (orders, refunds, subscriptions) Bolt-on: AI Agent add-on on an ecommerce helpdesk

If your reading of any cell differs from current product or pricing reality, email amit@richpanel.com and we will update it. The goal is to be accurate, not to win a column we have not earned. Gladly's pricing in particular is quote-based; confirm your total annual cost in writing, including the AI agent, before you compare.

The honest read of this table: every platform here can resolve and execute actions to some degree, so raw capability is no longer the only differentiator. The two columns that actually separate the field for a Gladly shopper are pricing transparency and how AI-native the architecture is. Gladly, Kustomer, Zendesk, and Gorgias all layer AI onto an existing helpdesk model and meter it in their own way. Richpanel is the outlier on both: visible per-conversation economics and a platform rebuilt around the agent. Whether that outlier position is an advantage depends entirely on your budget and what your support is actually for.

Where each one wins

The strength I would actually send a buyer toward.

For each competitor, here is a specific situation where it is the better choice than Richpanel. If your situation matches, take it seriously.

Gladly

Gladly has the most distinctive, customer-centered experience on this list, the strongest people-first model in premium retail, and deep voice support, and it carries the credibility of marquee names like Nordstrom, HOKA, UGG, and Ulta. Choose Gladly over Richpanel if you are a premium or luxury retail brand whose support is the relationship, where a customer spending heavily expects a high-touch, deeply personalized concierge experience and a human in the loop on valued conversations. For that brand the no-tickets timeline is not a quirk, it is the whole point: every agent sees the full relationship, and the model is built to make service feel seamless and personal. If voice is central to how you serve, and you have the budget for a high-touch enterprise platform, Gladly is built for exactly that surface, and it is one we lose to.

Kustomer

Kustomer is the most CRM-first platform on this list, organizing support around a rich customer data model and built for high-volume B2C operations. Choose Kustomer over Richpanel if you want a unified customer data layer at the center of support, you want every team working from one richer profile across the customer journey, and you prefer AI that assists your reps rather than replaces the frontline, and you have the team to operate a CRM-style platform. Its data model and channel breadth are a real edge for that buyer. The trade-off is that its AI is framed as supporting reps rather than resolving autonomously, and voice, SMS, and HIPAA are paid add-ons, so model the full stack before you compare.

Zendesk AI

Zendesk is the broadest overall customer service platform on this list, spanning use cases far beyond ecommerce CX, with a vast app marketplace of third-party integrations and a mature, separately-sold QA product. Choose Zendesk over Richpanel if you are a large organization standardizing one vendor across many functions (IT service, internal help desks, large-enterprise workflows) and you value that breadth over AI-native resolution depth, or if its proven-platform reputation is what your leadership needs to sign off. The trade-off is that Zendesk's AI is a paid add-on and its QA is a separate product, so the bill stacks. If you are weighing Zendesk specifically, our Zendesk alternatives comparison breaks down the full cost stack.

Gorgias

Gorgias is the most Shopify-native helpdesk in this group, with the widest ecommerce app marketplace and deep, fast order-operation actions built specifically for DTC stores. Choose Gorgias over Richpanel if you want the broadest ecommerce app ecosystem and you are comfortable with a per-ticket plan plus a per-AI-resolution fee on top, and an AI Agent that is a strong add-on rather than the core of the platform. For a Shopify store that values marketplace breadth above all, that is a real edge. If you are weighing Gorgias specifically, our Gorgias alternatives comparison breaks down the double-meter math.

Richpanel

For completeness, here is where we are the right answer, stated as plainly as the others. Richpanel is the AI-native helpdesk: a team of AI agents that runs customer service end to end, resolving 70-80% of conversations autonomously while your people handle the exceptions, on one bill at about $0.30 per AI-resolved conversation. Choose Richpanel if you are a DTC or mid-market brand that wants autonomous resolution proven on your own tickets before go-live, visible per-conversation economics instead of a quote-gated premium price, a CX Manager AI that reads your business and sets up the agents instead of a vendor consultant doing it for you, transparent evals your CX team owns with every regression visible, multi-brand support in one workspace, and a resolution guarantee with money attached (50% resolution in 30 days or your money back). In production that has looked like a wellness brand whose AI sends 60% of every customer message at 4.43 out of 5 CSAT, higher than its own human team's 4.25 average, with a median first response of 28 seconds.[5] Where we are weaker than Gladly: we are not built for the luxury concierge model, we do not have Gladly's people-centered timeline or its native voice depth, and we are younger and less established in premium retail, so if "people-centered experience for a high-touch luxury brand" or "deep native voice" is your top criterion, Gladly is the fair choice.

A decision tree, not a verdict

Match your situation to the shortlist.

There is no single best Gladly alternative. There is a best one for your channels, your ticket mix, your budget, and what your support is for. Map yourself to a line below.

Notice that the right answer flips on facts about you (your budget, your ticket mix, what your support is for), not on which vendor wrote the article. That is what a real comparison is supposed to do. If a single name appeared on every line, you would be reading marketing again. Note too that one line here says stay with Gladly, because for a high-touch premium retailer, it usually is the right call.

Run these before you switch

Six tests that cut through the pitch.

Whichever shortlist you land on, these six tests separate platforms that resolve from platforms that demo well. The first one is the one most Gladly shoppers skip and most regret skipping. For the full version, see our 40-question vendor RFP template.

1. Get the total annual cost in writing, including the AI.

If pricing is quote-based, the quote is the contract. Ask for the all-in number, including the AI agent and every channel add-on, and compare it against a per-conversation model where the cost is visible up front.

2. Ask how many tickets the AI resolves with no human touch.

Assist and resolve are different jobs. Ask for the share of support tickets closed autonomously with a confirmed outcome, not the share the AI touched. That is how you tell a tool that only assists from one that manages customer support through to resolution.

3. Run the agent on 100 of my historical tickets.

Ask for per-response accuracy and a walk-through of the failures. A vendor that will not do this is selling a demo, not production.

4. Show me a refund executed as a tool call, not free text.

Ask to see the typed parameters and the policy constraints. Free-text "I'll refund you" with no validation layer is how a bot sells a car for one dollar.

5. Is the AI the core of the platform, or a layer on top?

Ask how the agent is wired into the data model and who configures it. An AI bolted onto an existing helpdesk behaves differently from one the platform was rebuilt around.

6. Connect me with three customers like me, live within your timeframe.

Reference customers at your size and vertical are a more reliable signal than any ranking, including this one.

How this comparison is limited

What this guide cannot tell you.

An honest comparison names its own blind spots. Three apply here.

The claim this guide is willing to stand behind is narrow and defensible: Gladly's experience is rarely the reason teams shop, the premium quote-based pricing and the hybrid AI core usually are, and a vendor's willingness to prove accuracy on your own tickets is the single most predictive signal you can test before signing.

Frequently asked

Leaving Gladly, in plain English.

Why do teams look for Gladly alternatives if Gladly works well?

Rarely because the Gladly experience falls short. Gladly's people-centered, no-tickets model is one of the most loved in premium retail, built around a single lifelong conversation per customer instead of a ticket number. The two reasons teams shop are budget and how AI-native the platform really is. Gladly is positioned at the premium, enterprise end with quote-based pricing, so smaller and mid-market teams often find it out of range. And its AI agent, Gladly Sidekick, sits on a hybrid helpdesk-plus-AI core rather than a platform rebuilt around the agent, so teams that want autonomous resolution as the default rather than an assist sometimes look for an AI-native option. If your budget is tighter or you want the AI to resolve most of the volume on its own, a different model can fit better.

How much does Gladly cost in 2026?

As of June 2026, Gladly does not publish a per-seat price. Pricing is quote-based and sales-gated, and the platform is positioned at the premium, enterprise end of the market, with marquee retail customers like Nordstrom, HOKA, UGG, and Ulta. The practical implication is that you cannot model your bill without a sales conversation, and the floor tends to be high relative to mid-market alternatives. If budget predictability matters, ask for the total annual cost in writing, including the AI agent, and compare it against a per-conversation model where the cost is visible up front.

Is Gladly's no-tickets, customer-centered model better than a ticketing system?

For the right brand, yes, and it is the reason Gladly is loved by premium retailers. Organizing support around the customer and one lifelong conversation, rather than around disposable ticket numbers, makes high-touch, personalized service feel seamless, which is exactly what a luxury or premium brand wants. The trade-off is that the model is built for human-led, relationship-heavy service, so if your real goal is to automate a high volume of repetitive order-status, returns, and subscription questions, a platform built around autonomous AI resolution may serve that goal more directly. Neither model is universally better. Match it to whether your support is high-touch relationship work or high-volume repeat work.

Can I keep Gladly and just add a different AI agent?

Partly. Gladly's AI agent, Sidekick, is built into Gladly's own customer-centered data model, so the deepest in-platform behavior is hard to match from outside. You can layer some third-party automation on top, but in practice teams that want a different AI model usually move to a platform that owns its own inbox and resolution loop rather than bolting a second agent onto Gladly. The honest question is whether you are keeping Gladly for its people-centered experience and voice, in which case Sidekick is the path of least resistance, or whether your priority is autonomous resolution of repeat work, in which case an AI-native platform is worth comparing on its own terms.

Which Gladly alternative is best for an ecommerce brand?

For a DTC or mid-market ecommerce team, the deciding factors are usually action depth on order operations (refunds, cancellations, subscription and address edits), proof of accuracy on your own tickets before go-live, and pricing you can model without a sales gate. Richpanel is built for that profile with per-conversation economics and a pre-launch eval on your historical tickets. Gladly remains the strongest option if you are a premium retail brand that wants a people-centered, no-tickets experience and have the budget for a high-touch enterprise platform. Kustomer fits if you want a CRM-first data model with AI assisting reps, Zendesk if you need breadth across many functions, and Gorgias if you want the most Shopify-native ecommerce helpdesk. Match the platform to your ticket mix, not to a ranking.

What are the main alternatives to Gladly?

They group by what you want. For a like-for-like helpdesk with a shared inbox, live chat, and a knowledge base, the closest customer service software is Kustomer, Zendesk, Freshdesk, Zoho Desk, and Help Scout. For ecommerce specifically, Gorgias is the Shopify-native option. If you want a people-centered model like Gladly's, Kustomer's CRM-first approach is the nearest in spirit. And if you want the helpdesk and the AI agent rebuilt as one AI-native platform that resolves the repeat work on one bill, Richpanel is built for that. Most match Gladly on the basic key features like a ticketing system and live chat, so score them on whether the AI resolves autonomously and how the pricing is structured.

Is there a free Gladly alternative?

Yes. Zoho Desk and Freshdesk offer free or low-cost entry tiers, HubSpot Service Hub has a free plan, and most vendors offer a free trial so you can test on real conversations. Those free tiers suit smaller teams handling low volume through a shared inbox, live chat, and a basic knowledge base, but they cap the automation and the AI. If you are leaving Gladly because its premium quote-based pricing was out of range, model the all-in cost of any alternative at your real resolved-conversation volume, because a cheap base seat with a per-resolution meter on top can still cost more than flat per-conversation pricing.

What should a Gladly alternative actually do?

More than personalize a human-led conversation. A real alternative handles customer interactions across every communication channel, reads the customer's message, pulls the answer from your knowledge base, and resolves routine customer inquiries end to end across live chat, email, and social, taking the action the request needs rather than drafting a reply for a human. It should give your agents one shared inbox with full customer context, offer self-service options and knowledge base management that actually resolve instead of looping website visitors back to a search box, and hand off cleanly for personalized support when judgment is required. The test is confirmed resolution on your own tickets, because that is what lifts customer satisfaction, not a feature list.

Sources & references

Where the claims come from.

Inline citations [1]–[5] map to the entries below. Vendor product and pricing pages used to source matrix rows are linked inline in the table.

  1. Gladly, product and platform. Gladly's people-centered, no-tickets model (one lifelong conversation per customer rather than ticket numbers), the gladly.ai positioning, and the Gladly Sidekick AI agent. gladly.com
  2. Gladly, pricing positioning. Gladly's pricing is quote-based and sales-gated, positioned at the premium / enterprise end of the market alongside retail customers such as Nordstrom, HOKA, UGG, and Ulta. No public per-seat price; request a written quote before modeling. gladly.com/pricing
  3. Richpanel buyer demo dataset (April to May 2026). 69 recorded inbound demo calls. The observations on premium pricing pressure, the people-centered preference, and AI-native architecture trade-offs are drawn from this dataset. Underlying call data is confidential; aggregate counts are publishable. Methodology available on request via amit@richpanel.com.
  4. Richpanel platform and pricing. The AI-native helpdesk model, the CX Manager AI, per-conversation economics at about $0.30 per AI-resolved conversation, and the 50% resolution in 30 days money-back guarantee. richpanel.com/pricing
  5. Richpanel production case study (wellness brand). AI sends 60% of every customer message at 4.43/5 CSAT, above the brand's human-team average of 4.25, with a median AI first response of 28 seconds. richpanel.com/case-studies/wellness

Version history, v1.0 (2026-06-18): initial publication. Matrix cells are a snapshot of public vendor product and pricing documentation as of the publication date.

Before you re-sign with Gladly, get the quote and run the eval.

30 minutes. We connect Richpanel to your store, model your real resolved-conversation volume against visible per-conversation pricing, and run our pre-launch eval against 100 of your historical tickets so you see per-response accuracy. Then weigh it against Gladly's quote and AI core. If the numbers favor staying, stay.

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