4A LABS AI
apartmentENTERPRISE AI

Our engineer works
from inside
your team.

Most enterprise AI projects stall at the presentation, because the team writing the solution never sees the floor. We do the opposite: our engineer sits at the same table as your team, with your data, on your systems.

START A PROJECTarrow_forwardHOW IT RUNS
groups Inside your teamshield Security and compliance from day oneinventory_2 Code and model stay with you
An engineer with a laptop at the same table as the client's operations team; the production floor is visible through the glass behind them.
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MODEL

Forward Deployed Engineer

code

METHOD

Hyper Engineering, not vibecoding

hub

INTEGRATION

ERP / MES / CRM and data

handshake

OUTCOME

A delivery you can take over

An engineer in a hard hat and vest holding a laptop next to an industrial machine; data lines run from the machine to the laptop.

Representative scene.

MODEL

The FDE Model

Our engineer works inside your team, walks the floor and reads the systems first-hand. Decisions take a day because the person who builds the solution is in the room.

  • person_pinThe engineer works inside your team
  • check_circleSees the floor and the process first-hand
  • check_circleDecisions take a day, not weeks
  • check_circleUses your tools and your channels
Two engineers seen from behind reviewing work at a large monitor; a pipeline of connected steps runs across the screen.

Representative scene.

METHOD

Hyper Engineering

AI makes us fast, but it does not take responsibility. Every change is reviewed, tested and shipped through a pipeline your team can read and run.

  • codeAI is used for speed, not for responsibility
  • check_circleEvery change is reviewed
  • check_circleTests and CI/CD are standard, not an option
  • check_circleArchitectural decisions come with written rationale
A server room with an open rack; a glowing shield outline hovers in front of it.

Representative scene.

REQUIREMENTS

Enterprise Requirements

Security and compliance are not a final phase. Authentication, data rules, audit trails and on-prem deployment are part of the design from the first week.

  • verified_userAuthentication and role-based authorisation
  • check_circleData protection and retention rules from the start
  • check_circleRuns on your own servers or on edge devices
  • check_circleAudit trail and logging
HOW IT RUNS

How an Enterprise AI Project Moves

01

Embedding

The engineer joins the team; process, systems and data are studied first-hand.

02

Scope and Metric

Which problem, and by which metric it counts as solved — written down.

03

PoC

A working version on your data in a tight scope; the result is measured and reported.

04

Production

Security, authorisation and integrations are completed; it goes live.

05

Handover

Code, model, documentation and operating knowledge are transferred to your team.

handshake

We do not sell dependency.

Your team being able to operate the system at the end of the project is part of how we measure success.

START A PROJECTarrow_forward
Server racks on one side and a production line on the other, connected by flowing data lines.

Representative scene.

INTEGRATION

AI Between Your Systems, Not Beside Them

A model that does not talk to ERP, MES or CRM stays a demo. We build the layer that reads from your systems, makes the decision and writes the result back where your team already works.

  • hubTwo-way connection with ERP, MES and CRM
  • dnsRuns on your own servers or edge devices
  • policyRole-based access and an audit trail
  • warningFailures are visible: monitoring and alerts
TYPICAL WORK

What We Build on the Enterprise Side

hub

System Integration

An AI-driven data flow and decision layer between ERP, MES, CRM and production systems.

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AI Agents and Automation

Agents that run repeating office and operations processes end to end.

visibility

Computer Vision

Camera-based inspection and reporting across production, quality and safety.

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Data and Forecasting

Demand, failure and stock forecasting; decision support from the data you already have.

description

Document Processing

Reading, validating and posting invoices, waybills, contracts and forms.

build

Hardening What You Have

Making working but slow, fragile or unmaintained software solid again.

FAQ

Frequently Asked Questions

How is 4A Labs AI different from an agency?

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Our engineer works inside your team as a Forward Deployed Engineer, sees the process first-hand and builds alongside the people who will take the system over.

Will we become dependent on you?

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No. Code, model, documentation and operating knowledge are handed over to your team; your team being able to run the system is part of how we measure success.

How do you use AI in software development?

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With Hyper Engineering: AI is used for speed, not responsibility. Every change is reviewed, tests and CI/CD are standard, and architectural decisions come with written rationale.

Pick one process.
Let us set the metric together.

On the first call we settle which problem counts as solved, and by which number.

  • check_circle The first call is free and technical
  • check_circle We start under NDA
  • check_circle Scope and price are clear up front

PROJECT REQUEST FORM