Dynamiq
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Platform for building and managing on-premise GenAI applications.
Dynamiq Product Information
Dynamiq — The Operating Platform for GenAI Applications
Dynamiq is an enterprise-grade platform designed to accelerate the development, deployment, and governance of GenAI-powered applications. It provides a low-code agentic builder, robust observability, RAG tooling, LLM deployment, fine-tuning, and on-premise options to keep data under your control.
Overview
Dynamiq enables teams to build agentic GenAI applications in hours rather than months. It consolidates workflows, data sources, and model management into one platform with interfaces designed for IT, data science, and business users. Key value propositions include rapid prototyping, on-premise deployment for data sovereignty, cost efficiency, and strong governance to ensure compliance and security.
How it Works
- Build: Use the low-code agentic builder to assemble AI-powered agents and workflows tailored to business use cases.
- Integrate: Connect company data sources with RAG (Retrieve- Augment-Generate) to enhance responses.
- Deploy: Push models and workflows to private infrastructure with on-premise options and VPC isolation.
- Govern: Leverage observability, guardrails, and fine-tuning controls to maintain precision and reliability.
- Operate: Monitor, audit, and iterate with rapid prototyping and testing within the platform.
Core Capabilities
- Agentic GenAI Development: Build conversational workflows and AI agents that can perform complex, multi-step tasks.
- Data Integration (RAG): Centralize data sources and retrieve relevant information to improve AI outputs.
- Deployments: Flexible deployment options including on-premise, VPC-bound, and cloud-adjacent configurations.
- Observability: Real-time monitoring, logging, and diagnostics for rapid issue resolution.
- Guardrails: Built-in safety and validation to ensure outputs align with expectations.
- Fine-Tuning: Fine-tune open-source LLMs on private data to customize behavior.
- Collaboration: Shared workspaces with company-wide guardrails for governance and teamwork.
- Private Infrastructure: Full control over data and compliance with regulatory requirements.
- Data Security & Privacy: Bank-grade security, GDPR, HIPAA compliance, and strict access controls.
- Time-to-Value: Prototyping and deployment can accelerate from months to hours.
Use Cases & Industries
Dynamiq supports enterprise use cases across Financial Services, Healthcare, and Public Sector, including AI assistants, knowledge bases, and enterprise workflow automations.
Security, Compliance & Data Control
- On-Premise Deployment: Retain full control over data and ensure regulatory compliance.
- Private LLMs: Train and deploy models within your own infrastructure (VPC).
- Data Residency & Privacy: PII protection and secure data processing with GDPR/HIPAA alignment.
- Access Controls: Fine-grained permissions and robust security measures.
What’s Included
- Low-code agentic builder for rapid development
- On-premise / VPC deployment options for data sovereignty
- Observability suite for real-time metrics, tracing, and debugging
- RAG tooling to enrich AI responses with internal data
- Fine-tuning of open-source LLMs on private data
- Guardrails and validation to ensure output quality and safety
- Collaboration spaces with governance controls
- End-to-end security and regulatory compliance support
How to Get Started
- Start for free: Explore the platform with a no-cost trial to prototype your GenAI use cases.
- Plan your deployment: Choose between on-premise or VPC-bound deployments based on data requirements.
- Build and iterate: Use the low-code builder to create agents, connect data sources, and deploy in days rather than months.
Pricing & Resources
- Pricing: Flexible plans to accommodate enterprise needs.
- Resources: Documentation, blogs, and partner network to accelerate implementation.
- Training & Support: Access to best practices, templates, and expert guidance.
Why Dynamiq
Dynamiq helps organizations extract ROI from GenAI initiatives by reducing development time, increasing governance, and enabling private-data models that stay within corporate boundaries, all while maintaining speed and adaptability.