AI & Automation
AI wired into the systems your business already runs on.
Not a chatbot bolted on the side. We integrate AI into your ERP, CRM, databases and internal tools, and build agents that carry out real work across them: reading, deciding, updating records and asking a person only when it matters.
What you get
- AI working inside your existing systems, not beside them
- Multi-step work done end to end, with every action logged
- Your data kept private, with a person approving what matters
What's included
What we do, in detail.
Agents that act across your systems
Agents with secure, scoped access to your ERP, CRM, email, file storage and databases. They plan a task, call the right systems in the right order, and finish it: raise the order, update the account, file the document, notify the owner.
AI inside your own software
Classification, extraction, drafting, forecasting and search built directly into your applications and back office, through APIs your team can maintain. Custom systems or platforms like SAP, Salesforce, HubSpot, Microsoft 365 and Google Workspace, through their APIs.
Tool and API layer for AI
We expose your internal systems to AI safely: typed tools, MCP servers and APIs with permissions, rate limits and audit logs, so any model or agent can use them without direct database access.
Knowledge over your private data
Retrieval over contracts, manuals, tickets, wikis and databases, with permissions respected per user and every answer linked to its source. Kept in your cloud account.
Document and data pipelines
Invoices, orders, contracts, emails and scans turned into structured data, validated against business rules and written to the right system. Exceptions routed to a person with the reason attached.
Evaluation, guardrails and governance
Test sets built from your real cases, accuracy measured before and after every change, human approval for high-impact actions, cost ceilings and full traces of what the AI did and why. Designed with the EU AI Act in mind.
How it runs
Five steps, on any system.
Trigger
Any event in any system: an email, a new record, a file, a webhook, a schedule.
Understand
The model reads it with your context: customer history, price lists, policies.
Act
The agent calls your systems through scoped tools: ERP, CRM, database, storage.
Check
Business rules and confidence thresholds decide what goes through and what a person approves.
Learn
Every run is traced and scored, so accuracy and cost are measured, not guessed.
An agent at work
Pick a process. Watch it run.
- Purchase order arrives from a distributor, PDF attached
- Reads the PDF: 14 lines, quantities and the delivery date
- Checks contract prices and stock across two warehouses
- Creates the sales order, one line on back-order
- Discount above 10% on one line: the account owner approves
- Logs the order and sets a follow-up for the back-order
- Sends the order confirmation to the customer
Result: Orders entered without retyping. People handle only the exceptions.
Use cases
Where it makes a difference.
Order to invoice
Orders arriving as PDFs and emails are read, checked against price lists and stock in the ERP, entered, confirmed to the customer and invoiced. People handle only the exceptions.
Sales operations
An agent enriches new leads, updates the CRM after every call and email, drafts follow-ups and flags deals that have gone quiet, for the account owner to approve.
Finance and compliance
Supplier invoices matched to purchase orders and deliveries, anomalies explained in plain language, and a complete audit trail for the accountant.
How we work
What makes it hold.
Integrated, not bolted on
AI is only useful where the work already happens. We connect it to the systems of record through proper APIs and permissions, so its output lands in your ERP or CRM instead of in a chat window someone has to copy from.
Measured before it ships
Every AI feature starts with a test set taken from your real cases. We measure accuracy, cost and speed before launch and after every change, so improvements are proven rather than assumed.
A person approves what matters
Agents act on their own where the risk is low and ask for approval where it is not: payments, contracts, anything a customer sees. You decide where that line sits, and every action is logged.
Your data, your cloud, any model
Data stays in your own cloud account in the EU, with private or self-hosted models where needed. We are not tied to one AI provider and switch when a better or cheaper model appears, with a monthly ceiling on model costs.
Tools & methods
- AI agents
- Tool calling
- MCP
- RAG
- Evaluations
- OpenAI
- Anthropic
- AWS Bedrock
- Private models
- n8n
- Python
- TypeScript
Questions
Asked before, answered here.
Where do we start?
With an Automation Scan. It shows which processes are worth automating and which one to start with.
Will AI make mistakes?
Sometimes, which is why every system we build has rules it cannot break and sends unclear cases to a person. We design for that from day one.
Which AI models do you use?
The one that fits the task and the budget. We are not tied to a single provider and can switch when a better or cheaper model appears.
Related
Layers that work with this one.
Tell us what you are
trying to build.
A paragraph is enough to start. We will tell you what we would build, what it would take, and whether we are the right people for it.
Start a project