Sarja

AI Automation & Integration

Take the repetitive work off your team's desk.

We connect AI to your inboxes, documents and business systems, so requests are read, checked and prepared automatically — and people only step in where their judgement is needed.

Talk to SarjaWhat's included

Why organisations commission it

  • Less time spent re-keying, sorting and searching
  • AI output lands in the systems people already use
  • People stay accountable for the decisions that count

A chat window doesn't change how work gets done.

Most teams have tried an AI chatbot. Few have seen it take real work off their plate, because the work still lives in the inbox, the CRM and the shared drive — not in a separate tab.

We put AI where the work already happens. It reads the incoming request, pulls the right context from your systems, prepares the output and writes it back, with a person approving anything that matters.

What we deliver.

Connect AI to the workflows and software your team already uses.

  • Document processing and data extraction
  • Email and request triage
  • Internal knowledge search and retrieval
  • Research and reporting automation
  • AI assistants inside existing tools
  • Approval queues for human review
  • Connectors to internal systems and APIs
  • Scheduled and event-driven workflows

What an automated workflow actually looks like.

An example from accounts payable. The same pattern works for enquiries, applications, claims, onboarding and reporting.

  1. 1Trigger

    A supplier invoice arrives in the accounts inbox.

  2. 2AI

    Supplier, amounts and line items are read from the PDF.

  3. 3AI

    Everything is checked against the purchase order in your finance system.

  4. 4AI

    Mismatches are flagged; clean invoices go to an approval queue.

  5. 5Person

    Your finance lead approves in one step.

  6. 6System

    The invoice is posted to your accounting software, with a full record.

Illustrative example.

How it works.

  1. Step 1

    Map the workflow

    We follow the process with the people who run it, exceptions included.

  2. Step 2

    Prove one path

    A single, well-scoped workflow is piloted on your real data.

  3. Step 3

    Connect and harden

    Production integrations, permissions, error handling and logging.

  4. Step 4

    Extend

    Further workflows are added on the same foundation.

Usually delivered alongside

Let's find the first AI system worth building.

Tell us about the workflow, system or data involved. We'll come back with a straight view of what's possible, what it would take, and where to start.

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