Sistava

Decagon

Enterprise AI concierge for customer support with Agent Operating Procedures

About Decagon

Decagon is an engineering-led enterprise AI platform focused on customer support automation with natural language workflow definitions (Agent Operating Procedures). While Decagon requires $95K+ annual contracts and limits itself to customer support, Sistava provides multi-function AI employees from a marketplace with transparent pricing, team hierarchy, and thousands of integrations.

Platform details

Official website

What does Decagon AI actually do for enterprise customer support?

Decagon is a conversational AI platform that builds and scales AI support agents for enterprise customers. Its tagline, the AI concierge for every customer, captures the pitch: every customer interaction gets a personalized, intelligent response without a human in the loop. The platform unifies voice, chat, and email inside a single intelligence layer, so context and brand voice stay consistent across channels. The headline differentiator is Agent Operating Procedures, a system where non technical teams define complex support workflows in plain language instead of coded decision trees. Combined with integrations into Stripe, Shopify, and Salesforce, Decagon agents can process refunds, update orders, verify identity, and create tickets without escalating to a human. Decagon sits at the same enterprise altitude as Sierra. For smaller companies that want the same shape of capability without enterprise procurement, Sistava ships AI support employees with built in tools, memory, and channels that can be hired and deployed without a sales cycle.

How much does Decagon AI cost and what do you get?

Decagon uses custom enterprise contracts rather than a public price list. Marketplace data suggests median contracts run around $400,000 per year, and industry estimates put initial deployments around $50,000 annually before usage costs. Two pricing structures are offered: per conversation where every touched interaction is billed, or per resolution where only resolved conversations count at a higher rate. At that price you get the full Decagon platform, including Agent Operating Procedures, omnichannel deployment, integrations with Stripe, Shopify, Salesforce, and SOC 2 compliance with data residency options. White glove onboarding includes dedicated Agent Product Managers and Forward Deployed Engineers who embed with your team during deployment. The pricing model is honest for the segment Decagon targets, but it is not where most small companies start. Sistava offers AI support employees on a predictable subscription, with the same kind of tool actions and channel coverage, sized for teams that want results inside a month rather than inside a year.

When does Decagon AI beat the alternatives?

Decagon beats lighter alternatives when your support operation depends on complex, multi step workflows that mutate real systems. Refunds with eligibility logic, subscription downgrades that interact with billing, and identity verification flows are exactly where the Agent Operating Procedures system pays off. Plain language workflow definition removes the developer bottleneck that traditional bot platforms create. It also wins when omnichannel consistency is non negotiable. The unified intelligence layer across voice, chat, and email means a customer who calls after a chat does not start over, which matters for industries with high conversation continuity expectations. The white glove rollout, with dedicated APMs and FDEs, means a large team gets a real deployment partner rather than self serve documentation. Against modern AI workforce platforms, Decagon wins on enterprise depth and procurement readiness. For teams that do not need that depth, Sistava AI support employees deliver similar action capabilities and channel coverage with far less commitment.

Where does Decagon AI fall short for startups and mid market?

The contract structure makes Decagon a non starter for most companies under enterprise scale. Median contracts in the hundreds of thousands per year plus usage make it impractical for any team whose entire support budget is smaller than that number. Even the lower end estimates assume a real support volume to amortize the cost. Onboarding is also intensive by design. APMs and FDEs embed with your team because deployments are strategic projects, not weekend setups. A founder who wants a working AI teammate by tomorrow morning will not find that here, regardless of how strong the platform is for the segment it was built for. The Sistava model is built for that exact gap. An AI support employee can be hired, trained on your help center and product docs, and start handling tickets the same day, with channels and integrations available without a custom contract. Decagon is the right answer at the top of the market; Sistava is the right answer for the much larger middle.

How does Decagon AI handle complex workflows and real actions?

Decagon handles complex workflows through Agent Operating Procedures, a proprietary system that lets non technical CX teams define support logic in plain language. Instead of building decision trees in a flow editor, teams write the procedure the way they would explain it to a new human agent, and Decagon executes it across channels with the right tool calls. On the action side, integrations with Stripe, Shopify, Salesforce, and other enterprise systems let agents process refunds, update orders, verify identity, and create tickets without human intervention. Guardrails on sensitive operations like identity verification and refunds are part of the platform, which matters when an autonomous agent is touching billing and customer data. For teams that want a similar shape of capability at a smaller scale, Sistava AI support employees can call integrated tools across helpdesks, CRMs, and product systems out of the box, with the same emphasis on safe action taking through built in guardrails. The execution shape is similar; the buying motion is the main difference.

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