Guides, tutorials, and insights on AI automation
Every platform demos well. The seven layers that decide whether a pilot survives — deployment, tenancy, audit, cost control, system access, retrieval, agents — and a requirements table for your RFP.
The six properties an automation needs before it can run without anyone watching, the eight step types that make up a real workflow, and four processes that repay the effort quickly.
“Runs in Docker” and “operates inside your perimeter” are different claims. What you take on, which calls still leave, and an eight-question checklist for any vendor.
Helpdesk suites, dedicated resolution engines, AI platforms and DIY — with the three questions that decide your shortlist and an evaluation you can run in two weeks.
Fin resolves tickets from help centre content inside Intercom. Orckai answers from documents and live systems, runs back-office workflows, and self-hosts. An honest scope comparison.
Generated MCP tools, read-only scoping, bounded results, identity pass-through, and the two failure modes that surprise everyone. The design that gets past a security review.
Drawing a flow is the easy half. Tenancy, permissioned database access, an embeddable interface, audit and spend caps are the half that takes a quarter.
Eight tools called “agent platforms” are really four categories doing four jobs. What each group is good at, where each leaves you holding the work, and a shortlist you can defend.
LangChain is a framework you write code in; Orckai is a platform you operate. Retrieval, database access, multi-tenancy and audit compared — including when the framework is the better call.
File monitoring, spreadsheet validation, scheduled reporting, incident sync, and health monitoring. Practical workflows that replace the "someone checks it every morning" pattern.
Process arrays of files, records, or API results with foreach steps. Handle partial failures, filter with sub-step conditions, and get structured success/failure summaries.
Reuse your existing login system with an embedded AI widget. Learn the identity handoff model for custom auth, Auth0, Okta, Clerk, WorkOS, and SAML-backed apps.
Build an AI chat widget that captures leads, triggers smart notifications, and lets your team take over conversations in real time — all in one script tag.
Add an AI-powered chat widget to any website with a single script tag. Connect it to your knowledge base for instant, accurate answers with citations and enterprise-grade security.
Build an AI pipeline that triggers when resumes land in Google Drive, SharePoint, or OneDrive. Score candidates, filter by fit, and notify HR — zero manual effort.
Understand the protocol that lets AI models access databases and APIs securely. Learn how MCP works, why it matters, and how to get started.
Feature-by-feature breakdown of AI agents, system connections, knowledge bases, widgets, deployment, and pricing between Orckai and n8n.
Compare built-in AI agents, system connections, and RAG knowledge bases against Make's 1,500+ app integrations and visual scenario builder.
Two AI-focused platforms compared: full orchestration with system connections and workflow automation vs open-source LLM app development with broad model support.
Step-by-step tutorial for generating an MCP server that connects your AI agents to a PostgreSQL database. No code required, deployed as a Docker container.
Learn how to build, configure, and deploy AI agents without writing a single line of code. Choose from 19+ LLM models, attach tools, and go live in minutes.
Compare the trade-offs between cloud-hosted and self-hosted AI platforms. Security, cost, compliance, and control considerations for enterprise teams.
From customer support triage to financial report generation, discover real-world workflows you can build today with AI agents and automation.
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