HelpDesk Picker › Compare › Helply vs Helpshift

Helply / GrooveHQ vs Helpshift: Helpdesk Software Comparison 2026

Helply and Helpshift are both helpdesk and customer support platforms, but they are built for different operating models, budgets, and team workflows. This comparison reviews pricing, AI and automation, integrations, use cases, migration considerations, and practical buying trade-offs.

Answer-first summary

Helply vs Helpshift: choose Helply if you need teams that prioritize ['ai-native b2b support platform', 'no seat-based pricing', 'outcome-based ai model']; choose Helpshift if you need teams that prioritize ['in-app support for mobile', 'strong for gaming', 'sdk-based integration']. Helply lists free platform / AI outcome model; Helpshift lists custom MAU / quote pricing. Verify current vendor pricing and AI add-ons before budgeting.

Quick verdict

Helply is a stronger fit for teams that prioritize ['ai-native b2b support platform', 'no seat-based pricing', 'outcome-based ai model']. Helpshift is a stronger fit for teams that prioritize ['in-app support for mobile', 'strong for gaming', 'sdk-based integration']. Use the comparison below to check pricing source, AI scope, migration complexity, and integrations before choosing.

Brand naming and legacy search terms

Product names in helpdesk and ITSM change faster than buyer search behavior. HelpDeskPicker keeps current names and high-intent legacy names together so comparisons remain useful for users searching either version.

  • Helply (formerly GrooveHQ): Helply is the current brand for the Groove + InstantDocs rebrand. Buyers may still search for Groove, GrooveHQ, Groove HQ, or GroveHQ, so the canonical Helply profile keeps these legacy names visible for search intent and migration research. Legacy terms: Groove, GrooveHQ, Groove HQ, GroveHQ.
  • Helpshift: Helpshift is the preferred capitalization. HelpShift remains a common historical spelling in searches and migration discussions. Legacy terms: HelpShift, Helpshift support.

Pricing comparison

Helply lists free platform / AI outcome model; Helpshift lists custom MAU / quote pricing. Treat this as a starting point, not a full total cost estimate. Real pricing can change with seats, AI usage, channels, reporting, implementation, marketplace apps, and data migration needs.

FactorHelplyHelpshift
Starting pricefree platform / AI outcome modelcustom MAU / quote pricing
G2 rating4.54.4
Best fitSMBSaaS / Chat
Founded20112011
HQRemote (USA)San Francisco, USA
Customers8,000+3,000+
Known clientsBootstrapped SaaS companies, small support teamsBlizzard, Microsoft Gaming, Supercell, Zynga

AI and automation

Helply

Basic — some AI reply suggestions added in recent updates.

Helpshift

AI-powered in-app bots and smart routing.

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.

Integrations

Helply is commonly evaluated by teams that prioritize ['ai-native b2b support platform', 'no seat-based pricing', 'outcome-based ai model']. Helpshift is commonly evaluated by teams that prioritize ['in-app support for mobile', 'strong for gaming', 'sdk-based integration']. Before choosing, check native integrations for your CRM, ecommerce platform, chat tools, telephony, BI stack, identity provider, and data warehouse.

When to choose Helply

Choose Helply when you need teams that prioritize ['ai-native b2b support platform', 'no seat-based pricing', 'outcome-based ai model'].

  • ['AI-native B2B support platform', 'No seat-based pricing', 'Outcome-based AI model']

Check these trade-offs before rollout:

  • ['Newer positioning after Groove', 'Best fit for B2B companies', 'Outcome pricing needs fit validation']

When to choose Helpshift

Choose Helpshift when you need teams that prioritize ['in-app support for mobile', 'strong for gaming', 'sdk-based integration'].

  • ['In-app support for mobile', 'Strong for gaming', 'SDK-based integration']

Check these trade-offs before rollout:

  • ['Niche mobile focus', 'Complex SDK integration', 'Not for non-mobile']

Migration considerations

If you are moving from Helply to Helpshift, or from Helpshift to Helply, 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.

Review methodology and disclosure

Reviewed by Dmytro Lazarchuk, founder of Help Desk Migration. HelpDesk Picker is an independent software comparison project connected to Help Desk Migration. Some pages link to HDM migration services, but platform rankings and comparison notes are based on public product information, vendor documentation, pricing pages, and visible feature evidence. Read the methodology.

FAQ

What is the main difference between Helply and Helpshift?

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.

Is Helply better than Helpshift?

Not universally. Helply can be better for some teams, while Helpshift can be better for others. The right choice depends on your support channels, team size, budget, automation needs, and existing software stack.

Can I migrate data between Helply and Helpshift?

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.

Which platform is cheaper?

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.

Related comparisons