Where the operation loses time and value.
Teams work like islands. Sales, operations, finance and support swap context in emails, loose files and meetings. Knowledge gets lost at every handoff, and value goes with it.
Repetitive manual work
Copying data between systems, filling in spreadsheets, reconciling by hand. Hours every week on tasks a system does better.
Long processes
Chained approvals, twelve-step onboardings, a three-day month-end close. The team wears out while the company stands still.
Systems that don't talk
The customer in one system, invoicing in another, history across three inboxes. Every simple answer needs manual reconciliation.
Siloed teams
Each team works with its own data and its own tools. Nobody has the full picture of the operation.
Process first. Technology second.
We start with a diagnostic of the operation. Technology comes after, where it has the most impact, and every technical service is a deliverable of one of these phases.
Process diagnostic and redesign
We understand how the work is done today, then simplify and redesign it before automating.
Automation and AI agents
AI takes over the repetitive work, with clear rules on what it decides alone and what it prepares for a person to decide.
Systems and data integration
Systems start talking to each other and data stops living in loose spreadsheets.
Team adoption and training
Change only counts when the team uses it every day. We train with real cases from your operation.
No reports left in a drawer.
Free AI diagnostic
A meeting with a Scalor specialist to understand the operation and where AI can have the most impact.
Proposal with quantified gains
What changes, in what order and what gains to expect: hours freed, cycle time, errors avoided.
Weekly deliveries
Implementation moves forward every week, with results from the first phase.
Measure and improve
We measure the impact on the operation and keep optimising after delivery.
Diagnostic and proposal at no cost. You only pay when we move to implementation.
Why Scalor.
Process before the tool
We start with a diagnostic of the operation; technology comes after.
Diagnostic and implementation by the same team
No reports left in a drawer: weekly deliveries and results from the first phase.
Measured gains and continuous improvement
We measure the impact and keep optimising after delivery.
Built to scale
We don't automate isolated processes: we design the process and systems architecture that holds up as you grow.
Companies that want to grow without growing their structure at the same pace.
- SMEs with 10 to 200 employees in a growth phase.
- Organisations with siloed teams and too much manual work.
- Founders and CEOs stuck in the operation, with no time for strategy.
- Leadership teams that see the potential of AI but need someone to implement it with method.
- Large companies and groups that need to change operations and processes without depending on long internal cycles.
Use cases by process.
Invoicing and accounts payable
Invoices issued, validated and reconciled without copying data between systems.
Order management
Stock and reorders managed from the data, with supplier orders generated automatically.
Month-end close and reporting
Month-end close and management reporting without hand-built spreadsheets.
Customer service
Requests triaged, instant answers to repeated questions and the history in one place.
Onboarding
From signature to first delivery, with every step tracked and no lost emails.
Sales and CRM
Proposals in hours, not days, and a CRM the team actually uses.
Practical guides to put AI
to work in your operations.
Codex, Claude Code or Copilot: when to do it yourself and when to call someone who has done it before
DIY with LLMs and coding agents, or call in someone who has done it? It isn't about company size: it's the risk of it going wrong and the cost of learning.
AI in e-commerce and marketplaces: nine practical opportunities that already work
Not the future of retail: what an online store, a marketplace seller or a B2B distributor can get working this quarter, ordered by effort and return.
Change management in the age of AI: why the technology is the easy part
AI has cut the gap between a tool existing and everyone using it from years to weeks. Change management is no longer an appendix: it is the project.