$ stack_track_scores
methodology →$ buyer_risk_breakdown
UNRATEDUnrated — 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.
$ technical_anatomy
- Wrapper Status
- Fine-Tuned
- Agent Autonomy
- Fully Agentic
- Data Governance
- External Processing
- Deployment
- Unknown
- Data Retention
- Unknown
- Last Detected Update
- 1 mo ago
Customized/fine-tuned models on top of base providers.
Plans and executes multi-step workflows end-to-end.
Data is sent to vendor infrastructure for processing.
Where the inference pipeline runs.
How long ingested data persists in vendor systems.
When we last detected a meaningful infrastructure change.
$ marketing_fit
- Use cases
- Unknown
- Channels
- Unknown
- Output types
- Unknown
- Integrations
- Unknown
$ commercial
- Pricing model
- Unknown
- Pricing transparency
- Unknown
- Time to value
- Unknown
- Compliance
- Unknown
- Notable customers
- Unknown
- Customer logo count
- Unknown
How customers are charged.
Is pricing visible without sales contact?
How quickly customers see results.
Public customer logos counted on vendor site.
$ company
- Founded
- Unknown
- Team size
- Unknown
- Funding stage
- Unknown
- Headquarters
- Unknown
Year of incorporation.
Headcount band.
Latest disclosed round.
Primary office location.
$ changelog --tail
privacy_policy1 mo agoc427e6a046a8 → 32974ca676f8src: Privacy Policyview source ↗security1 mo ago087a1039cd76 → 8da913ef1907src: Security Pageview source ↗security1 mo ago869b33618df0 → 087a1039cd76src: Security Pageview source ↗privacy_policy2 mo agof3f4d0bbac1e → c427e6a046a8src: Privacy Policyview source ↗vendor_site2 mo ago604273aa1e5e → 6fb80e82aa58src: Vendor Siteview source ↗vendor_site2 mo agoc5f5c6e54dc9 → 604273aa1e5esrc: Vendor Siteview source ↗vendor_site2 mo agoc44b22e409d3 → c5f5c6e54dc9src: Vendor Siteview source ↗vendor_site2 mo ago9c704ebfa422 → c44b22e409d3src: Vendor Siteview source ↗security3 mo ago024cc1630bf3 → 869b33618df0src: Security Pageview source ↗vendor_site3 mo agofd87bfb710c5 → 9c704ebfa422src: Vendor Siteview source ↗security3 mo ago24e7bbd1045b → 024cc1630bf3src: Security Pageview source ↗vendor_site3 mo agoed307bb65540 → fd87bfb710c5src: Vendor Siteview source ↗vendor_site3 mo ago519b304e6eab → ed307bb65540src: Vendor Siteview source ↗vendor_site4 mo agobc222c0d78ff → 519b304e6eabsrc: Vendor Siteview source ↗privacy_policy4 mo agof6d1f3752234 → f3f4d0bbac1esrc: Privacy Policyview source ↗security4 mo ago11dee59ca896 → 24e7bbd1045bsrc: Security Pageview source ↗vendor_site4 mo ago42f792f2488d → bc222c0d78ffsrc: 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/sonartoday[ ] not mentionedprompt: Recommend the top AI tools for Conversational AI. List 5 with one-sentence descriptions.
1. **Google Dialogflow CX** — Best for enterprises needing sophisticated, structured chat and voice flows, especially within Google Cloud.[2][7] 2. **Microsoft Copilot Studio** — Best for organizations building custom business assistants integrated with Microsoft 365 and enterprise data. 3. **Rasa** — Best for teams requiring self-hosting, extensive customization, and control over conversational data.[2][8] 4. **Cognigy** — Best for large contact centers deploying complex, high-volume voice and chat automation.[1][3][6] 5. **Amazon Lex** — Best for AWS-native teams building scalable conversational interfaces with integrated speech recognition and cloud services.[1][5][6]
perplexity/sonartoday[✓] mentionedprompt: 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**. Its AI agents handle customer interactions across **chat, email, voice, and SMS**, and can take actions in business systems—such as processing refunds, updating accounts, and resolving support issues end to end. Teams define workflows in natural language through **Agent Operating Procedures (AOPs)**, while technical teams manage integrations, guardrails, testing, and versioning.[2][7][10] - **Competitors:** Its main competitive set includes **Intercom Fin**, **Ada**, **Forethought**, **Zendesk AI**, **Sierra**, and **Salesforce Agentforce**—all of which provide AI-driven customer-service automation. Decagon is positioned more toward autonomous, end-to-end resolution and managed enterprise deployment than conventional chatbot or agent-assist products.[5][9] - **Pricing model:** Decagon does **not publish standard list pricing**. It uses enterprise, usage-based contracts rather than per-seat pricing. Reported models include **per conversation**—charging for each AI-handled interaction—and **per resolution**—charging only when the AI fully resolves the issue.[5][8][9] AWS Marketplace lists platform access as available through a private offer, with one listing showing **$1 million**, which should not be treated as a universal price.[6] - **Notable customers:** Publicly identified customers include **Notion, Duolingo, Chime, Rippling, Hertz, Avis Budget Group, Oura Health, Substack, Bilt, Away, Noom, Faire, ClassPass, Samsara, and 1-800-FLOWERS.COM**.[2][6][10] Decagon says ClassPass reduced AI-support costs by **95%** and that Hunter Douglas generated **$1 million in AI-driven revenue** using the platform.[6]
lovable_ai/google/gemini-3-flash-previewtoday[✓] mentionedprompt: 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 and customer interactions using Large Language Models (LLMs). ### **Core Functionality** Decagon builds autonomous "AI agents" that go beyond simple chatbots. Key capabilities include: * **Action-Oriented Automation:** It doesn't just answer questions; it performs actions like processing refunds, checking order statuses, and updating account settings by integrating directly with back-end systems (APIs). * **Human-Like Reasoning:** It uses generative AI to understand nuanced customer intent and maintain context across long conversations. * **Self-Learning:** It analyzes historical support tickets to build its own knowledge base and identifies gaps where documentation is missing. * **Omnichannel Support:** It operates across email, chat, SMS, and social media. ### **Key Competitors** Decagon competes with both legacy customer service platforms and new generative AI startups: * **Incumbents:** Intercom (Fin AI), Zendesk (Advanced AI), and Salesforce (Service Cloud). * **AI-Native Startups:** Sierra (founded by Bret Taylor), Ada, Forethought, and Maven AGI. ### **Pricing Model** Decagon typically follows a **usage-based enterprise pricing** model. While specific rates are not public, the structure generally includes: * **Platform Fee:** A base cost for integration and access to the dashboard. * **Success-Based Pricing:** Charges based on the number of "automated resolutions" (tickets handled successfully without human intervention), aligning cost with the value provided. ### **Notable Customers** Decagon is utilized primarily by high-growth tech companies and consumer brands, including: * **Eventbrite** * **Bilt Rewards** * **ClassPass** * **Substack** * **Ripcord**
perplexity/sonar14 days ago[ ] not mentionedprompt: Recommend the top AI tools for Conversational AI. List 5 with one-sentence descriptions.
1. **Google Dialogflow** — A mature platform for building text- and voice-based agents with strong natural-language understanding and broad integrations.[2][7] 2. **Microsoft Copilot Studio** — A low-code tool for creating business agents connected to Microsoft 365, Teams, and enterprise data.[10] 3. **Amazon Lex** — An AWS-managed service for developing conversational interfaces using speech recognition and language understanding.[7] 4. **IBM watsonx Assistant** — An enterprise-focused assistant platform designed for customer service, automation, and governed deployments.[6][7] 5. **Yellow.ai** — An omnichannel platform for deploying customer-support agents across chat, voice, and messaging channels.[1][5]
perplexity/sonar14 days ago[✓] mentionedprompt: 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**. Its AI agents operate across chat, email, voice, and SMS; answer questions, access business systems, and take actions such as refunds, cancellations, account updates, and transaction disputes.[1][5] - **Competitive set:** Decagon competes with enterprise customer-service AI and agent platforms such as **Sierra, Intercom Fin, Ada, PolyAI, Cognigy, and Cresta**. Its differentiation is end-to-end task execution across multiple channels rather than simply generating replies or deflecting tickets. - **Pricing model:** Decagon does not publish standard list pricing; contracts are negotiated through enterprise sales.[4] Reported models are: - **Per conversation:** a fee for each inbound customer interaction, generally with volume discounts. - **Per resolution:** a higher fee charged only when the AI fully resolves the issue without escalation.[5] - AWS Marketplace lists platform access through a private offer, including a displayed **$1 million** platform-access amount, but this should not be treated as Decagon’s universal price.[6] - **Notable customers:** Publicly named customers include **Notion, Duolingo, Chime, Rippling, Hertz, Avis Budget Group, Oura Health, Substack, Bilt, Block, Deutsche Telekom, and Hunter Douglas**.[1][5][10] Decagon says its platform supports companies including **Delta Air Lines, American Airlines, Ticketmaster, Affirm, and Snap**.[7] - **Reported customer outcomes:** ClassPass reportedly reduced AI-support costs by **95%**, while Hunter Douglas generated **$1 million in AI-driven revenue** through the platform.[6]
lovable_ai/google/gemini-3-flash-preview14 days ago[✓] mentionedprompt: 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 customer interactions across chat, email, and SMS. Unlike basic chatbots, Decagon uses Large Language Models (LLMs) to perform complex tasks such as processing refunds, troubleshooting technical issues, and updating account settings by integrating directly with a company's internal tools and APIs. ### Key Capabilities * **Autonomous Resolution:** It can resolve tickets end-to-end without human intervention by connecting to backend systems (e.g., Zendesk, Salesforce, Stripe). * **Semantic Search:** It ingests help centers and documentation to provide accurate answers. * **Analytics:** It categorizes customer feedback and identifies recurring issues to help product teams prioritize features. ### Competitors Decagon competes with both legacy customer service platforms and new AI-native startups: * **Intercom (Fin AI):** Established customer service suite with built-in AI. * **Ada:** A long-standing automated customer service platform moving into LLM-based resolution. * **Sierra:** An enterprise AI agent platform co-founded by Bret Taylor. * **Forethought:** An AI platform focused on the entire support lifecycle. ### Pricing Model Decagon uses an **enterprise-based pricing model**. While they do not publish fixed public rates, their structure typically includes: * **Platform Fee:** A recurring subscription for access to the software and integrations. * **Performance-based/Usage-based:** Pricing often scales based on the volume of tickets handled or successful resolutions achieved. ### Notable Customers Decagon serves high-growth B2C and B2B companies, including: * **Eventbrite** * **ClassPass** * **Bilt Rewards** * **Substack** * **Ripling**
$ 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.
Its profile is nearly identical to Sierra's, offering 'fully agentic' functionality but hampered by a standard data governance model and a complete absence of disclosures on key criteria like pricing and integrations.
- +'Fully_agentic' capabilities address growth-oriented priorities
- +'Fine_tuned' model may offer some level of specialization
- −Fails to disclose any information on pricing, integrations, compliance, or vendor maturity
- −Data governance relies on 'external_processing', raising concerns for IT and RevOps
- −Lack of transparency on supported channels and deployment model
- −Provided 'transparency_index' of 7 is contradicted by numerous null fields
$ 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.