Before a new application
We check which parts of the process are worth designing with AI from the start.
AI audit before implementation
BeeLogic / map of sensible AI use cases
Before you implement AI, check where it should really work.
An AI audit organizes ideas, data, risks and first scenarios. It can begin a larger web project or stand alone as a stage that lets you decide without the pressure of random tools.
use caseselection of the first area
danereadiness, access and risks
roadmapapilot and implementation sequence
An audit without theatre
A good AI audit does not end with a list of fashionable tools. It ends with a decision on what is worth implementing first.
First we examine how the company works: where repetition appears, where documents get lost, where context is missing and where people make decisions based on incomplete data.
01Processwhat takes time today
02Datawhat AI can safely read
03Riskwhere control is needed
04Pilotwhat to implement first
Where an audit makes sense
The audit connects AI with real BeeLogic services.
It does not have to start a large program. It can precede a website, application, customer portal, shop, document workflow or a completely separate AI implementation.
Before e-commerce
We look for places where AI can help with service, reports, descriptions or requests.
Before document workflow
We assess which documents can be read, classified and passed further.
As a separate starting point
We choose the first use case without rebuilding the whole environment.
Project scope
Three audit levels — from a quick decision to an implementation roadmap.
We match the scope to the maturity of the company and the number of processes. The goal is not a document for its own sake, but a decision on whether and where AI makes sense.
AI map
Quickly organizing ideas and choosing the first direction.
- workshop with the team
- list of use cases
- initial data assessment
- recommendation for the first pilot
Implementation audit
A deeper analysis of the process, data, risks and integrations.
- process map
- data sources and access
- risk and control assessment
- pilot specification
AI roadmap
A phased implementation plan for several areas of the company.
- business priorities
- implementation order
- architecture and integrations
- post-pilot development plan
Use scenario
The company has five AI ideas. After the audit, one first move remains.
Instead of starting with everything at once, we choose the process with the highest repeatability, the best data access and the lowest production risk. Only then do we build a pilot.
less chaosideas turned into a priority list
less riskit is clear where a human must approve
a better starta pilot based on real data samples
Next step
Let's start by checking where AI makes sense in your company.
An audit is a good first step if you have ideas, market pressure or a lot of repetitive work, but do not want to implement AI blindly.
Processwhere time disappears today
Datawhat can be used safely
Riskwhere control is needed
Pilotwhat to launch first