Plain vs Gladly: Helpdesk Logiciel Comparaison 2026
Plain and Gladly are both helpdesk and support client platforms, but they are built for different operating models, budgets, and team workflows. This comparaison aviss pricing, IA et automatisation, integrations, use cases, migration considerations, and practical buying trade-offs.
Verdict rapide
Plain is usually a stronger fit for SaaS / Chat teams that value API-first, Developer, Modern. Gladly is usually a stronger fit for Entreprise teams that value B2C, People-centric, Entreprise. Based on the available G2 rating in this dataset, Plain has the higher user rating.
Tarifs comparaison
Plain starts at Custom pricing, while Gladly starts at from $150/agent/mo. Treat this as a starting point, not a full total cost estimate. Real pricing can change with agent count, AI features, phone or messaging channels, advanced reporting, implementation, marketplace apps, and data migration needs.
| Factor | Plain | Gladly |
|---|---|---|
| Starting price | Custom pricing | from $150/agent/mo |
| G2 rating | 4.9 | 4.5 |
| Best fit | SaaS / Chat | Entreprise |
| Founded | 2022 | 2014 |
| HQ | London, UK | San Francisco, USA |
| Customers | 200+ | 1,000+ |
| Known clients | Developer-centric SaaS companies | Crate & Barrel, Ulta Beauty, Ralph Lauren, Warby Parker |
IA et automatisation
Plain
AI reply drafts and ticket classification via API.
Gladly
Gladly AI — voice AI agent for order status and refunds, automated routing by customer lifetime value.
For AI buying decisions, compare not only feature names but also automation limits, handoff quality, knowledge base dependency, pricing per resolution or add-on, reporting, and how much configuration your team needs before AI becomes useful.
Intégrations
Plain is commonly evaluated by teams that need API-first, Developer, Modern. Gladly is commonly evaluated by teams that need B2C, People-centric, Entreprise. Before choosing, check native integrations for your CRM, ecommerce platform, chat tools, telephony, BI stack, identity provider, and data warehouse.
When to choose Plain
Choose Plain when its pricing model, workflow depth, and operational fit match your team better than Gladly. It may be the better option if the following strengths are central to your support strategy:
- API-first support
- Built for developers
- Modern architecture
- 4.9 on G2
Watch out for these limitations before committing:
- Developer-focused - not for non-technical teams
- Very new
When to choose Gladly
Choose Gladly when its ecosystem, product direction, and implementation model are a better fit for your team than Plain. It may be the better option if these strengths matter most:
- Radical 'people-centric' approach
- Great for B2C
- Unified timeline
Check these trade-offs carefully before rollout:
- Very high entry price
- Not ideal for B2B/ITSM
Migration considerations
If you are moving from Plain to Gladly, or from Gladly to Plain, the main challenge is usually not just ticket export. You need to plan how users, organizations, companies, comments, private notes, attachments, tags, statuses, custom fields, knowledge base articles, and record relationships will map into the new system.
Before migration, verify API limits, attachment handling, deleted or archived records, field mapping, ticket status logic, agent matching, knowledge base structure, and whether you need a delta migration close to go-live.
FAQ
The main difference is usually fit: pricing model, workflow depth, integrations, AI capabilities, implementation complexity, and the type of support team each product serves best.
Not universally. Plain can be better for some teams, while Gladly can be better for others. The right choice depends on your support channels, team size, budget, automation needs, and existing logiciel stack.
Yes, in many cases you can migrate tickets, users, companies, comments, attachments, tags, custom fields, and knowledge base data. The exact scope depends on each platform's API and export/import limitations.
Based on listed starting prices, neither platform clearly is cheaper at entry level. However, total cost depends on add-ons, AI usage, number of agents, support channels, and implementation work.