AI Consulting Services
Assess where AI fits before you invest in the project. We select use cases, define the architecture, and plan the integration.
Building an AI-Ready Data System for a Multi-Brand Group
Unifying data from 50+ webshops into one warehouse and configuring a custom AI system that answers ad-hoc business questions in plain language.
Key results:
Data from 50+ brands made structured and AI-readable
AI access layer with business definitions, used by Claude
Ad-hoc questions answered without manual reporting
Context and Challenge
Our client owns more than 50 brands, and each one sells through its own webshop. An off-the-shelf reporting tool worked for the company at first. Then, the questions got more specific, and the solution stopped keeping up:
- Webshop data came in different formats, which blocked shared reporting across the client’s brands
- Business analytics was limited to preset views, with no room for custom queries
- Data was stored on the third-party vendor’s side instead of the company’s own infrastructure
To fix those limitations, our client decided to move to a custom AI analytics solution. Before that could work, they needed to prepare the data and the mechanisms around it. To address this, the client brought in Forbytes.
Client’s Objectives
The AI readiness project started with data preparation, and the goals followed from there:
- Prepare the data from 50+ webshops for AI analytics
- Configure AI to work with that data and report on it
- Support custom queries and custom output formats
- Enable brand-to-brand comparison for data-driven decisions
- Remove analytical blind spots and the limits of preset reports
Start With the AI Readiness Session
Bring your questions about data, systems, and access rules, and leave with a clear first step.
Project Overview
AI readiness for the client involves five steps:
1. Data Source Selection
The client’s numbers don’t live in one place. Marketing and financial data sit in Google Analytics; ad spend data is stored in Google Ads. The rest resides in internal tools and ERPs, with each of the 50+ brands running its own webshop. AI can only answer based on what it can see, so we started by sitting down with the client to determine which data sources were essential.
2. Building a Trusted Data Layer
Our team used spec-driven development to build a warehouse and centralize data from 50+ webshops in one solution. We cleaned and standardised the data so it means the same thing across all brands and can be used correctly by AI. One brand’s order number and another’s order ID are now the same identifier. Each table and column carries a business definition. Fields are split or merged where needed to allow AI to interpret them properly.
Besides, we prepared data marts for specific teams and subjects, so AI questions hit a narrower set of data. New sources are onboarded using a standard instruction that AI uses to build integrations.
3. AI Configuration and Access Layer
Forbytes configured Claude to work with data through a controlled access layer built on APIs. Claude never reads the database itself. It writes the request, and our tool turns it into a query and returns the output.
When someone asks for revenue in the third quarter of 2025, Claude looks the term up in the business dictionary we prepared, asks for the sales order table, and works from what comes back. Conversions, order value, transactions, cart abandonment, bounce rate, delays, and many other business metrics are covered the same way. On top of that, we’re building reports and custom KPIs for each brand.
4. Operational Controls
We also set limits. AI control rules define what it can do with company data. Our engineers built the rules and instruments, so AI works with the data according to the group’s business definitions. For day-to-day operation, we added audit trails, monitoring, and rollback. The team knows what happened and can safely undo a change.
5. Security and Access Control
Access is enforced per user using application authentication and authorization protocols and role-level-security approach on data layer. AI only sees what the requesting user is allowed to see. For example, a finance user only sees finance data unless additional access is allowed. Sensitive data is masked, and high-impact actions don’t run until someone approves them.
Qualitative Results
The project is in active development, with AI readiness work underway across the client’s data sources. The AI readiness foundation is designed to deliver the following outcomes:
- One unified, AI-readable data layer across 50+ independent brands
- Faster access to answers that used to require manual report creation
- Business questions answered in plain language, without waiting for a report
- Full ownership of company data, hosted on the client’s own infrastructure
- AI readiness layer built around how the client operates, not a generic template
- Access to performance insights and revenue opportunities that preset reports used to hide
Is Your Business Data Ready for AI Implementation?
Fill in the form to tell us about your current data setup and AI plans. We’ll follow up to discuss a tailored AI readiness assessment session.
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Forbytes created an app that allowed users to quickly measure themselves to be fitted for custom shirts. As a result, we could increase our speed, quality, and shirt output per week. Forbytes was dedicated to delivering a solution that accurately addressed our needs.
Forbytes’ engineers and team leads worked as part of our RnD group and were directly managed by our company directors. They were both proactive and adaptable, qualities that perfectly match our needs in our fast-growing and constantly evolving environment.
Forbytes has a strong process-oriented way of leading the company, with good respect for themselves and their managers. They made a choice not to become too big but build slowly on more qualified people, which is paying off.
Niklas Hammar
COO & Business
Development at Offerta.se
Our e-commerce site saw online inquiries and orders rise after working with Forbytes. The team used top-notch expertise to inform their suggestions and improvements. Constant communication, quick responses, and prompt delivery made for a smooth and enjoyable collaboration.
The Forbytes team was very professional and demonstrated a great understanding of the business aspects. All tasks were completed above expectations. Their experts were always available, and we never needed to wait for a response or a suggested solution.
