Dynamiq vs Sierra

Sierra is a closed, outcome-priced platform for customer experience agents. Dynamiq is a governed platform for chat, voice and workflow agents, with an Apache-2.0 SDK, that you can self-host.

By Maksym Buleshnyi, Applied AI, RAG systems Updated September 29, 2026

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In short

Sierra is a closed platform for customer experience AI agents across chat, SMS, WhatsApp, email, voice and ChatGPT, built with Ghostwriter, the no-code Agent Studio or its proprietary Agent SDK, and sold with outcome-based pricing and an expert agent development team. Dynamiq is a governed platform for chat, voice and workflow agents with an Apache-2.0 SDK, covering internal and back-office work as well as customer conversations, that runs inside your environment with forward-deployed engineers. Enterprises focused on customer experience that want outcome-based pricing fit Sierra; teams that need self-hosting, an open-source engine or internal agents fit Dynamiq.

Side by side

Facts checked September 29, 2026. Sources below.

Dimension	Dynamiq	Sierra
Best for	Enterprises in regulated industries that need chat, voice and workflow agents on one governed stack, deployed inside their own environment.	Enterprises that want customer experience agents built and run with Sierra under outcome-based pricing, in industries such as financial services, healthcare, telecom, media, travel, retail and technology.
Deployment options	Dynamiq Cloud, or self-hosted on your AWS, Azure, GCP, IBM Cloud, Red Hat OpenShift or any Kubernetes 1.32+ cluster, or on-prem. Fully isolated or air-gapped setups are delivered with our engineers.	Not publicly documented. Sierra's pages describe a hosted platform across chat, SMS, WhatsApp, email, voice and ChatGPT, and list FedRAMP High, without stating self-hosted or on-premises options.
Self-hosted or on-prem	Yes. Self-hosted on your cloud or on-prem, or Dynamiq Cloud; both run the same engine.	Not publicly documented.
License and source code	The Python SDK is open source under Apache-2.0 (github.com/dynamiq-ai/dynamiq), and the visual canvas runs on the same engine. The platform around it is not open source.	Closed platform, and its Agent SDK is proprietary; Sierra's public GitHub holds open-source benchmarks such as tau-bench, not platform code. Each customer's agent code lives in a Git repository the customer can access and export.
Model choice	29 model providers in the SDK, the most-used models behind one OpenAI-compatible AI Gateway endpoint, plus open models served on vLLM and LoRA fine-tuning.	No customer model choice is stated. Sierra runs on a constellation of frontier, open-weight and proprietary models and switches between LLM providers automatically.
Agent types (chat, voice, workflow)	Chat, inbound voice and workflow agents on one engine. AI Coworker works with its own cloud sandbox computer, in the browser, Slack, Microsoft Teams and Telegram; Voice Agents answer inbound calls; Agent Builder runs workflow agents.	Customer-facing agents across chat, SMS, WhatsApp, email, voice and ChatGPT, plus Horizon (July 2026) for long-running goals such as originating a loan or getting prior authorization for a procedure. Internal or employee agents are not described.
Voice	Inbound calls only, over WebRTC, SIP and WebSocket, with per-turn latency measurement and simulations scored by an LLM judge.	Inbound and outbound calls, with models tuned across 60+ locales, and Voice Sims that test languages, emotional states, background noise and interruptions.
Developer surface	Agent Builder pairs a visual canvas with the open-source Python SDK on one engine, with Choice and rules nodes, workflows generated from a prompt, and versions with rollback.	Ghostwriter builds agents from SOPs, transcripts, audio or a plain-language goal; Agent Studio edits them without code; and the Agent SDK uses a declarative programming language inside your existing development lifecycle.
Memory	Session memory scoped by user and session, plus long-term memory, where the agent decides when to save and recall durable, user-scoped facts that people can see and correct. Knowledge adds ingestion pipelines, permission-aware retrieval filters and knowledge graphs.	A Context Engine gives agents a memory layer the customer owns: permissioned, retained on the customer's terms and exportable to a data warehouse or another system.
Governance (guardrails, approvals, SSO)	Guardrails that detect PII and prompt injection, policy detection, validators and approvals with editable fields on any tool step, on every plan; SSO (OIDC with Okta and Microsoft Entra ID) on Enterprise.	Supervisory layers around the models to reduce hallucinations and prevent abuse, PII that is automatically encrypted and masked, PCI-certified infrastructure for payment data, and guardrails that set where human sign-off is required.
Evals and observability	Evals with datasets built from traces, LLM-as-a-judge, predefined and code metrics, and real-time evaluations on live deployments; traces with cost and latency per node, monitoring, and an AI agent that surfaces issues from production traces.	Simulations and regression test suites before release, Voice Sims, observability over tool calls, knowledge lookups and latency, Monitors and Pulse to surface issues, and multivariate Experiments.
Integrations	2,100+ app integrations and 11,800+ actions, plus MCP servers and per-user connections.	40+ pre-built integrations plus custom integrations for proprietary systems; agents also work with ChatGPT Apps through MCP.
Compliance	SOC 2 and CASA Tier 2, with a BAA for HIPAA workloads and a DPA under GDPR.	SOC 2, HIPAA, GDPR, PCI, FedRAMP High, CCPA, CSA STAR, ISO 27001 and ISO 42001 on its trust and reliability page, the EU AI Act among its homepage badges, and AIUC-1 certification (September 2026).
Delivery help (engineers)	Forward-deployed engineers run a bootcamp in your environment, ship the first production agent with your team, then hand over.	An expert agent development team that, per Sierra, has supported hundreds of deployments, with agent engineers and strategists who work directly with customers.
Pricing model	Free to start ($0), and Enterprise with custom pricing. Available on AWS Marketplace, Microsoft Azure Marketplace and IBM Marketplace.	Outcome-based: customers pay for business outcomes delivered rather than tokens, per Sierra; rates are not published.

Best for

DynamiqEnterprises in regulated industries that need chat, voice and workflow agents on one governed stack, deployed inside their own environment.

SierraEnterprises that want customer experience agents built and run with Sierra under outcome-based pricing, in industries such as financial services, healthcare, telecom, media, travel, retail and technology.

Deployment options

DynamiqDynamiq Cloud, or self-hosted on your AWS, Azure, GCP, IBM Cloud, Red Hat OpenShift or any Kubernetes 1.32+ cluster, or on-prem. Fully isolated or air-gapped setups are delivered with our engineers.

SierraNot publicly documented. Sierra's pages describe a hosted platform across chat, SMS, WhatsApp, email, voice and ChatGPT, and list FedRAMP High, without stating self-hosted or on-premises options.

Self-hosted or on-prem

DynamiqYes. Self-hosted on your cloud or on-prem, or Dynamiq Cloud; both run the same engine.

SierraNot publicly documented.

License and source code

DynamiqThe Python SDK is open source under Apache-2.0 (github.com/dynamiq-ai/dynamiq), and the visual canvas runs on the same engine. The platform around it is not open source.

SierraClosed platform, and its Agent SDK is proprietary; Sierra's public GitHub holds open-source benchmarks such as tau-bench, not platform code. Each customer's agent code lives in a Git repository the customer can access and export.

Model choice

Dynamiq29 model providers in the SDK, the most-used models behind one OpenAI-compatible AI Gateway endpoint, plus open models served on vLLM and LoRA fine-tuning.

SierraNo customer model choice is stated. Sierra runs on a constellation of frontier, open-weight and proprietary models and switches between LLM providers automatically.

Agent types (chat, voice, workflow)

DynamiqChat, inbound voice and workflow agents on one engine. AI Coworker works with its own cloud sandbox computer, in the browser, Slack, Microsoft Teams and Telegram; Voice Agents answer inbound calls; Agent Builder runs workflow agents.

SierraCustomer-facing agents across chat, SMS, WhatsApp, email, voice and ChatGPT, plus Horizon (July 2026) for long-running goals such as originating a loan or getting prior authorization for a procedure. Internal or employee agents are not described.

Voice

DynamiqInbound calls only, over WebRTC, SIP and WebSocket, with per-turn latency measurement and simulations scored by an LLM judge.

SierraInbound and outbound calls, with models tuned across 60+ locales, and Voice Sims that test languages, emotional states, background noise and interruptions.

Developer surface

DynamiqAgent Builder pairs a visual canvas with the open-source Python SDK on one engine, with Choice and rules nodes, workflows generated from a prompt, and versions with rollback.

SierraGhostwriter builds agents from SOPs, transcripts, audio or a plain-language goal; Agent Studio edits them without code; and the Agent SDK uses a declarative programming language inside your existing development lifecycle.

Memory

DynamiqSession memory scoped by user and session, plus long-term memory, where the agent decides when to save and recall durable, user-scoped facts that people can see and correct. Knowledge adds ingestion pipelines, permission-aware retrieval filters and knowledge graphs.

SierraA Context Engine gives agents a memory layer the customer owns: permissioned, retained on the customer's terms and exportable to a data warehouse or another system.

Governance (guardrails, approvals, SSO)

DynamiqGuardrails that detect PII and prompt injection, policy detection, validators and approvals with editable fields on any tool step, on every plan; SSO (OIDC with Okta and Microsoft Entra ID) on Enterprise.

SierraSupervisory layers around the models to reduce hallucinations and prevent abuse, PII that is automatically encrypted and masked, PCI-certified infrastructure for payment data, and guardrails that set where human sign-off is required.

Evals and observability

DynamiqEvals with datasets built from traces, LLM-as-a-judge, predefined and code metrics, and real-time evaluations on live deployments; traces with cost and latency per node, monitoring, and an AI agent that surfaces issues from production traces.

SierraSimulations and regression test suites before release, Voice Sims, observability over tool calls, knowledge lookups and latency, Monitors and Pulse to surface issues, and multivariate Experiments.

Integrations

Dynamiq2,100+ app integrations and 11,800+ actions, plus MCP servers and per-user connections.

Sierra40+ pre-built integrations plus custom integrations for proprietary systems; agents also work with ChatGPT Apps through MCP.

Compliance

DynamiqSOC 2 and CASA Tier 2, with a BAA for HIPAA workloads and a DPA under GDPR.

SierraSOC 2, HIPAA, GDPR, PCI, FedRAMP High, CCPA, CSA STAR, ISO 27001 and ISO 42001 on its trust and reliability page, the EU AI Act among its homepage badges, and AIUC-1 certification (September 2026).

Delivery help (engineers)

DynamiqForward-deployed engineers run a bootcamp in your environment, ship the first production agent with your team, then hand over.

SierraAn expert agent development team that, per Sierra, has supported hundreds of deployments, with agent engineers and strategists who work directly with customers.

Pricing model

DynamiqFree to start ($0), and Enterprise with custom pricing. Available on AWS Marketplace, Microsoft Azure Marketplace and IBM Marketplace.

SierraOutcome-based: customers pay for business outcomes delivered rather than tokens, per Sierra; rates are not published.

Choose Dynamiq when

One engine for chat, voice and workflow agents, covering internal and back-office work as well as customer conversations.
The agent engine is an open-source Python SDK under Apache-2.0, so the code your agents run on is yours to read, audit and fork.
Runs inside your environment: Dynamiq Cloud, or self-hosted on your AWS, Azure, GCP, IBM Cloud, OpenShift or any Kubernetes 1.32+ cluster, or on-prem, with isolated setups delivered with our engineers.
Model choice stays with you: 29 model providers in the SDK, the most-used models behind one OpenAI-compatible endpoint, plus open models on vLLM and LoRA fine-tuning.

Choose Sierra when

Ghostwriter builds production agents directly from SOPs, call transcripts, audio or a plain-language goal, and Agent Studio lets CX teams edit them without code.
Outcome-based pricing tied to business results, for buyers who prefer it to seat or usage pricing.
Outbound calling, long-running customer journeys with Horizon, and an agent development team that builds alongside you.

Moving from Sierra

Journeys, policies and personas built in Sierra, whether with Ghostwriter, Agent Studio or the Agent SDK, are rebuilt as agents and workflows in Dynamiq's Agent Builder; because Sierra agent code lives in a Git repository customers can export, it is a practical reference for the rebuild. Channels reconnect through AI Coworker, Voice Agents for inbound calls, and Dynamiq integrations or MCP servers, and knowledge sources move to Dynamiq Knowledge. Outbound calling has no direct equivalent, because Dynamiq voice agents are inbound only.

Questions and answers

Is Sierra open source?

No. Sierra's platform and Agent SDK are proprietary; its public GitHub holds research benchmarks. Dynamiq's Python SDK is open source under Apache-2.0; the Dynamiq platform is not.

Can Sierra run self-hosted or on-premises?

Not publicly documented; Sierra's site describes a hosted platform without stating a self-hosted or on-premises option. Dynamiq self-hosts on your own cloud or on-prem.

How is Sierra priced?

Sierra uses outcome-based pricing, where customers pay for business outcomes delivered rather than tokens, without published rates. Dynamiq offers a free plan to start and custom Enterprise pricing.

Does Sierra handle outbound calls?

Yes. Sierra's channels page describes agents across inbound and outbound calls. Dynamiq Voice Agents handle inbound calls only.

Does Dynamiq build agents from existing procedures or transcripts like Sierra's Ghostwriter?

Partly. Dynamiq's Agent Builder can generate a workflow from a prompt, which you then refine on the canvas or in the Python SDK. Building an agent directly from uploaded SOPs, transcripts or audio, the way Ghostwriter does, is not a stated Dynamiq feature.

Sources

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