AI strategy and implementation — Claude, OpenClaw, and beyond.
Not sure which AI tool fits your stack? Renato looks at what you actually do, figures out where AI helps, and builds the implementation with you.
TOOLS & PLATFORMS
What's covered
Claude & LLM Integration
Claude API, Claude Code, and MCP server setups that turn plain-English prompts into deployed workflows. Model selection included: Claude, OpenAI, or Ollama, depending on your budget.
OpenClaw Deployment
Self-hosted AI agents for Discord, Telegram, or your own internal tools. OpenClaw runs on your VPS or local machine. Your data stays local, no subscription fees.
AI Stack Audit
A full review of your current tools and workflows. You get a prioritised list: what to automate first, which model fits, and whether to build or buy each piece.
How it works
Discovery call
Walk through your current stack, where it breaks down, and what you want to do. Straight conversation.
Roadmap
A written recommendation: tools, models, build order, and cost estimates.
Implementation
Hands-on build alongside your team, or a fully delivered solution. Your call.
From the blog
Free Claude Code? Here's How
Run Claude Code for free using an OpenRouter API key and a local proxy. Switch between free models in 10 seconds.
I Built A Discord AI Army For Free
Deploy OpenClaw on a VPS, connect multiple Discord bots, create separate agents per channel — full walkthrough.
I Run A Free Private AI At Home
Set up OpenClaw locally with Docker and Ollama — a private AI agent on your machine, no subscription, no tracking.
One Prompt Builds Any n8n Workflow
Wire the n8n MCP server with Claude Code so one plain-English prompt generates a fully deployable workflow.
Common questions
How do I know which AI model is right for my workflow?
It depends on your task type, budget, and data privacy requirements. Claude is strong for reasoning and long-context work. GPT-4o is strong for structured output. Ollama runs locally with no data leaving your machine. The audit covers this — we look at what you're actually doing and recommend accordingly.
What happens after the discovery call?
You get a written roadmap within 48 hours: which tools to use, in what order, and an honest cost estimate. No commitment needed beyond the call.
Do you build it, or just advise?
Both options are available. Some clients want an independent recommendation and handle implementation themselves. Others want us to build alongside their team or deliver the solution directly.
What does the AI stack audit cover?
A review of your current tools, workflows, and where they break down. You get a prioritised list: what to automate first, which model fits each task, and whether to build or buy. Delivered as a written document.
Not sure where to start with AI?
Describe your workflow and current tools. You'll get an honest recommendation within 24 hours.
Book a discovery call