What does 4M Labs do?

4M Labs builds revenue, operations, and AI-native systems for companies. Websites, lead capture, automation, internal tools, dashboards, and AI workflows.

What engagement models does 4M Labs offer?

4M Labs offers Revenue System Sprints, Operations System Sprints, Knowledge System Sprints, Managed DevSquads, and Squish. These cover fixed-scope delivery, monthly retainers, and custom production work.

Can 4M Labs build custom AI agents?

Yes. 4M Labs designs and builds AI workflows, automation systems, internal tools, dashboards, and software that connects to real business processes.

Does 4M Labs only build AI products?

No. 4M Labs builds revenue systems, operations systems, knowledge systems, and product systems. Sometimes that means a website. Sometimes automation. Sometimes AI. The point is business leverage.

How much do 4M Labs services cost?

Revenue System Sprints from $1.5K-$5K. Operations System Sprints from $3K-$10K. Knowledge System Sprints from $5K-$20K. Managed DevSquads available for ongoing capacity. 4M Labs provides detailed proposals with transparent pricing for every engagement.

How long does a typical 4M Labs project take?

Revenue System Sprints are 14-21 days. Operations System Sprints are 10-15 days. Knowledge System Sprints are 2-4 weeks. Managed DevSquads are ongoing monthly. 4M Labs provides detailed timelines upfront and uses production-ready handoff criteria.

How is 4M Labs different from other development agencies?

4M Labs builds business systems that help companies get more leads, automate follow-up, and run smoother. Under the hood, we use software, automation, and AI where it makes sense. Each engagement has clear scope, a fixed timeline, and a production-ready outcome instead of open-ended billing.

AI Product Engineering

AI that ships.
Not just demos.

We build production-ready AI features, agents, and automation systems. Fixed scope. Fixed timeline. Working software.

Start a Revenue System Sprint Read the AI Cookbook

What We Build

Real AI systems that solve real problems. Not research papers.

smart_toy

AI Agents

Autonomous agents that reason, plan, and execute. LangGraph, CrewAI, or custom architectures.

database

RAG Systems

Retrieval-augmented generation for your documents, knowledge base, or internal data.

bolt

Workflow Automation

AI-powered workflows that replace manual processes. Document processing, data extraction, decision support.

code

LLM Integration

Add GPT, Claude, or open-source LLMs to your product with proper prompt engineering and guardrails.

visibility

Computer Vision

Image analysis, object detection, OCR, and visual AI for industrial and consumer applications.

psychology

Custom ML Models

When off-the-shelf models don't work. Custom training, fine-tuning, and deployment.

The Revenue System Sprint

One problem. One model. Shipped in 21 days.

Days 1-5

Scope & Data

Define the single-variable outcome. Audit data availability. Clean the dataset. Establish baseline metrics.

Days 6-15

Build & Tune

Select optimal model architecture. Implement RAG if needed. Tune for cost and latency. Ship working API.

Days 16-21

Integrate & Handover

Wrap model in robust API. Build demo UI. Deploy to production. Full documentation and handoff.

Deliverables

check_circleProduction-ready API endpoint

check_circleSource code and model weights

check_circleDemo User Interface (React)

check_circleArchitecture Documentation

check_circleDeployment pipeline

check_circlePerformance benchmarks

Our AI Stack

We pick the right tool for the problem. Not the trendy one.

OpenAI GPT-4o

Anthropic Claude

LangGraph

CrewAI

LlamaIndex

Pinecone

Weaviate

ChromaDB

FastAPI

Next.js

React

TypeScript

PostgreSQL

Redis

Docker

AWS/GCP

Frequently Asked Questions

What is AI product engineering?

AI product engineering is the practice of building production-ready AI features, agents, and automation systems that solve real business problems. Unlike generic AI consulting, we ship working software with clear scope, fixed timelines, and production-ready handoffs.

What AI technologies does 4M Labs work with?

We work with LLMs (OpenAI, Anthropic, open-source models), RAG systems, AI agents (LangGraph, CrewAI, custom), vector databases, workflow automation, computer vision, and custom ML models. We select the right tool for your specific problem, not the trendy one.

How does a Revenue System Sprint work?

A Revenue System Sprint is a 21-day fixed-scope engagement. We define one business problem, build a production-ready AI solution, and hand off with full documentation. The sprint includes data pipeline, model selection, API development, demo UI, and deployment.

Can you integrate AI into our existing product?

Yes. Most of our AI work involves adding AI capabilities to existing products. We integrate with your current stack, data sources, and workflows. The Revenue System Sprint is specifically designed for this use case.

Do we need to have data ready for AI?

Not necessarily. We help audit your data availability, clean datasets, and establish baselines during the first phase of any engagement. If you have structured data (databases, CSVs, APIs), we can work with it.

What is the difference between AI consulting and AI engineering?

AI consulting gives you a strategy document. AI engineering gives you working software. 4M Labs does engineering. Every engagement ends with production-ready code, deployed infrastructure, and documentation your team can maintain.

Ready to ship AI features?

Book a strategy call. We'll scope your Revenue System Sprint in 30 minutes.

Book a Strategy Call

AI that ships.Not just demos.