Agentic Index
Decagon vs Fin (2026)
Both vendors last verified
The pricing models are as different as the products. That verdict is the Agentic Index coverage score, graded from each vendor's own published materials.
Fin charges $0.99 per outcome, and as a standalone agent on another helpdesk it carries a 50 outcome monthly minimum of $49.50. Decagon is built for support teams, integrates deeply with their tools and quotes through sales. Fin is the one you can price before the call. Decagon is the one you configure to a support operation that has outgrown packaged tooling.
This comparison is published by Agentic Index, an independent agentic AI vendor research platform. Decagon and Fin are each graded against the same 14 capability Agentic Index taxonomy, from the vendor's own public materials under the Agentic Index verification standard, alongside 1,084 researched vendors. No vendor pays for placement and no vendor has reviewed this page. How this evidence is graded
Choose Decagon if
- Deep integration into an existing support toolchain is the requirement and you want it configured to you.
- Customer context should carry across sessions and channels.
- Your volume and complexity justify a sales led implementation rather than a packaged product.
Choose Fin if
- You want to model cost before committing, and $0.99 per outcome is a number you can forecast.
- Simulation based testing before deployment is a requirement.
- You are already on Intercom, or you want to start standalone at $49.50 a month without a sales cycle.
| Feature | D Decagon |
F Fin |
|---|---|---|
| Action & orchestration | ||
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Integrations & Tool Calling Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools. |
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DecagonIntegrations & Tool Calling Connectors span CRM, helpdesk and ticketing (Salesforce, Intercom, Zendesk), knowledge bases (Confluence, Contentful, Kustomer), and CPaaS and telephony (Amazon Connect, RingCentral, SIP trunking), plus custom endpoints and MCP connectivity for any other system. Agents both retrieve data and take action. Sourcedecagon.ai/product/integrationsread 2026-09-05 |
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FinIntegrations & Tool Calling Fin runs on the customer's existing helpdesk across Intercom, Salesforce, HubSpot, Freshworks, Dixa, Front, Zoho, Sprinklr and Gorgias, adds Data Connectors for live external data, takes action to update external systems, and spans messaging and telephony channels. Sourcefin.ai/pricingread 2026-09-05 |
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Workflow Orchestration Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps. |
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DecagonWorkflow Orchestration Agent Operating Procedures turn natural language inbound and outbound workflows into executable agent logic that pulls live data and triggers actions across connected systems. Versions are tracked in Git, and rollout is staged across agent versions. Sourcedecagon.ai/product/aopread 2026-09-05 |
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FinWorkflow Orchestration Procedures are configured multi-step workflows the agent runs end to end, including branches that end in a handoff to a human or into a workflow. Workflow automations on the Intercom helpdesk and Operator, a separate agent for customer operations work, sit alongside. Sourcefin.ai/pricingread 2026-09-05 |
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Triggers & Channel Coverage How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools. |
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DecagonTriggers & Channel Coverage Chat, voice and email run on one intelligence layer. Inbound calls route over SIP and CPaaS platforms, email comes in through Zendesk and Intercom, live chat escalates through Zendesk Sunshine and Salesforce, and outbound and proactive agents are supported as a core feature. Sourcedecagon.ai/product/overviewread 2026-09-05 |
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FinTriggers & Channel Coverage Channels include Voice, Email, Messenger, Slack, WhatsApp, SMS, Instagram, Facebook Messenger and Fin over API. Tickets, cases and emails come in from the connected helpdesk, and a proactive outbound suite runs on the Intercom helpdesk. Sourcefin.ai/pricingread 2026-09-05 |
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| Knowledge & context | ||
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Knowledge Grounding & RAG Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers. |
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DecagonKnowledge Grounding & RAG Decagon maintains the agent's own knowledge base, filled by sync from customer systems including Confluence, Contentful and Kustomer. Suggestions keeps it current by finding gaps from conversations, ranking their impact on coverage and issuing monthly content updates. Traces name the knowledge articles the agent referenced. The knowledge base persists between conversations. Sourcedecagon.ai/product/suggestionsread 2026-09-05 |
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FinKnowledge Grounding & RAG Fin is trained on Knowledge Sources, Data Connectors, Procedures, Guidance and Categories, ingesting help center content from Intercom, Zendesk or Salesforce plus any public URL. The ingested content re-syncs every 24 hours for connected help centers and weekly for external web content. Sourcefin.ai/help/en/articles/13975777-pricing-and-usage-limitsread 2026-09-05 |
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Memory & State Persistence Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer. |
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DecagonMemory & State Persistence Memory is a named part of the agent engine. It holds customer context across sessions and channels alongside the customer's systems of record, with stated data portability and control, so a conversation started in chat continues by voice without repetition. Decagon does not publish how long memory is kept or how to delete it for one customer. Sourcedecagon.ai/product/overviewread 2026-09-05 |
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FinMemory & State Persistence Context carries within a conversation and across a voice call, and Fin passes full customer context to a human on escalation. No memory layer with a stated scope or lifetime is named, and the persistence Fin advertises is a learning flywheel that feeds conversations into model improvement, not a memory store that can be located or deleted for a given customer. Sourcefin.ai/capabilitiesread 2026-09-05 |
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| Control & trust | ||
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Human Oversight & Guardrails Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls. |
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DecagonHuman Oversight & Guardrails Guardrails can be configured for brand voice, escalation and hallucination. A supervisor model revises ungrounded responses before they are sent, bad actor detection escalates to a human, and Watchtower flags conversations for triage against criteria the customer sets. Oversight is automated gating and quality review after the fact, with no customer facing approval queue that holds an agent action until someone signs off. Sourcedecagon.ai/product/aopread 2026-09-05 |
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FinHuman Oversight & Guardrails Procedures carry deterministic controls and cross-team approvals, with multi-stage validation and approval workflows running before any action is taken, and Fin performs only actions the customer has explicitly configured and approved. Refund paths enforce eligibility windows, value thresholds and approval requirements, and Guidance bounds tone, scope and escalation. Sourcefin.ai/trainread 2026-09-05 |
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Security, Identity & Governance RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy. |
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DecagonSecurity, Identity & Governance Access controls include role based access control, SSO with Okta and Microsoft Entra, tamper protected audit logs and short lived scoped JWTs for agent access. Data is encrypted with AES-256 at rest and TLS 1.2+ in transit, DLP based redaction removes PII, and model providers are held to zero-day retention. Decagon shows SOC 2, ISO 27001, PCI DSS, HIPAA, CCPA and Data Privacy Framework marks and runs a live trust portal. SourceDecagon security page and trust.decagon.ai; decagon.ai/securityread 2026-09-05 |
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FinSecurity, Identity & Governance Intercom supports SSO with Okta, Azure AD and OneLogin, plus 2FA, SCIM provisioning and IP restrictions, and holds SOC 2, ISO 27001, ISO 42001, ISO 27701, AIUC-1 and HIPAA. Sourcefin.airead 2026-09-05 |
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Observability & Auditability Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior. |
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DecagonObservability & Auditability Traces explain how and why the agent decided as it did at any point in a conversation, covering model calls, workflow triggers, the knowledge articles referenced, and runtime and latency figures. Watchtower reviews every conversation against criteria the customer defines and flags outliers for triage. Sourcedecagon.ai/product/overviewread 2026-09-05 |
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FinObservability & Auditability The Analyze stage includes Topics Explorer, CX Score quality scoring across every conversation, an Optimize Dashboard and configurable alerts, which measure what happened. No production trace showing why the agent acted as it did is described, and the view of Fin's reasoning sits inside Simulations, a test surface used before launch. Sourcefin.ai/analyzeread 2026-09-05 |
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Deployment & Data Residency Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting. |
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DecagonDeployment & Data Residency The platform runs on multi region infrastructure with autoscaling and automatic failover for resilience. There is no customer selectable region, VPC, single tenant or on premises option, so where data sits depends on Decagon's architecture, not the customer's choice. The product is delivered only as SaaS hosted by Decagon. Sourcedecagon.ai/securityread 2026-09-05 |
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FinDeployment & Data Residency Customer data is hosted in the United States, the European Union or Australia, chosen to meet the customer's residency requirement, with redundancy across regions behind a 99.8% uptime SLA. Sourcefin.airead 2026-09-05 |
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| Solution readiness | ||
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Prebuilt Agents, Templates & Packs Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value. |
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DecagonPrebuilt Agents, Templates & Packs Customers build agents by writing Agent Operating Procedures in natural language, or Duet generates them from the customer's own conversation transcripts, applying Decagon's deployment learnings behind the scenes. The seven industry pages are positioning and case studies, not solutions to adopt. There is no template gallery, named prebuilt agent set, blueprint library or industry pack. Sourcedecagon.ai/product/aopread 2026-09-05 |
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FinPrebuilt Agents, Templates & Packs Fin ships named role-specific agents that customers adopt as units, Fin for Service, Fin for Sales and Fin for Ecommerce, each with pre-trained skills, alongside packaged helpdesk editions for Salesforce, Freshdesk and HubSpot, a Simulation library and the AI Agent Blueprint. Sourcefin.ai/capabilitiesread 2026-09-05 |
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| Platform extensibility | ||
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Model Flexibility & Routing Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys. |
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DecagonModel Flexibility & Routing The agent engine runs on a network of frontier and specialized models, with OpenAI and Anthropic named as providers held to zero-day retention, and model redundancy is a platform property. Routing happens inside Decagon, and customers and admins cannot select the model that powers the product. Sourcedecagon.ai/product/overviewread 2026-09-05 |
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FinModel Flexibility & Routing Answers come from Fin's own proprietary model family, the Apex model built for customer support and Apex Flash for low latency voice, under the patented Fin AI Engine. No customer or admin model selection is described. Sourcefin.ai/pricingread 2026-09-05 |
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APIs, SDKs & MCP Extensibility Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems. |
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DecagonAPIs, SDKs & MCP Extensibility A REST API for the platform sits at api.decagon.ai, authenticated with a customer issued key passed as a bearer token, and rate limited. An API key can be generated from the Developer page of the Decagon dashboard. The documentation at docs.decagon.ai sits behind a customer login, nothing on the public site links to it, and the public Integrations page describes only connections into the customer's own systems. SourceDecagon developer documentation at docs.decagon.airead 2026-09-05 |
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FinAPIs, SDKs & MCP Extensibility The Fin API Platform exposes the Apex generative, Retrieval and Reranker models individually or as a complete RAG pipeline for building custom agents, and the Fin Agent API embeds Fin in a customer's own product without the Intercom messenger. API is a first-class deployment channel, and the versioned REST API comes with an OpenAPI specification, interactive reference and changelog. A help center note says Fin cannot serve conversations created through the API, but it predates the API Platform and covers only that one path. Sourcefin.ai/api-platformread 2026-09-05 |
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Testing, Debugging & Optimization Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment. |
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DecagonTesting, Debugging & Optimization Testing & QA and Experiments are customer facing products. Agents are validated before launch with end to end simulated conversations and unit tests. Live traffic is then routed across agent versions to A/B test changes and measure their effect on CSAT, deflection rate and other metrics at scale, with readable results the customer can compare. Sourcedecagon.ai/product/overviewread 2026-09-05 |
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FinTesting, Debugging & Optimization Customers get a test suite covering Simulations, Regression Tests, Previews and Audience Testing, run against their own configured agent, with results readable before deployment. Sourcefin.ai/pricingread 2026-09-05 |
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| Specialist automation | ||
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Browser & Computer Use Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone. |
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DecagonBrowser & Computer Use The agent acts only through API and MCP connectors, CRM and ticketing integrations, CPaaS platforms and SIP telephony. It does not control a browser or virtual desktop or operate software that lacks a programmatic interface. Sourcedecagon.ai/product/integrationsread 2026-09-05 |
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FinBrowser & Computer Use Every deployment surface is a messaging, voice or API channel, and actions on external systems run through helpdesk connectors and Data Connectors. No browser control, virtual desktop or operation of software without a programmatic interface is described. Sourcefin.ai/pricingread 2026-09-05 |
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Pricing snapshot
Sourced from the Index pricing dataset · open each vendor's profile for full detail.
| Pricing | D Decagon |
F Fin |
|---|---|---|
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Entry price Lowest public entry point |
Contact sales | $0.99 per outcome |
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Pricing confidence How public the numbers are |
Contact only | Public, exact |
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Billing Primary billing axis |
Usage, per conversation or per resolution. Per conversation is the default and bills every interaction, and per resolution charges a higher rate only for conversations the AI fully resolves. | Outcomes, at $0.99 each, plus helpdesk seats when Fin runs inside Intercom. |
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Variable cost Workload / overage exposure |
High variable cost | High variable cost |
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Free tier / trial Try before you buy |
No free tier
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No free tierTrial
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Buying motion Self-serve vs sales call |
Sales call | Mixed |
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Pricing verified When this pricing was last checked |
Product updates
Newest first, each linked to its source.
Decagon
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· MCP / tool calling / API
The Personal Agent Consent & Trust Protocol (PACT), which Decagon open sourced with Instinct, builds on the Agent2Agent protocol and OAuth 2.0 so a business can verify which personal agent is calling and what the customer has authorized it to do.
Source -
· Agent capability
Decagon released Voice 3, a voice agent rebuilt so a fast conversational model listens and speaks while a stronger model handles reasoning, tools and guardrails in parallel.
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· Browser/computer use
Decagon introduced Browser Actions, a feature that allows its AI agents to access and complete tasks inside any web-based system.
Source
Fin
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· Human approval / guardrails
When a conversation needs a review, a piece of information or an approval, Fin now loops in a human teammate to approve, edit or take over, instead of escalating and leaving.
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· Observability / auditability
Intercom introduced custom reporting metrics that can be filtered by Fin AI Agent ratings or used to count escalations from AI agents to humans.
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· Observability / auditability
Intercom launched Evals and Releases for Fin, providing tools to test AI agent changes before deployment, control gradual rollouts, and monitor live conversations for quality.
Source
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