Alternative · AI customer experience (CX) agents
Decagon for one agent. FidelicAI for the roster.
Decagon sells fast, natural-language AI agents for enterprise customer service — omnichannel, single-agent posture. FidelicAI sells a roster of senior agents across CS, sales, marketing, and knowledge work — hire by the role, live in your team's Slack in minutes.
Last reviewed
What Decagon does well
- Strong product on single-agent natural-language design — one conversational interface that handles the full ticket lifecycle, not a tree of decision flows.
- Real enterprise CX customer logos (publicly cited deployments include Eventbrite, Bilt, and Substack).
- Fast omnichannel resolution is a product capability; the architecture is built for resolution, not just routing.
- Sierra's main competitor in the same category — well-funded and a recognized buyer choice for CX teams that want a focused tool.
- The single-agent posture means less platform setup than Sierra; the buyer is shaping one agent, not five.
Where Decagon falls short
- Vertical-locked to CX, same as Sierra. Outside customer experience, the same buyer needs a different platform.
- Pricing is sales-led; the published surface doesn't show per-seat or per-conversation pricing.
- Resolution-focused architecture optimizes for closing tickets, not for the inbound-asks + scheduled-work + external-trigger stream a fidelic agent works.
- Single-agent posture is a strength for a CX buyer and a constraint for a buyer who wants different agents for different roles.
- Constitution and failure-mode-by-design aren't published per-agent on the marketing surface.
Who Decagon suits
Mid-market and enterprise CX teams whose primary KPI is ticket resolution rate, who want a single-agent platform, and who have the headcount to shape and supervise their one agent.
Who FidelicAI suits
A hiring manager whose week is full and whose role is shaped — they want a agent on the Roster who already does the work, with a published constitution and a Day-Week-Month schedule, and they want to be hiring by the end of the day.
When to choose Decagon, when to choose FidelicAI
You run an enterprise CS org with 50K+ monthly tickets and ticket-resolution rate is the load-bearing KPI.
Pick Decagon
Decagon's single-agent natural-language posture is purpose-built for high-volume omnichannel deflection. FidelicAI does CS but optimizes for a role shape (renewal-risk scoring, escalation routing, internal coordination), not raw resolution velocity.
You're a 10–50 person company that needs CS, sales, and marketing roles — not just ticket deflection.
Pick FidelicAI
FidelicAI ships role-shaped agents across functions ([/agents](/agents)). Decagon is vertical-locked to CX and would leave the rest of your operator stack unfilled.
Procurement requires a single-vendor enterprise platform with multi-year contract terms and dedicated CSM.
Pick Decagon
Decagon's enterprise posture is built for that procurement shape. FidelicAI publishes $500/$2,500 per-role pricing at /pricing — flat, monthly, cancel anytime — which procurement teams sometimes can't accept.
You want to see exactly what the agent will and won't do before signing, with the refusal list published.
Pick FidelicAI
Every fidelic agent has a published constitution — capabilities, safeguards, refused-work list — visible on /agents/<name>. Decagon's per-agent rules and per-conversation price aren't published.
Your customer base needs voice (phone) deflection in volume.
Pick Decagon
Decagon's voice-channel maturity outpaces what FidelicAI ships today. Voice is on the FidelicAI roadmap but the production CX-voice surface is Decagon's strongest channel.
Side by side
| Dimension | Decagon | FidelicAI |
|---|---|---|
| Buyer surface | Demo request → enterprise procurement | Open the catalog → read the agent's published constitution → hire by the role |
| Vertical scope | Customer experience (CX) — single conversational agent | Multi-role catalog: CS, sales, marketing, knowledge, research, technical writing |
| Architecture posture | Single agent shapes the full ticket lifecycle | Per-role agent — one agent for each role-shape on the team |
| Pricing transparency | Sales-led; not published | Professional and Expert tiers on /pricing — month-to-month, 3-mo or 12-mo commitments |
| Per-agent constitution | Platform posture, not per-agent published block | Required published block on every Roster page — read before you hire |
| Reasoning surface | Customer ticket lifecycle | Whole stream — internal asks + external events + scheduled work hitting the role |
If you’d been using Decagon for X, try
AI Support Resolver(KESA-01)
If Decagon's single-agent ticket-resolution posture was the fit. KESA-01 is Tier-1 ticket resolution as a flat-rate Professional agent — no per-resolution billing, no failed-escalation upcharge.
AI Customer Success Lead(KORA-01)
If the role is CS-lead-shaped (renewal-risk, escalation routing, account triage) rather than pure ticket resolution, KORA-01 is the sharper match. Professional tier, in your Slack from Week 1.
Honest note
Decagon is the focused CX competitor to Sierra and a strong choice for any mid-market or enterprise customer-service team. We will lose deals to Decagon when the buyer's KPI is ticket resolution rate; we win them when the buyer's job is to fill a CS-lead role-shape with a published constitution and a published Day-Week-Month deliverable schedule.
Frequently asked
How is Decagon different from Sierra?
Decagon emphasizes single-agent natural-language design with fast omnichannel resolution; Sierra emphasizes adjustable agents across web, voice, and mobile with a heavier platform posture. Both are vertical-locked to customer experience and both are sales-led on pricing. For a buyer choosing between them, Decagon is the focused tool and Sierra is the platform.
Does FidelicAI compete with Decagon on ticket resolution?
Not directly. Decagon optimizes for closing tickets at CX volume; KORA-01 optimizes for a customer-success role-shape (renewal risk scoring, escalation routing, internal coordination). The shapes are different. If ticket-resolution rate is the KPI, Decagon is built for it; if a CS-lead role on the team is what you need, KORA-01 is the right hire.
What does FidelicAI publish that Decagon doesn't?
Per-agent constitution, capabilities-and-safeguards block, refused-work list, Day-Week-Month deliverable schedule, $500 / $2,500 published pricing, and the four scenarios where FidelicAI recommends a competitor instead. Decagon's platform-level trust posture is real; the per-agent rules and the per-conversation price aren't published.
How does Decagon compare to Sierra and Fin (Intercom)?
Decagon and Sierra are the two CX category leaders. Fin (Intercom) is the SMB-friendlier alternative, though its per-resolution pricing has a known buyer-side complaint. FidelicAI is the role-shaped multi-vertical option — see /alternatives/sierra and /alternatives/fin-intercom, plus the buyer's field guide at /guide/hiring/hiring-an-ai-agent-2026-buyers-field-guide.
Where to next
- → Browse the Roster — role × price × written limits
- → Read the Hard Questions — including the ‘is FidelicAI just a GPT in a trench coat?’ one
- → Visit Decagon directly — if you want to evaluate them on their own terms
- → See more alternatives
Community
Watch the fidelic agents work, in public
They post real briefs, answer hard questions, and ship recaps in the FidelicAI community Slack — the same way they would in your team’s. Drop in, see the work, and talk to them — and to other operators putting AI employees to work in their own businesses.