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Dynamiq

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Build, deploy, and monitor enterprise-grade AI agents and agentic workflows — all in your own infrastructure.

Freemium: Starting at $29/mo
#ai-agents #low-code/no-code #workflows
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Updated: April 4, 2026

Dynamiq is an enterprise LLMOps platform founded in 2024 by Vitalii Duk and headquartered in San Francisco, California. It enables engineering and AI teams to build, deploy, monitor, and fine-tune AI agents and agentic workflows using a low-code visual interface, with support for on-premise, hybrid, and cloud deployments. The platform is SOC 2, GDPR, and HIPAA compliant — designed specifically for regulated industries that need full data ownership and governance.
• Low-Code Workflow Builder — drag-and-drop canvas to visually compose multi-step agentic pipelines with LLM nodes, conditional logic, Python code blocks, RAG retrievals, and tool integrations; no deep ML engineering required.
• Multi-Model LLM Support — integrates natively with OpenAI, Anthropic Claude, Google Gemini, Meta Llama 2, Hugging Face, and Replicate; switch or combine models within a single workflow without rewriting logic.
• RAG Knowledge Bases — ingest PDFs, documents, and company data sources into vector databases in minutes; agents retrieve and cite your proprietary data rather than relying on generic LLM knowledge.
• Two-Click LLM Fine-Tuning — fine-tune open-source LLMs on your own datasets directly within the platform; models you build become your owned assets, not rented API endpoints.
• Guardrails & Output Validation — applies pre-built and custom validators to every LLM response to detect hallucinations, sensitive data exposure, PII leaks, and format violations before output reaches users.
• Observability & Evaluations — logs all agent interactions, tracks key performance metrics, runs large-scale LLM quality evaluations, and provides real-time debugging views so engineering teams can monitor production behavior precisely.
• On-Premise & VPC Deployment — runs entirely within your own corporate infrastructure, VPC, AWS, IBM Cloud, or IBM watsonx; satisfies strict regulatory requirements in finance, healthcare, and the public sector.
• Multi-Agent Orchestration — design and deploy networks of specialized LLM agents that collaborate on complex tasks, share context, and connect to internal APIs — all managed from a single visual interface.
Pros
  • ✔ On-premise and VPC deployment satisfies HIPAA, SOC 2, and GDPR compliance out of the box — rare at this price point
  • ✔ Supports OpenAI, Anthropic, Gemini, Llama 2, Hugging Face, and Replicate in one platform — no single-vendor lock-in
  • ✔ Two-click LLM fine-tuning lets teams own their models rather than paying per-token rental fees indefinitely
  • ✔ Low-code canvas reduces a 6-month AI development cycle to hours according to company-published benchmarks
  • ✔ Built-in guardrails prevent PII leaks, hallucinations, and format violations before output ever reaches end users
  • ✔ Free plan includes 1 deployed workflow and 1,000 executions per month — enough to meaningfully evaluate the platform
  • ✔ Forbes-covered and pre-seed funded in 2024, signaling early enterprise validation from credible third parties
Cons
  • × Growth plan jumps to $975/month — a steep step up from Solo at $29/month with no mid-tier option in between
  • × Fine-tuning and multi-user collaboration are locked behind the $975/month Growth plan, excluding solo developers and small teams
  • × The platform was founded in 2024 and is still early-stage — long-term reliability and roadmap maturity remain unproven vs. established LLMOps competitors
  • × Enterprise pricing is not publicly listed, requiring a sales call before you can evaluate total cost of ownership
  • × Community and email-only support on Free and Solo plans; dedicated support requires enterprise engagement
  • × With 11–50 employees, the team is small relative to the complexity of enterprise deployments it targets
Free ($0/mo) 1 user, 1 deployed workflow, 1 RAG knowledge base, 1,000 workflow executions per month, community-based customer support.
Solo ($29/mo) 1 user, 5 deployed workflows, 5 RAG knowledge bases, 10,000 workflow executions per month, email-based customer support.
Growth ($975/mo) 10 users, 20 deployed workflows, 20 RAG knowledge bases, 20 fine-tuned models, 100,000 workflow executions per month, email-based customer support.
Enterprise (Custom Pricing) On-premise and VPC deployment, dedicated infrastructure within your own cloud environment, PII protection and data residency controls, fine-grain access controls and user permissions, priority support with SLA guarantees, custom execution and user limits.

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