Decagon is a sophisticated enterprise AI concierge built around Agent Operating Procedures, deep integrations, and high-touch deployment. ify takes a different approach: connect the helpdesk you already use, define specialist agents around the work they know best, and orchestrate them together when a customer problem crosses multiple domains.
Last verified: September 2026. Decagon pricing and contract figures are based on Decagon’s published pricing model descriptions plus current third-party procurement data where list pricing is not public.
Quick answer
Decagon
Decagon is a well-reviewed enterprise AI concierge platform built around Agent Operating Procedures, broad integrations, and a high-touch implementation model. It does not publish list pricing, and current Vendr procurement data shows a median annual contract of about $432,750, with observed contracts ranging from roughly $105,000 to $923,183. Decagon publicly supports both per-conversation and per-resolution pricing and says most customers choose per-conversation pricing.
ify
ify is enterprise-grade with self-serve options, uses specialist-agent orchestration for multi-intent support work, and prices on resolved outcomes rather than requiring a sales-led enterprise contract to get started.
Arrives
Customer writes in
Email, WhatsApp, chat or your helpdesk — one memory across all of them.
Resolves
ify checks systems and acts
Looks up the account, takes the approved action, answers the customer.
Lands
A real ticket in your helpdesk
Native ticketing, so SLAs, reporting and the audit trail stay where they already are.
What Decagon reviewers actually say
4.7 / 5
Decagon’s G2 rating, from roughly 30 reviews — a small sample, but consistently positive about implementation support, integrations, and workflow flexibility.
What reviewers praise
What reviewers flag
Decagon prices conversations and resolutions differently
Decagon publicly confirms two pricing models: per-conversation and per-resolution. It also says the majority of customers choose per-conversation pricing. Under that model, the unit of billing is the conversation rather than only a successful resolution. Decagon does not publish the rates on its site, so actual pricing is custom and should be confirmed directly with its sales team.
Third-party sources have reported negotiated per-resolution rates for some customers, but this page does not present those as Decagon list pricing because Decagon does not publicly publish the rates.
One honest exception: if you want a deeply configured enterprise AI concierge, a dedicated implementation team, and natural-language Agent Operating Procedures built around complex support workflows, Decagon is designed for exactly that buying model.
Sources: Decagon’s published product and pricing-model documentation, G2’s current review data, and Vendr procurement data, verified September 2026.
Security & compliance
Enterprise AI support needs the same security and governance scrutiny as any other system handling customer data. ify publishes SOC 2 Type II, ISO 27001, HIPAA, and GDPR information through its trust center, with the same platform available whether you start self-serve or through an enterprise conversation.
GDPR · HIPAA compliant · ISO certified company · AICPA SOC 2
Decagon currently publishes SOC 2 Type II, ISO 27001, HIPAA, GDPR, and PCI compliance information. Both products should be evaluated against your organization’s specific security, data-handling, and deployment requirements.
The same ticket, two agents
Two issues in one message — a useful way to compare how each platform organizes the work.
Decagon’s path
The customer-facing agent identifies the intents
Decagon uses its concierge and Agent Operating Procedures to determine the right workflows, tools, and actions for the request.
AOPs guide the work across systems
The agent can follow configured procedures, use integrations, take actions, and change procedures as the conversation evolves.
Pricing follows the contracted model
Customers can be contracted on per-conversation or per-resolution pricing, with actual rates custom quoted.
ify’s path
The message is split into its real sub-problems
Refund and shipment delay are recognized as two distinct issues.
Specialist agents work both in parallel
Each resolves its piece; results merge into one coherent reply.
Closes as a timestamped ticket
In your existing helpdesk — your SLA clock, not a new one.
Same request. The difference is organizational: Decagon centers the customer interaction around an AOP-driven concierge, while ify explicitly decomposes multi-intent work across specialist agents and recombines the result.
Available now
Complex conversations
Complex customer conversations often contain more than one intent: a refund plus a shipping issue, a product question plus an account change, or a billing problem mixed with a technical request. ify is designed to decompose those conversations into distinct pieces of work instead of treating the entire ticket as one undifferentiated task.
Parallel specialists
ify's multi-agent orchestration changes that math. The moment a message comes in, it's read for what it actually contains, split into its real sub-problems, and handed to the specialist agents built for each one — running at the same time, not in a queue — before their answers are woven back into a single, coherent reply the customer never has to know was a team effort.
Operating model
It drops in without disturbing your existing setup: specialist agents keep their own instructions, tools, and guardrails, while orchestration decides when several of them should contribute to one customer outcome. Decagon takes a different approach through its customer-facing concierge, Agent Operating Procedures, and orchestrated workflows — so the architectural question is which operating model better matches your support organization.
Adding ify to your helpdesk
Connect your helpdesk
Freshdesk, Zendesk, Intercom, HubSpot or Salesforce — no migration required.
ify reads what you've already built
Macros, saved replies and Help Center articles are indexed automatically.
Set your guardrails
Decide what ify can resolve on its own, and where a human approves first.
Go live, channel by channel
Email, WhatsApp, chat and social reconnect individually — no cutover weekend.
The practical difference is the buying motion: ify can be evaluated through self-serve setup, while Decagon is positioned around a sales-led enterprise deployment.
Side by side
Stated plainly — including where Decagon's implementation depth genuinely wins. A comparison that only ever favors one side isn't one you should trust.
Last verified: September 2026
Getting started
Pricing model
Observed contract values
Billing unit
Architecture
Helpdesks it runs on
G2 rating
Published resolution rate
Deployment model
Decagon pricing-model descriptions come from Decagon; observed contract values come from Vendr; G2 rating data comes from G2; resolution figures are vendor case-study claims. Confirm current commercial terms directly with Decagon before deciding.
If you can't find what you're looking for, .
Connect any of five helpdesks and evaluate ify on real support work before committing to a large enterprise rollout. Use specialist agents, shared context, and resolution-based pricing inside the stack you already run.
14-day free trial · Setup under 20 min · Cancel anytime
Last verified: September 2026. Decagon product and pricing-model descriptions are based on Decagon’s published materials; contract values come from Vendr; review data comes from G2. Commercial terms may have changed since. Decagon is a trademark of its respective owner. ify is not affiliated with or endorsed by Decagon.
