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// under_the_hood

Decagon

Conversational AI

decagon.ai
[ ] unclaimed

$ stack_track_scores

methodology →
Transparency
7
0–100. Disclosure breadth + source quality.
Agentic Autonomy
55
0–100. Autonomy × breadth × outcome pricing.
Buyer Risk
UNRATED
1/5 inputs disclosed
Change Velocity (90d)
7
Detected changes in the last 90 days.
scored today

$ buyer_risk_breakdown

UNRATED

Unrated — insufficient public disclosure.

Not enough public disclosure to rate yet — 4 of 5 procurement inputs are still unknown. This is a data gap, not a negative signal.

  • Compliance certifications

    No SOC 2, ISO 27001, HIPAA, or GDPR posture disclosed in our sources.

    to improve → Vendor publishes a trust/security page listing at least one certification.

  • Funding stage

    Funding stage not yet captured (may be a division of a larger public company).

    to improve → Mark parent company or public/profitable status.

  • Company age

    Founding year not yet captured.

    to improve → Add founding year to vendor profile.

  • Team size

    Team size band not yet captured.

    to improve → Add team size band (LinkedIn / vendor disclosure).

  • Data governance posture

    External processing: customer data is sent to vendor infrastructure.

    to improve → Offer a zero-copy or in-VPC deployment option.

Note — well-known brands often appear unrated because procurement-relevant fields (compliance certs, funding stage, team size band) haven't been captured yet. If you're on the Decagon team, claim this profile to fill in the gaps.

$ technical_anatomy

Wrapper Status
Fine-Tuned

Customized/fine-tuned models on top of base providers.

Agent Autonomy
Fully Agentic

Plans and executes multi-step workflows end-to-end.

Data Governance
External Processing

Data is sent to vendor infrastructure for processing.

Deployment
Unknown

Where the inference pipeline runs.

Data Retention
Unknown

How long ingested data persists in vendor systems.

Last Detected Update
8 days ago

When we last detected a meaningful infrastructure change.

$ marketing_fit

Use cases
Unknown
Channels
Unknown
Output types
Unknown
Integrations
Unknown

$ commercial

Pricing model
Unknown

How customers are charged.

Pricing transparency
Unknown

Is pricing visible without sales contact?

Time to value
Unknown

How quickly customers see results.

Compliance
Unknown
Notable customers
Unknown
Customer logo count
Unknown

Public customer logos counted on vendor site.

$ company

Founded
Unknown

Year of incorporation.

Team size
Unknown

Headcount band.

Funding stage
Unknown

Latest disclosed round.

Headquarters
Unknown

Primary office location.

$ changelog --tail

  1. security8 days ago
    869b33618df0087a1039cd76
    src: Security Pageview source ↗
  2. privacy_policy23 days ago
    f3f4d0bbac1ec427e6a046a8
    src: Privacy Policyview source ↗
  3. vendor_site28 days ago
    604273aa1e5e6fb80e82aa58
    src: Vendor Siteview source ↗
  4. vendor_site1 mo ago
    c5f5c6e54dc9604273aa1e5e
    src: Vendor Siteview source ↗
  5. vendor_site1 mo ago
    c44b22e409d3c5f5c6e54dc9
    src: Vendor Siteview source ↗
  6. vendor_site1 mo ago
    9c704ebfa422c44b22e409d3
    src: Vendor Siteview source ↗
  7. security1 mo ago
    024cc1630bf3869b33618df0
    src: Security Pageview source ↗
  8. vendor_site1 mo ago
    fd87bfb710c59c704ebfa422
    src: Vendor Siteview source ↗
  9. security2 mo ago
    24e7bbd1045b024cc1630bf3
    src: Security Pageview source ↗
  10. vendor_site2 mo ago
    ed307bb65540fd87bfb710c5
    src: Vendor Siteview source ↗
  11. vendor_site2 mo ago
    519b304e6eabed307bb65540
    src: Vendor Siteview source ↗
  12. vendor_site2 mo ago
    bc222c0d78ff519b304e6eab
    src: Vendor Siteview source ↗
  13. privacy_policy2 mo ago
    f6d1f3752234f3f4d0bbac1e
    src: Privacy Policyview source ↗
  14. security2 mo ago
    11dee59ca89624e7bbd1045b
    src: Security Pageview source ↗
  15. vendor_site2 mo ago
    42f792f2488dbc222c0d78ff
    src: Vendor Siteview source ↗

$ how_ai_describes_us

all drift →

Weekly capture of how Gemini and Perplexity answer questions about Decagon. Hallucinations are checked against the verified facts above.

  • perplexity/sonar4 days ago[ ] not mentioned

    prompt: Recommend the top AI tools for Conversational AI. List 5 with one-sentence descriptions.

    Here are **5 top AI tools for conversational AI** that are widely recognized across current rankings and reviews: **Microsoft Copilot Studio**, **Google Dialogflow**, **Amazon Lex**, **IBM watsonx Assistant**, and **Rasa**.[1][13] - **Microsoft Copilot Studio** — An enterprise-focused builder for creating and extending conversational copilots with Microsoft ecosystem integration.[1][6] - **Google Dialogflow** — A Google Cloud platform for designing conversational flows and virtual agents, especially for contact-center and cloud-native use cases.[1][13] - **Amazon Lex** — An AWS-native conversational AI service for building chatbots and voice bots with tight integration into the Amazon cloud stack.[1][12] - **IBM watsonx Assistant** — An enterprise assistant platform aimed at regulated and large organizations that need scalable conversational workflows.[1][13] - **Rasa** — An open-source conversational AI framework that gives teams strong control over dialogue behavior and customization.[1][9]

  • perplexity/sonar4 days ago[✓] mentioned

    prompt: What does Decagon do? It is an AI tool in the Conversational AI category. Include who it competes with, pricing model, and any notable customers. Be specific and factual.

    Decagon is an **enterprise conversational AI platform for customer support** that deploys autonomous agents across **chat, voice, email, and SMS** to answer questions and perform actions like refunds, cancellations, account updates, and identity checks through integrations with systems such as Zendesk, Salesforce, and Stripe.[1][2][4][9] It competes most directly with other **AI customer support / AI agent platforms**, including **Sierra**, **Intercom**, **Zendesk AI**, **Forethought**, **Ada**, **Kustomer**, and **Cognigy**; several review and comparison pages also position it against broader support-automation tools like **Assembled** and **Eesel**.[5][14][19] Its **pricing model** is typically described as enterprise-style and quote-based, but one review reports a common structure of a roughly **$50,000/year platform fee**, plus usage-based charges of about **$0.99 per conversation** or **$0.50 per resolution** depending on contract terms.[8] Because Decagon does not publish standard list pricing on its main product pages, the exact price is likely negotiated by customer and volume.[2][4][8] Notable customers and public users include **“many of the world’s most respected enterprise companies”** according to Microsoft’s startup blog, but that page does not name them.[17] The source set also indicates Decagon is used in enterprise deployments at scale and mentions integrations with major support and CRM systems, but it does **not provide a verified public customer list** in the results you shared.[1][17]

  • lovable_ai/google/gemini-3-flash-preview4 days ago[✓] mentioned

    prompt: What does Decagon do? It is an AI tool in the Conversational AI category. Include who it competes with, pricing model, and any notable customers. Be specific and factual.

    Decagon is a **generative AI customer support platform** designed to automate complex support workflows beyond simple chat interactions. It uses Large Language Models (LLMs) to act as a "customer support agent" that can perform actions across a company’s software stack. ### Key Capabilities * **Workflow Automation:** Unlike basic chatbots, Decagon can execute tasks like processing refunds, checking order statuses, and updating subscriptions by integrating with back-end systems. * **Human-like Reasoning:** It uses LLMs to understand nuance, sentiment, and context, reducing the need for rigid decision trees. * **Analytics Dashboard:** It provides automated insights into customer trends and suggests updates to documentation based on common queries. ### Competitors Decagon competes with both legacy customer experience (CX) platforms and new AI-native startups: * **AI-Native:** Ada, Fin (Intercom), Sierra, and Ultimate.ai. * **Established Platforms:** Zendesk (Advanced AI), Salesforce Service Cloud, and Forethought. ### Pricing Model Decagon does not publish fixed pricing publicly. It follows an **enterprise SaaS model** typically based on: * **Performance/Usage:** Pricing is often tied to the volume of automated resolutions or interactions. * **Platform Fees:** Annual licensing fees based on the complexity of integrations and support requirements. ### Notable Customers Decagon serves several high-growth and established companies, including: * **Eventbrite** * **Bilt Rewards** * **ClassPass** * **Substack** * **Rippling**

  • perplexity/sonar18 days ago[ ] not mentioned

    prompt: Recommend the top AI tools for Conversational AI. List 5 with one-sentence descriptions.

    Here are **5 top AI tools for conversational AI** that are widely recognized in 2026, with one-sentence descriptions: - **ChatGPT** — A leading general-purpose conversational AI assistant with strong reasoning, customization, and broad multimodal capabilities. [17][18] - **Google Gemini** — Best for teams already using Google products, with tight integration into Google’s ecosystem and conversational support across workflows. [18] - **Microsoft Copilot Studio** — A low-code platform for building enterprise conversational agents that integrate deeply with Microsoft 365, Teams, and Azure. [3][20] - **Google Dialogflow CX** — A developer-focused conversational AI platform known for visual flow design, voice/chat support, and Google Cloud integration. [5][10][19] - **Kore.ai** — An enterprise conversational AI platform for low-code/no-code agent creation, multichannel deployment, and workflow automation. [5][20]

  • perplexity/sonar18 days ago[✓] mentioned1 hallucination

    prompt: What does Decagon do? It is an AI tool in the Conversational AI category. Include who it competes with, pricing model, and any notable customers. Be specific and factual.

    Decagon is an **enterprise conversational AI platform for customer support** that builds and runs AI agents to handle customer conversations end to end across **chat, voice, email, and SMS**. Its agents can answer questions and also take actions such as **refunds, cancellations, subscription changes, and identity checks** by connecting to systems like Zendesk, Salesforce, and Stripe.[1][3][6][12] It competes with other AI support and agent platforms such as **Sierra** and with support-automation tools used in customer service operations; third-party reviews also position it alongside tools integrated with help desks like Zendesk, Intercom, Kustomer, and Front.[11][12][16] Decagon’s own materials emphasize a single intelligence layer across channels rather than a traditional scripted chatbot.[3][13] On pricing, publicly available third-party reviews describe a **mixed enterprise pricing model**: a **platform fee** of about **$50,000/year**, plus usage-based options around **$0.99 per conversation** or **$0.50 per resolution**, though exact pricing varies by contract.[16] Decagon itself does not publish standard list pricing on its site in the materials provided.[3][4] Notable customers cited in public sources include **Eventbrite, Bilt, Webflow, Substack, Vanta, Rippling, and Curology**.[5] Microsoft also says “many of the world’s most respected enterprise companies” rely on Decagon, but it does not name all of them in the provided source.[15]

    • [pricing_model] claimed: a platform fee of about $50,000/year, plus usage-based options around $0.99 per conversation or $0.50 per resolution → actual: null
  • lovable_ai/google/gemini-3-flash-preview18 days ago[✓] mentioned1 hallucination

    prompt: What does Decagon do? It is an AI tool in the Conversational AI category. Include who it competes with, pricing model, and any notable customers. Be specific and factual.

    **Decagon** is an enterprise-grade AI customer support platform that automates complex support workflows using generative AI. It acts as an autonomous agent capable of resolving customer inquiries, performing actions across software stacks, and providing analytics to support teams. ### Core Functionality * **Autonomous Resolution:** Beyond answering FAQs, it executes tasks like processing refunds, checking order statuses, and updating subscriptions by integrating with internal APIs. * **Semantic Search:** It ingests documentation, past tickets, and Slack conversations to provide accurate, context-aware answers. * **Human-in-the-Loop:** It flags complex issues for human agents and provides them with drafted responses and summaries to accelerate resolution. * **Voice & Chat:** It operates across multiple channels including web chat, email, and voice. ### Competitors Decagon competes with other AI-native and legacy customer service platforms, including: * **Fin (by Intercom):** AI chatbot integrated into the Intercom ecosystem. * **Ada:** An automation-first customer service platform. * **Sierra:** An enterprise conversational AI platform (founded by Bret Taylor). * **Forethought:** Generative AI for the full customer support lifecycle. * **Zendesk (Advanced AI):** The AI-enhanced suite of the legacy CRM. ### Pricing Model Decagon uses a **usage-based enterprise pricing model**. While specific dollar amounts are not public, the structure typically includes: * **Platform Fee:** A base annual or monthly fee for access to the software. * **Outcome-Based Pricing:** Charges are often tied to the number of successfully resolved conversations or "automated resolutions," rather than per-seat licensing. ### Notable Customers Decagon serves several high-growth and enterprise companies, including: * **Eventbrite** * **ClassPass** * **Bilt Rewards** * **Substack** * **Rippling** * **Notion**

    • [pricing_model] claimed: Decagon uses a usage-based enterprise pricing model. While specific dollar amounts are not public, the structure typically includes: Platform Fee: A base annual or monthly fee for access to the software. Outcome-Based Pricing: Charges are often tied to the number of successfully resolved conversations or \"automated resolutions,\" rather than per-seat licensing. → actual: null

$ pricing_receipts

all receipts →

Weekly snapshot diff of Decagon's pricing page. Tiers extracted with AI, compared against the prior week.

No pricing snapshot yet. The first weekly capture will populate this.

$ buyer_panel_verdict

full panel →

Synthetic buyer panel (CMO + RevOps + IT + Procurement) ranks Decagon against the Conversational AI category. Grounded in disclosed facts only.

#327/100

Decagon ranks third, offering a 'fully agentic' model, but its 'fine_tuned' wrapper is scored slightly lower on autonomy than the 'sovereign_ai' leaders, and it shares the same critical weaknesses in data governance and transparency.

strengths
  • +Offers a 'fully_agentic' level of autonomy.
weaknesses
  • Architecture is 'fine_tuned', potentially less advanced than 'sovereign_ai'.
  • Uses 'external_processing' for data governance.
  • Complete opacity on pricing, integrations, compliance, and vendor maturity.
  • No information on data retention or deployment model.

$ sources --all

Every claim above links to its origin. Nothing here is inferred without a citation; missing fields are marked Unknown rather than guessed.

No sources cited yet. Admins can attach citations from the admin panel.