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.
· 7 min read
Notes on putting AI agents into production.
Guides, comparisons and engineering notes from the Dynamiq team.
Latest posts
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.
· 7 min read
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.
· 8 min read
Best Langflow alternatives for AI workflow and 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.
· 9 min read
Best Sana alternatives for AI knowledge and 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.
· 7 min read
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.
· 7 min read
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.
· 7 min read
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.
· 6 min read
Automating mortgage pre-approval with Dynamiq and Amazon Nova for banks and lenders
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.
· 5 min read
How to create an AI agent from scratch: a 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.
· 8 min read
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.
· 8 min read
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.
· 9 min read
Multi-agent AI systems: definition, benefits, limitations and how to build one
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.
· 8 min read
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.
· 9 min read
LLM agents explained: a complete guide
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.
· 7 min read
AI-driven due diligence through to exit: how private equity firms use GenAI
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.
· 7 min read
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.
· 8 min read
Dynamiq to launch enterprise-ready AI agents in IBM watsonx Orchestrate's 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.
· 4 min read
Agentic RAG with Apache Iceberg and Dynamiq on IBM 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.
· 6 min read
Generative AI for enterprises: practical ways 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.
· 6 min read
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.
· 4 min read
Understanding agentic AI: definition, benefits and applications in business
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.
· 8 min read
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.
· 4 min read
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.
· 4 min read
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.
· 5 min read
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.
· 4 min read
Agent orchestration patterns: linear and adaptive multi-agent systems 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.
· 5 min read
Automating customer support in banking with agentic RAG
How agentic RAG automates bank customer support: one agent retrieves your procedures, another acts through your APIs, with approvals and traces.
· 6 min read
Building a conversational AI agent with memory in 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.
· 5 min read
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.
· 4 min read
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.
· 7 min read
How the EU AI Act impacts your business: deadlines, obligations and fines
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.
· 8 min read
Mastering LLM security: an air-gapped approach 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.
· 6 min read
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.
· 7 min read
GenAIOps for enterprises: the build vs. buy decision
GenAIOps is how enterprises run generative AI and agents in production. Compare building a platform with buying one: costs, risks and a checklist.
· 8 min read
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.
· 6 min read
Less risk and no fee: an 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.
· 7 min read
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.
· 7 min read
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.
· 7 min read
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.
· 6 min read
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.
· 7 min read
Estimate what an agent could save.
Run your numbers through the ROI calculator, then validate them with our engineers.