# 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 simulations with an LLM judge.
- [Observability](https://www.getdynamiq.ai/product/observability): Trace every run node by node with cost, latency and tokens, monitor a deployment over time, and let an AI agent flag issues in your production traces.

## Solutions

- [Industries](https://www.getdynamiq.ai/industries): AI agents for financial services, insurance, government, telecommunications and healthcare.
- [Use cases](https://www.getdynamiq.ai/use-cases): Agents for customer service, contact centers, back-office work, KYC, claims, compliance and governance.
- [Customer stories](https://www.getdynamiq.ai/case-studies-dynamiq): Agents in production at regulated organizations.
- [Financial services](https://www.getdynamiq.ai/industries/financial-services): Agents for banks and lenders that automate back-office work, answer customers by phone and chat, and prepare KYC and AML files, with approval on every decision.
- [Insurance](https://www.getdynamiq.ai/industries/insurance): Agents for insurers that answer policyholders by phone and chat, prepare claims and underwriting files, and leave every decision to an adjuster or underwriter.
- [Government and public sector](https://www.getdynamiq.ai/industries/public-sector): Agents for citizen services, document review and program reporting, deployed on infrastructure your agency controls, with human oversight on every decision.
- [Telecommunications](https://www.getdynamiq.ai/industries/telecommunications): Voice and chat agents for telecom customer care in your subscribers' own languages, with billing reconciliation and network knowledge assistants.
- [Healthcare](https://www.getdynamiq.ai/industries/healthcare): Agents for patient intake, referral documents and clinical knowledge, with PII and prompt injection screened before a model reads anything.
- [Customer service](https://www.getdynamiq.ai/use-cases/customer-service): Voice and chat agents that answer inbound calls and messages, look up accounts in your systems, and hand complex cases to a person when they need one.
- [Contact center voice agents](https://www.getdynamiq.ai/use-cases/contact-center): Voice agents that answer your inbound lines, look up the caller's account, resolve routine calls and transfer to a person when needed. Inbound only.
- [Document review and underwriting](https://www.getdynamiq.ai/use-cases/document-review): An agent that reads loan files, underwriting submissions and contracts, checks them against your rules, and flags exceptions to a reviewer instead of approving.
- [Insurance claims processing](https://www.getdynamiq.ai/use-cases/claims-processing): An agent that takes first notice of loss by phone or chat, reads claim documents, checks coverage and prepares the file, with an adjuster deciding every claim.
- [Compliance and financial crime](https://www.getdynamiq.ai/use-cases/compliance-financial-crime): An agent that triages KYC and AML alerts, tracks regulatory change, and drafts reports, with every alert routed to an analyst for sign-off before it closes.
- [KYC and customer onboarding](https://www.getdynamiq.ai/use-cases/kyc-onboarding): An agent that reads onboarding documents, gathers screening results, applies your risk rules and prepares the file, with an analyst approving every account.
- [Research and knowledge assistants](https://www.getdynamiq.ai/use-cases/research-knowledge): A research assistant that answers from your documents and systems, respects who can see what, and cites its source for every claim it makes.
- [Back-office and finance operations](https://www.getdynamiq.ai/use-cases/back-office): Agents that reconcile accounts, investigate payment exceptions, prepare dispute cases and draft reports, with approval before anything posts, pays or files.
- [Accounts payable and invoices](https://www.getdynamiq.ai/use-cases/accounts-payable): An agent that reads invoices, matches them to purchase orders and receipts, routes exceptions and prepares payments, with approval before anything posts.
- [AI agent governance](https://www.getdynamiq.ai/use-cases/ai-agent-governance): Govern AI agents in production: detect PII and prompt injection, require approval before actions, trace every run and score live traffic with evals.
- [Sovereign AI](https://www.getdynamiq.ai/use-cases/sovereign-ai): Run the agent platform, open models and every trace inside your own cloud account or data center, operated by your team, with an open-source SDK.
- [How an Asian neo-bank automated customer support](https://www.getdynamiq.ai/case-studies/automating-customer-support-at-scale-how-a-neo-bank-saves-1-5m-a-year-with-ai): How a digital bank in Asia built a support agent on Dynamiq that answers routine requests, acts on backend systems, and hands off to a person when needed.
- [Document search for a B2B accounting platform](https://www.getdynamiq.ai/case-studies/smart-document-search-for-a-b2b-accounting-platform-built-in-one-week-with-dynamiq): How a B2B accounting platform added natural-language document search on Dynamiq, built by one engineer in a week using Claude and Amazon OpenSearch.

## Deployment

- [Forward-deployed engineers](https://www.getdynamiq.ai/deployment): A bootcamp in your environment, a first production agent and a handover to your team.
- [Where Dynamiq runs](https://www.getdynamiq.ai/deployment/self-hosted): Dynamiq Cloud, your cloud account, your data center or isolated environments.
- [Security and Trust Center](https://www.getdynamiq.ai/security): SOC 2, HIPAA, GDPR, CASA Tier 2, SSO on Enterprise, encrypted secrets, traced runs and the security review kit.

## Developers

- [Open-source SDK](https://www.getdynamiq.ai/open-source): The Apache-2.0 Python framework behind the platform.

## Resources

- [AI agent ROI calculator](https://www.getdynamiq.ai/resources/ai-agent-roi-calculator): Estimate the hours and cost an agent could save.
- [AI agent readiness assessment](https://www.getdynamiq.ai/resources/ai-agent-readiness-assessment): Ten questions, a score and a 90-day plan.
- [AI agent platform evaluation kit](https://www.getdynamiq.ai/resources/agent-platform-evaluation-kit): Questions to ask every vendor, with a scorecard.
- [Blog](https://www.getdynamiq.ai/blog): Guides and engineering notes on AI agents in production.
- [How Dynamiq built a cost-aware legal research workflow with IBM watsonx](https://www.getdynamiq.ai/post/how-dynamiq-built-a-cost-aware-legal-research-workflow-with-ibm-watsonx): How a three-agent legal research workflow on IBM watsonx routes every question by cost: Granite triages, deep research runs only when needed, all traced.
- [Best Dify alternatives for AI workflow automation](https://www.getdynamiq.ai/post/best-dify-alternatives-for-ai-workflow-automation): Dify is a source-available platform for agentic workflows and RAG. Compare the best Dify alternatives in 2026 on license, deployment, voice agents and evals.
- [Best Flowise alternatives for AI workflow automation](https://www.getdynamiq.ai/post/best-flowise-alternatives-for-ai-workflow-automation): Flowise reached end of life on August 31, 2026. Compare the best Flowise alternatives for agents, RAG and chatflows, and plan the move off the archived code.
- [Best Langflow alternatives for AI workflow and agent orchestration](https://www.getdynamiq.ai/post/best-langflow-alternatives-for-ai-workflow-agent-orchestration): Langflow is an MIT licensed builder for agents, RAG and MCP servers. Compare the best Langflow alternatives in 2026 for evals, governance and deployment.
- [Best Sana alternatives for AI knowledge and workflow automation](https://www.getdynamiq.ai/post/best-sana-alternatives-for-ai-knowledge-workflow-automation): Sana, now part of Workday, is an AI platform for knowledge, agents and learning. Compare the best Sana alternatives for agents, RAG, evals and deployment.
- [Microsoft Copilot alternatives for enterprise AI teams](https://www.getdynamiq.ai/post/microsoft-copilot-alternatives-for-enterprise-ai-teams): Copilot Studio runs only in Microsoft's cloud. Compare Copilot Studio alternatives in 2026 for self-hosting, model choice, voice agents, RAG and evals.
- [Smarter Zapier alternatives to scale AI automation](https://www.getdynamiq.ai/post/smarter-zapier-alternatives-to-scale-ai-automation): Zapier connects 9,000+ apps and runs AI agents in its own cloud. Compare smarter Zapier alternatives in 2026 for self-hosting, voice agents, RAG and evals.
- [LLM guardrails in private equity: how to scale GenAI safely across portfolio companies](https://www.getdynamiq.ai/post/llm-guardrails-in-private-equity-how-to-scale-genai-safely-across-portfolio-companies): How private equity firms set LLM guardrails once and apply them across a portfolio: data boundaries, risk tiers, approvals, audit trails and IC metrics.
- [Automating mortgage pre-approval with Dynamiq and Amazon Nova for banks and lenders](https://www.getdynamiq.ai/post/automating-mortgage-pre-approval-using-dynamiq-and-amazon-nova-for-financial-and-banking-institutions): Build a multi-agent mortgage pre-approval workflow on Amazon Nova: four specialist agents, a senior risk analyst, your lending policy and a human sign-off.
- [How to create an AI agent from scratch: a step-by-step guide](https://www.getdynamiq.ai/post/how-to-create-an-ai-agent-from-scratch-step-by-step-guide): Build an AI agent step by step: define the job, choose a model, add tools, knowledge, memory and guardrails, then test and deploy. With working Python code.
- [Best n8n alternatives for AI workflow automation](https://www.getdynamiq.ai/post/best-n8n-alternatives-for-ai-workflow-automation): n8n now builds AI agents alongside workflows. Compare the best n8n alternatives in 2026, from Zapier and Dify to Dynamiq, on license, deployment and evals.
- [Enterprise AI agents: benefits, use cases, implementation guide](https://www.getdynamiq.ai/post/enterprise-ai-agents-benefits-use-cases-implementation-guide): What enterprise AI agents are, the main types, what makes an agent enterprise-ready, where agents deliver value, and how to implement them without stalling.
- [Multi-agent AI systems: definition, benefits, limitations and how to build one](https://www.getdynamiq.ai/post/multi-agent-ai-systems-definition-benefits-limitations-how-to-build): What a multi-agent AI system is, the main coordination patterns, benefits and limits versus a single agent, regulated-industry examples, and how to build one.
- [Agentic workflows explained: benefits, use cases, best practices](https://www.getdynamiq.ai/post/agentic-workflows-explained-benefits-use-cases-best-practices): What agentic workflows are, how they differ from automation and autonomous agents, where they pay off in regulated work, and how to build them safely.
- [LLM agents explained: a complete guide](https://www.getdynamiq.ai/post/llm-agents-explained-complete-guide-in-2025): What LLM agents are, how they work, their components and types, where enterprises use them, the main challenges, and the frameworks used to build them.
- [AI-driven due diligence through to exit: how private equity firms use GenAI](https://www.getdynamiq.ai/post/ai-driven-due-diligence-through-to-exit-how-private-equity-firms-are-using-genai-in-2025): How private equity firms use GenAI from due diligence to exit: red flag scanning, target screening, investment memos, KPIs to track and pitfalls to avoid.
- [AI agents for private equity: use cases, KPIs, and deployment strategy](https://www.getdynamiq.ai/post/ai-agents-for-private-equity-use-cases-kpis-and-deployment-strategy): How private equity firms use AI agents in deal sourcing, diligence and portfolio operations, which KPIs prove ROI, and how to run a first pilot.
- [Dynamiq to launch enterprise-ready AI agents in IBM watsonx Orchestrate's agent catalog](https://www.getdynamiq.ai/post/dynamiq-to-launch-enterprise-ready-ai-agents-within-ibm-watsonx-orchestrates-agent-catalog): Dynamiq announced plans to bring a Medical Research Agent, a Legal Assistant Agent and an OCR Document Agent to IBM watsonx Orchestrate's agent catalog.
- [Agentic RAG with Apache Iceberg and Dynamiq on IBM watsonx.data](https://www.getdynamiq.ai/post/unlocking-enterprise-intelligence-with-agentic-rag-apache-iceberg-and-dynamiq-on-watsonx-data): How agentic RAG combines SQL over Apache Iceberg tables with vector search in Milvus on IBM watsonx.data, built with Dynamiq agents, with an HR example.
- [Generative AI for enterprises: practical ways to cut costs and boost sales](https://www.getdynamiq.ai/post/generative-ai-practical-ways-for-enterprises-to-cut-costs-and-boost-sales): Where generative AI and AI agents cut costs and grow revenue in large companies: support, back office, documents, sales and marketing, and how to measure it.
- [Build an intelligent agent system for market analysis with DeepSeek](https://www.getdynamiq.ai/post/build-an-intelligent-agent-system-for-market-analysis-with-deepseek): Build a market analysis agent system on DeepSeek models: a research agent with search and code, a validation agent, and a manager that coordinates them.
- [Understanding agentic AI: definition, benefits and applications in business](https://www.getdynamiq.ai/post/understanding-agentic-ai): What agentic AI is, how it works, how it differs from generative AI and AI agents, where businesses use it, and how to implement it with the right controls.
- [Build an automated social media management agent with Dynamiq](https://www.getdynamiq.ai/post/build-an-automated-social-media-management-agent-with-dynamiq): Build an agent that reads a client list, drafts a personalized email for each contact and sends it through Mailgun after a person approves the drafts.
- [Building an intelligent Linear app assistant](https://www.getdynamiq.ai/post/building-an-intelligent-linear-app-assistant): Build a Linear assistant that answers questions about projects and teams and writes well-scoped issues from chat, using Linear's MCP server and Dynamiq.
- [Build an autonomous data analyst using Dynamiq, E2B and Together AI](https://www.getdynamiq.ai/post/how-to-build-an-autonomous-data-analyst-using-dynamiq-e2b-and-together-ai): Build a data analyst agent in Python with the open-source Dynamiq SDK: it reasons with a Together AI model and writes and runs code in an E2B sandbox.
- [Building a Search GPT with Dynamiq](https://www.getdynamiq.ai/post/building-a-search-gpt-with-dynamiq): Build a Search GPT that rephrases a question, searches the web and writes a cited answer, as a visual workflow called over HTTP or in Python with the SDK.
- [Agent orchestration patterns: linear and adaptive multi-agent systems with Dynamiq](https://www.getdynamiq.ai/post/agent-orchestration-patterns-in-multi-agent-systems-linear-and-adaptive-approaches-with-dynamiq): Linear and adaptive agent orchestration explained: when to use each pattern, and how to build both with Dynamiq's Graph Orchestrator and manager agents.
- [Automating customer support in banking with agentic RAG](https://www.getdynamiq.ai/post/automating-customer-support-in-banking-using-agentic-rag): How agentic RAG automates bank customer support: one agent retrieves your procedures, another acts through your APIs, with approvals and traces.
- [Building a conversational AI agent with memory in Dynamiq](https://www.getdynamiq.ai/post/building-a-conversational-ai-agent-with-dynamiq): Build a conversational AI agent that remembers: session memory scoped by user and session, plus long-term facts the agent saves and recalls itself.
- [Dynamiq now deployable on IBM Cloud: simplify, scale and secure your AI projects](https://www.getdynamiq.ai/post/dynamiq-now-deployable-on-ibm-cloud-simplify-scale-and-secure-your-ai-projects): Dynamiq runs self-hosted on IBM Cloud Kubernetes Service or Red Hat OpenShift, so agents, knowledge bases and traces stay in an IBM Cloud account you control.
- [A comprehensive guide to transforming your business with multimodal AI](https://www.getdynamiq.ai/post/a-comprehensive-guide-to-transforming-your-business-with-multimodal-ai): What multimodal AI is, how models combine text, images, audio and video, where businesses use it, and how to adopt it safely in regulated industries.
- [How the EU AI Act impacts your business: deadlines, obligations and fines](https://www.getdynamiq.ai/post/how-the-eu-ai-act-will-impact-your-business): What the EU AI Act requires of businesses in 2026: risk categories, what applies now, the new high-risk deadlines after the AI Omnibus, fines and next steps.
- [Mastering LLM security: an air-gapped approach for high-security deployments](https://www.getdynamiq.ai/post/mastering-llm-security-an-air-gapped-solution-for-high-security-deployments): How to secure LLMs and AI agents in high-security environments: the OWASP 2025 risks, when an air-gapped deployment pays off, and the controls it still needs.
- [AMD Instinct MI250 vs NVIDIA A100: the LLM inference showdown](https://www.getdynamiq.ai/post/amd-instinct-mi250-vs-nvidia-a100-the-llm-inference-showdown): Our vLLM benchmark of the AMD Instinct MI250 against NVIDIA A100 40GB and 80GB on 7B to 14B models: throughput, latency, setup and what it means today.
- [GenAIOps for enterprises: the build vs. buy decision](https://www.getdynamiq.ai/post/genaiops-for-enterprises-the-build-vs-buy-dilemma): GenAIOps is how enterprises run generative AI and agents in production. Compare building a platform with buying one: costs, risks and a checklist.
- [Think global, act local: how data residency regulations influence banks' LLM use](https://www.getdynamiq.ai/post/think-global-act-local-how-data-residency-regulations-influence-banks-llm-use): How data residency and transfer rules shape banks' use of LLMs, where AI systems touch regulated data, and architectures that keep that data in-country.
- [Less risk and no fee: an overview of open-source LLMs for enterprises](https://www.getdynamiq.ai/post/less-risk-and-no-fee-overview-of-open-source-llms-for-enterprises): Open-source and open-weight LLMs for enterprises: model families to consider, how licenses differ, what they really cost to run, and when to self-host.
- [Balancing innovation and privacy: LLMs under GDPR](https://www.getdynamiq.ai/post/balancing-innovation-and-privacy-llms-under-gdpr): How to use LLMs under GDPR: lawful basis, data minimization, DPIAs, erasure and data residency, and where self-hosting and PII detection help.
- [Guardrails for LLMs in banking: essential measures for secure AI use](https://www.getdynamiq.ai/post/guardrails-for-llms-in-banking-essential-measures-for-secure-ai-use): The guardrails banks need around LLMs and AI agents: input screening, output checks, limits on actions, human approvals and audit trails, with examples.
- [Should enterprises consider implementing large language models?](https://www.getdynamiq.ai/post/should-enterprises-consider-implementing-large-language-models): Should your enterprise implement LLMs? Where they pay off, the risks and costs, when not to use them, and a step-by-step plan from first use case to scale.
- [Generative AI and LLMs in banking: examples, use cases, limitations and solutions](https://www.getdynamiq.ai/post/generative-ai-and-llms-in-banking-examples-use-cases-limitations-and-solutions): How banks use generative AI and LLMs today, from customer service to KYC triage, what still limits adoption, and the controls that get agents into production.
- [Comparisons](https://www.getdynamiq.ai/compare): Dynamiq compared with other AI agent platforms, with sources.
- [Dynamiq vs Amazon Bedrock AgentCore](https://www.getdynamiq.ai/compare/amazon-bedrock-agentcore): Amazon Bedrock AgentCore is AWS's usage-priced platform for running agents. Dynamiq runs chat, voice and workflow agents on any cloud or on-prem.
- [Dynamiq vs Microsoft Copilot Studio](https://www.getdynamiq.ai/compare/microsoft-copilot-studio): Microsoft Copilot Studio is a low-code agent studio run in Microsoft's cloud. Dynamiq runs chat, voice and workflow agents on any cloud or on-prem.
- [Dynamiq vs LangGraph and LangSmith](https://www.getdynamiq.ai/compare/langgraph): LangGraph is an MIT licensed agent framework, and LangSmith is LangChain's agent engineering platform. Dynamiq adds voice agents and a deployment team.
- [Dynamiq vs CrewAI](https://www.getdynamiq.ai/compare/crewai): CrewAI pairs an MIT licensed multi-agent framework with its AMP platform. Dynamiq adds voice agents, built-in evals and engineers who ship with your team.
- [Dynamiq vs Dify](https://www.getdynamiq.ai/compare/dify): Dify is a source-available platform for agentic workflows and RAG that restricts multi-tenant hosting. Dynamiq adds voice agents on an Apache-2.0 engine.
- [Dynamiq vs n8n](https://www.getdynamiq.ai/compare/n8n): n8n is fair-code workflow automation that now builds AI agents too. Dynamiq is a governed platform for chat, voice and workflow agents with an Apache-2.0 SDK.
- [Dynamiq vs StackAI](https://www.getdynamiq.ai/compare/stackai): StackAI, now part of Asana, is a closed no-code agent platform with VPC and on-prem options. Dynamiq adds voice agents and an Apache-2.0 SDK on one engine.
- [Dynamiq vs Langdock](https://www.getdynamiq.ai/compare/langdock): Langdock is a closed, EU-hosted platform for rolling out AI chat, agents and workflows. Dynamiq self-hosts on any cloud or on-prem, with an Apache-2.0 SDK.
- [Dynamiq vs Glean](https://www.getdynamiq.ai/compare/glean): Glean is an enterprise search and AI assistant platform with 275+ connectors, run by Glean. Dynamiq runs agents that act, inside your cloud or on-prem.
- [Dynamiq vs Flowise](https://www.getdynamiq.ai/compare/flowise): Flowise reached end of life on August 31, 2026, and its GitHub repo is archived. Dynamiq is an actively developed platform for chat, voice and workflow agents.
- [Dynamiq vs Langflow](https://www.getdynamiq.ai/compare/langflow): Langflow is an open-source, MIT licensed builder for agents, RAG and MCP servers. Dynamiq adds voice agents, built-in evals and a deployment team on one engine.
- [Dynamiq vs Sierra](https://www.getdynamiq.ai/compare/sierra): Sierra is a closed, outcome-priced platform for customer experience agents. Dynamiq runs chat, voice and workflow agents in your own environment.
- [Dynamiq vs Decagon](https://www.getdynamiq.ai/compare/decagon): Decagon is a closed, hosted platform for customer agents across chat, voice and email. Dynamiq runs chat, voice and workflow agents in your own environment.
- [Dynamiq vs Wonderful](https://www.getdynamiq.ai/compare/wonderful): Wonderful is a closed enterprise AI platform with air-gapped on-prem deployment. Dynamiq is a governed agent platform with an Apache-2.0 SDK and a free plan.
- [Dynamiq vs Kore.ai](https://www.getdynamiq.ai/compare/kore-ai): Kore.ai's Artemis is a closed agent platform for customer and employee experience. Dynamiq runs chat, voice and workflow agents with an Apache-2.0 SDK.

## Company

- [Dynamiq: enterprise AI agents in your cloud or data center](https://www.getdynamiq.ai/): Chat, voice and workflow agents on one governed platform, deployed with forward-deployed engineers.
- [Pricing](https://www.getdynamiq.ai/pricing): Free to start; Enterprise adds self-hosting, SSO, engineers and support.
- [Partners and marketplaces](https://www.getdynamiq.ai/partner-catalog): Cloud, technology and solutions partners, and AWS, Azure and IBM marketplaces.
- [Dynamiq and IBM watsonx](https://www.getdynamiq.ai/partners/ibm): Build with IBM watsonx models and data, deploy on IBM Cloud or on-prem.
- [Partner program](https://www.getdynamiq.ai/become-a-partner): For services firms, resellers and technology companies.
- [Apply to partner](https://www.getdynamiq.ai/partner-apply): Apply to the Dynamiq partner program.
- [About Dynamiq](https://www.getdynamiq.ai/about): Who we are and what we believe.
- [Careers](https://www.getdynamiq.ai/careers): Open roles at Dynamiq.
- [Contact](https://www.getdynamiq.ai/contact): Talk to the Dynamiq team.
- [Talk to the team](https://www.getdynamiq.ai/book-a-demo): Book a working session with Dynamiq's team and engineers on your use case.
- [DevOps Engineer](https://www.getdynamiq.ai/careers/devops-engineer): Engineering, Remote, Part-time
- [Director of B2B Sales (MENA)](https://www.getdynamiq.ai/careers/director-b2b-sales): Sales, Dubai or Riyadh, Full-time
- [Director of B2B Sales (North America)](https://www.getdynamiq.ai/careers/director-of-b2b-sales-north-america): Sales, New York, US, Full-time
- [Research Engineer](https://www.getdynamiq.ai/careers/research-engineer): Engineering, Remote, Full-time

## Glossary

- [AI agent glossary](https://www.getdynamiq.ai/glossary): Plain definitions of AI agent terms for enterprise teams.
- [Agent memory](https://www.getdynamiq.ai/glossary/agent-memory): The system that lets an AI agent recall earlier conversation turns or durable facts across separate runs, scoped to a user and session.
- [Agent orchestration](https://www.getdynamiq.ai/glossary/agent-orchestration): The layer that decides which agent or step runs next, in what order and with what shared state, when a task needs more than one agent.
- [Agent sandbox](https://www.getdynamiq.ai/glossary/agent-sandbox): An isolated, disposable virtual machine an agent can use to run shell commands, execute code and write files, separate from production systems.
- [Agentic AI](https://www.getdynamiq.ai/glossary/agentic-ai): AI systems that pursue a goal by planning steps, calling tools and acting on the results, rather than only generating a response to a single prompt.
- [Agentic memory](https://www.getdynamiq.ai/glossary/agentic-memory): Memory an AI agent manages itself, deciding which facts to save, update or recall across sessions, instead of only replaying past conversation.
- [Agentic workflow](https://www.getdynamiq.ai/glossary/agentic-workflow): A business process modeled as a graph of steps where at least one step is an agent that reasons and chooses its own actions, not a fixed script.
- [AI agent](https://www.getdynamiq.ai/glossary/ai-agent): A system that pairs a large language model with tools, memory and a control loop so it can plan and carry out multi-step tasks toward a goal.
- [AI agent platform](https://www.getdynamiq.ai/glossary/ai-agent-platform): Software for building, deploying, governing and monitoring AI agents in one place, from models and tools to approvals, evaluations and traces.
- [AI gateway](https://www.getdynamiq.ai/glossary/ai-gateway): A single endpoint that routes chat completion requests to many model providers behind one credential, so applications do not hold provider keys.
- [AI governance](https://www.getdynamiq.ai/glossary/ai-governance): The policies, controls and evidence an organization uses to decide how AI may be used, who is accountable, and how its behavior is checked over time.
- [AI guardrails](https://www.getdynamiq.ai/glossary/ai-guardrails): Checks placed around a model or agent, such as input screening and output validation, that flag or block unsafe behavior before it reaches anyone.
- [AI observability](https://www.getdynamiq.ai/glossary/ai-observability): The practice of recording every step an agent or workflow takes so its behavior, cost and failures can be inspected after the fact.
- [Air-gapped deployment](https://www.getdynamiq.ai/glossary/air-gapped-deployment): A deployment with no network path to the public internet, used when data must never leave a physically or logically isolated environment.
- [Approval gate](https://www.getdynamiq.ai/glossary/approval-gate): A control on a specific workflow step that pauses execution until a person approves, edits or rejects it, every time that step runs.
- [Barge-in and turn detection](https://www.getdynamiq.ai/glossary/barge-in-and-turn-detection): How a voice agent knows a caller has stopped talking, and how it stops speaking immediately if the caller interrupts.
- [Chunking](https://www.getdynamiq.ai/glossary/chunking): Splitting a document into smaller pieces before it is embedded and indexed, so retrieval returns focused passages instead of whole files.
- [Computer use agent](https://www.getdynamiq.ai/glossary/computer-use-agent): An agent that operates a computer the way a person would, controlling a browser or desktop through clicks, typing and screenshots.
- [Context window](https://www.getdynamiq.ai/glossary/context-window): The maximum amount of text, measured in tokens, a model can read and generate in one call, including the prompt, history and output.
- [Conversational AI](https://www.getdynamiq.ai/glossary/conversational-ai): Technology that lets people talk with software in natural language, by text or voice, and have it understand the request and respond or act on it.
- [Data residency](https://www.getdynamiq.ai/glossary/data-residency): A guarantee about which country or region a system stores and processes its data in, used to meet legal or contractual requirements.
- [Document parsing](https://www.getdynamiq.ai/glossary/document-parsing): Converting a file such as a PDF, scan or slide deck into clean, structured text, typically Markdown, that a model or index can use.
- [Embeddings](https://www.getdynamiq.ai/glossary/embeddings): Numeric vectors that represent the meaning of a piece of text, so pieces with similar meaning end up close together in vector space.
- [EU AI Act](https://www.getdynamiq.ai/glossary/eu-ai-act): The European Union's risk-based regulation of AI systems, Regulation (EU) 2024/1689, with obligations that scale to how risky a given use is.
- [Fine-tuning](https://www.getdynamiq.ai/glossary/fine-tuning): Further training a pretrained model on a smaller, specific dataset so it performs better on a narrower task, tone or domain.
- [Forward-deployed engineer](https://www.getdynamiq.ai/glossary/forward-deployed-engineer): An engineer who works inside a customer's own environment to build and ship the customer's first production use of a platform.
- [GDPR](https://www.getdynamiq.ai/glossary/gdpr): The EU's General Data Protection Regulation, Regulation (EU) 2016/679, governing how personal data of people in the EU and EEA is handled.
- [GraphRAG](https://www.getdynamiq.ai/glossary/graphrag): A retrieval method that answers questions by walking a knowledge graph of entities and relationships, not only by matching text similarity.
- [Grounding](https://www.getdynamiq.ai/glossary/grounding): Tying a model's answer to specific, retrievable source material, so the answer can be traced back to a document rather than training data.
- [Hallucination](https://www.getdynamiq.ai/glossary/hallucination): An answer a model states with confidence that is not supported by its source material or by fact, presented as if it were true.
- [HIPAA](https://www.getdynamiq.ai/glossary/hipaa): The US Health Insurance Portability and Accountability Act of 1996, whose Privacy and Security Rules govern protected health information.
- [Human in the loop](https://www.getdynamiq.ai/glossary/human-in-the-loop): A design pattern where a person reviews, confirms or supplies information at a defined point in an otherwise automated process.
- [Intelligent document processing](https://www.getdynamiq.ai/glossary/intelligent-document-processing): Using AI to read unstructured documents such as scans, PDFs and forms and turn them into structured, validated data fields.
- [Knowledge graph](https://www.getdynamiq.ai/glossary/knowledge-graph): A database of entities and the relationships between them, such as a person working at an organization, used to answer connection questions.
- [KYC and AML automation](https://www.getdynamiq.ai/glossary/kyc-and-aml-automation): Using software, including AI, to run the identity checks and transaction monitoring that anti-money-laundering and know-your-customer rules require.
- [LLM as a judge](https://www.getdynamiq.ai/glossary/llm-as-a-judge): Using a large language model to score another model's output against a written rubric, in place of, or alongside, a human reviewer.
- [LLM evaluation](https://www.getdynamiq.ai/glossary/llm-evaluation): Scoring an LLM or agent's outputs against test data with defined metrics, so changes in quality are measured rather than judged by feel.
- [LLM inference](https://www.getdynamiq.ai/glossary/llm-inference): Running a trained model to produce an output for a given input, as opposed to training the model in the first place.
- [LLM tracing](https://www.getdynamiq.ai/glossary/llm-tracing): A recorded, node-by-node execution tree of one run, including every prompt, tool call, retrieved document and token count.
- [LoRA](https://www.getdynamiq.ai/glossary/lora): Low-Rank Adaptation, a fine-tuning method that trains a small set of extra weights on top of a frozen base model, not the whole model.
- [Model Context Protocol (MCP)](https://www.getdynamiq.ai/glossary/model-context-protocol): An open protocol that lets an AI agent discover and call tools exposed by an external server over a standard interface.
- [Model routing](https://www.getdynamiq.ai/glossary/model-routing): Automatically or programmatically directing a request to one of several possible models, based on name, cost, capability or availability.
- [Multi-agent system](https://www.getdynamiq.ai/glossary/multi-agent-system): Two or more agents working together on one task, each with a narrower role, coordinated by delegation or an explicit control flow.
- [Online evaluation](https://www.getdynamiq.ai/glossary/online-evaluation): Automatically scoring a sampled share of a deployed system's live production traffic on an ongoing basis, not a one-time test.
- [Open-weight model](https://www.getdynamiq.ai/glossary/open-weight-model): A model whose trained weights are published for anyone to download and run, unlike a model only reachable through a hosted API.
- [PII detection](https://www.getdynamiq.ai/glossary/pii-detection): Automatically flagging personally identifiable information, such as names, emails or account numbers, before it reaches a model.
- [Prompt injection](https://www.getdynamiq.ai/glossary/prompt-injection): An attempt, hidden in user input or a retrieved document, to override a model's instructions and make it act against its role.
- [Reranking](https://www.getdynamiq.ai/glossary/reranking): Re-scoring and reordering a first pass of retrieved documents with a more precise model, so the most relevant ones reach the model first.
- [Retrieval-augmented generation (RAG)](https://www.getdynamiq.ai/glossary/retrieval-augmented-generation): Retrieving relevant passages from your own documents and giving them to a model as context, so its answer is grounded in that material.
- [Role-based access control (RBAC)](https://www.getdynamiq.ai/glossary/role-based-access-control): Granting permissions based on a person's assigned role, such as admin or member, rather than configuring access for each person.
- [Self-hosted AI platform](https://www.getdynamiq.ai/glossary/self-hosted-ai-platform): An AI platform installed and run inside an organization's own infrastructure, cloud account or data center, not a vendor's shared cloud.
- [Single sign-on (SSO)](https://www.getdynamiq.ai/glossary/single-sign-on): Letting people log in to a platform using the identity and credentials their organization already manages, not a separate password.
- [SIP trunking](https://www.getdynamiq.ai/glossary/sip-trunking): A connection between a phone network and a voice application over the internet using the Session Initiation Protocol, not analog lines.
- [SOC 2](https://www.getdynamiq.ai/glossary/soc-2): An audit standard from the AICPA evaluating a service organization's controls against the Trust Services Criteria: security, plus optional categories.
- [Sovereign AI](https://www.getdynamiq.ai/glossary/sovereign-ai): AI that an organization or country controls end to end: where it runs, which models it uses, where its data and records live, and who operates it.
- [Speech to text](https://www.getdynamiq.ai/glossary/speech-to-text): Converting spoken audio into written text in real time, the first stage of a pipeline voice agent's turn.
- [Structured output](https://www.getdynamiq.ai/glossary/structured-output): Constraining a model's final answer to a JSON schema, so downstream code receives typed, parseable data instead of free-form prose.
- [Text to speech](https://www.getdynamiq.ai/glossary/text-to-speech): Converting written text into spoken audio, the final stage of a pipeline voice agent's turn, or one channel of a realtime model.
- [Tool calling](https://www.getdynamiq.ai/glossary/tool-calling): A model's ability to invoke a defined function or external action mid-response, then read the result back before continuing.
- [Vector database](https://www.getdynamiq.ai/glossary/vector-database): A database built to store embeddings and search them by similarity, returning the nearest vectors to a query, not exact matches.
- [Voice agent](https://www.getdynamiq.ai/glossary/voice-agent): A real-time conversational agent that talks with people over audio, on a phone call, in a browser, or over a raw audio connection.
- [WebRTC](https://www.getdynamiq.ai/glossary/webrtc): An open, browser-native protocol for real-time audio and video that lets a web page or app stream microphone audio to a voice agent.

## Docs

- [Documentation](https://docs.getdynamiq.ai): platform, SDK and API reference
- [Docs index for LLMs](https://docs.getdynamiq.ai/llms.txt)

## Optional

- [Full site content](https://www.getdynamiq.ai/llms-full.txt): product, solutions, customer stories and glossary as one markdown file