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Dynamiq
Dynamiq is an enterprise AI agent platform for chat, voice and workflow agents. It runs in Dynamiq Cloud or inside the customer's own cloud account or data center, and forward-deployed engineers take the first agents to production with the customer's team.
For agents: Enterprise AI agent platform for chat, voice and workflow agents, deployable in Dynamiq Cloud or the customer's own cloud. Docs cover quickstarts, SDK and API r
ai agentsworkflow builderagent platformsdkenterprise ai deployment
- Authority
- 50 reach 5 · trust 5 · quality 25 · freshness 15
- Tier
- listed
- llms.txt
- https://www.getdynamiq.ai/llms.txt
- llms-full.txt
- https://www.getdynamiq.ai/llms-full.txt
- Sections
- 9
- Links
- 177
- Size
- 40993 bytes
- Popularity rank
- #885629
- Country
- United States
- Categories
- AI and machine learning · AI agents and MCP
- For agents
- Interface: a documented API or declared MCP endpoint an agent can call
- Audience
- mixed · agents can: read docs, call api · en
- First seen
- 2026-10-19T10:45:14.936Z
- Last checked
- 2026-10-21T19:40:03.205Z
- Badge
Their llms.txt
The beginning of the file, from our validated copy saved 2026-10-21T19:39:54.365Z. Cached copy · Source on getdynamiq.ai
# Dynamiq
> Dynamiq is an enterprise AI agent platform for chat, voice and workflow agents. It runs in Dynamiq Cloud or inside the customer's own cloud account or data center, and forward-deployed engineers take the first agents to production with the customer's team.
Key facts:
- Compliance: SOC 2, HIPAA, GDPR, CASA Tier 2. BAA and DPA available.
- Deployment: Dynamiq Cloud, or self-hosted on AWS, Azure, GCP, IBM Cloud, Red Hat OpenShift or any Kubernetes 1.32+ cluster; isolated environments are delivered with our engineers.
- Models: 29 model providers in the SDK, the most-used models through the AI Gateway, plus open models you host.
- Integrations: 2,100+ app integrations, MCP servers and databases.
- Open source: the dynamiq Python SDK, Apache-2.0: https://github.com/dynamiq-ai/dynamiq
- Pricing: Free to start; Enterprise is custom.
- Every page is also available as markdown: request it with `Accept: text/markdown` or add `.md` to the URL.
## Platform
- [The Dynamiq platform](https://www.getdynamiq.ai/product): Build, ground, govern and deploy agents on one platform, in your cloud or ours.
- [AI Coworker](https://www.getdynamiq.ai/product/chat): AI Coworker plans, browses, writes code and works your apps from one conversation, in the browser and in Slack, Microsoft Teams and Telegram.
- [Voice Agents](https://www.getdynamiq.ai/product/voice-agents): Dynamiq Voice Agents answer inbound calls over the phone, web and your own backend, with tools, simulations and per-turn latency you can tune.
- [Agent Builder](https://www.getdynamiq.ai/product/agents): Design agents on a canvas or in the open-source Python SDK. Both run on one engine, with decision nodes, approvals and versioned deploys.
- [Apps and deployments](https://www.getdynamiq.ai/product/deployments): Deploy a workflow as an App: call it over HTTP, embed a chat widget, run it on a schedule or a trigger, and roll back to any earlier version in one click.
- [Knowledge](https://www.getdynamiq.ai/product/knowledge-rag): Build a knowledge base from files, websites or apps. Dynamiq converts, chunks, embeds and stores documents, with GraphRAG and permission-aware retrieval.
- [Integrations](https://www.getdynamiq.ai/product/integrations): Reach 2,100+ app integrations, 11,800+ actions and 3,300+ triggers from a workflow, connect MCP servers, and query databases and warehouses.
- [Models and AI Gateway](https://www.getdynamiq.ai/product/models): Use 29 model providers from one SDK, the most-used models through one OpenAI-compatible endpoint, and open models you host and fine-tune.
- [Guardrails and approvals](https://www.getdynamiq.ai/product/guardrails): Screen input for PII and prompt injection before it reaches a model, and pause any tool step for a reviewer who can edit the fields before it runs.
- [Evals](https://www.getdynamiq.ai/product/evaluations): Score agents on datasets built by hand or captured from traces, attach real-time evals to a live deployment, and grade voice simulation
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