- Developers & Engineers: Rapidly prototype, orchestrate, fine-tune, and deploy AI agents and workflows using APIs or visual tools.
- Enterprises & Compliance Teams: On-prem or VPC deployment with SOC 2, HIPAA, GDPR compliance ensuring data sovereignty.
- Product & IT Teams: Manage lifecycle of AI assistants, monitor performance, enforce guardrails, and troubleshoot via observability.
- Data & Analytics Teams: Build RAG-powered knowledge bases and autonomous data-analyst agents with low-code templates.
- Business Users & Non-Tech Teams: Use intuitive drag-and-drop tools to automate workflows without writing extensive code.
How to Use Dynamiq?
- Agent Builder: Use low-code visual editors with pre-built templates and Python extension to create AI agents.
- Workflow Automation: Drag-and-drop workflow modules to automate tasks like document review, fraud detection, and support response.
- RAG & Knowledge Integration: Connect enterprise data sources and enable retrieval-augmented generation.
- Deployment & Guardrails: Deploy agents on-premise or cloud-privately, setting validation rules for structured JSON/YAML output, filters, and policies.
- Fine-Tuning & Observability: Fine-tune LLMs with private data; monitor interactions, quality, token usage, error rates, and receive alerts.
- Unified GenAI Ops: Combines agent creation, RAG, deployment, observability, and guardrails in one platform.
- Enterprise Security: SOC 2, HIPAA, GDPR support with VPC, on-prem deployment, fine-grained access control.
- Low-Code, High Flexibility: Visual builder plus Python extensibility enables both non-technical and technical teams to customize agents.
- Deep Observability: Live metrics, logs, LLM-as-judge evaluation, alerting, and drift detection ensure reliability.
- Multi-Agent Orchestration: Support for specialized agents coordinating within workflows to handle complex, modular tasks.
- End-to-end platform—from idea to production—with no glue code
- Strong enterprise compliance and security posture
- Visual low‑code builders with developer-level customization
- Built-in fine-tuning and observability pipelines
- Scalable multi-agent orchestration and RAG-ready workflows
- Platform complexity may be overwhelming for smaller teams
- On-prem deployments require infrastructure management
- May be costly for low-volume or small-scale use cases
Free
$ 0.00
1 deployed workflow
1 RAG knowledge base
1,000 workflow executions per month
Community-based customer support
Solo
$ 29.00
5 deployed workflows
5 RAG knowledge bases
10,000 workflow executions per month
Email-based customer support
Starter
$ 125.00
10 deployed workflows
10 RAG knowledge bases
10 fine-tuned models
50,000 workflow executions per month
Email-based customer support
Growth
$ 975.00
20 deployed workflows
20 RAG knowledge bases
20 fine-tuned models
100,000 workflow executions per month
Email-based customer support
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Editorial Note
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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