Documents & data
Turn emails, PDFs, spreadsheets, quotations, invoices and forms into structured business data.
REAL WORK. REAL POSSIBILITIES.
What could AI remove from your workday?
Less repetitive work. Better information. More room to move.
Repetitive office work
Automate data entry, reports, approvals, notifications and recurring administration.
Customer enquiries
Classify incoming enquiries, retrieve useful information and prepare responses.
Sales & quotations
Extract requirements, find historical pricing, prepare quotes and route approvals.
Operations
Connect tasks, projects, inventory, procurement and service delivery.
Management intelligence
Ask which projects are delayed, deliveries are at risk, or customers haven’t paid.
How we put AI to work.
Every AI feature we build starts with a clearly defined task, an approved set of data sources and a decision about where a person stays in the loop. That is what makes it dependable in day-to-day operations rather than a demo.
We combine language models with traditional engineering: databases, APIs, validation rules, access control and logging. The model reads, classifies, extracts and drafts. Your systems store, route and enforce.
The toolkit is chosen per workflow: LLM APIs such as Anthropic Claude and Google Gemini, workflow engines such as n8n, the WhatsApp Business API, and custom code in Laravel, Node.js and Python.
HOW IT HAPPENS
From idea to a working assistant.
Small scope first. Real data early. Controls before launch.
- 01
Pick one workflow
We choose a task with a clear input, a predictable handoff and a useful outcome, such as enquiry triage or invoice extraction.
- 02
Connect the data
We give the model only the sources it needs: documents, your ERP or CRM, price lists, policies, with access rules in place.
- 03
Build and test with your team
Your people try it on real cases. We tune prompts, rules and edge cases until the output is reliable.
- 04
Deploy with controls
Approvals, audit trails and fallbacks go live with the feature, so you stay in charge of every important decision.
HONEST SCOPING
Where AI fits. And where it doesn’t.
Knowing the difference saves months.
A strong fit
Repetitive, document-heavy or rule-based work: reading emails and PDFs, classifying requests, drafting replies and quotations, summarising reports.
Needs care
Decisions with financial, legal or safety consequences. AI prepares the work; a named person reviews and approves.
Not the right tool
When a plain integration, a report or a better form solves the problem, we build that instead.
QUESTIONS
Questions we hear first.
Do we need to replace our existing software?
No. Most AI features sit beside the systems you already run and exchange data with them through APIs, exports or email. We integrate first and replace only when there is a clear reason.
Which AI models do you use?
We select the model per task. Commercial APIs such as Anthropic Claude or Google Gemini cover most business work; for sensitive data or high volumes we can evaluate self-hosted options.
How is our data handled?
Data stays in your systems. The model receives only what a task needs, and we document which sources are used, who can access the feature and how outputs are logged.
What does a first project look like?
Typically one workflow, a few weeks from scoping to a working feature your team uses daily, followed by review and the next improvement.
AUTOMATION IDEAS
Ideas by department.
Practical starting points for sales, procurement, HR, finance and operations teams.
AI for Sales
Practical automation ideas for sales teams, built around the work they already do.
Explore ideasAI for Procurement
Practical automation ideas for procurement teams, built around the work they already do.
Explore ideasAI for HR
Practical automation ideas for HR teams, built around the work they already do.
Explore ideasSTART WITH ONE WORKFLOW
Let’s find your first AI workflow.
Tell us about the task that eats the most time. We’ll show you what a practical AI implementation could look like.