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AX

AI Work Automation (AX)

We apply AI to rule-heavy work in accounting, finance, and HR — not as a demo, but built into the systems you already run.

Why It Takes a Team That Knows the Work

Automating accounting and HR work depends less on model performance than on how precisely the underlying rules are understood.

Designed by a team that knows the work

AX succeeds or fails on domain understanding, not model choice. Without knowing your chart of accounts, closing sequence, and payroll exception rules, the automation scope itself gets set wrong. Nora has built ERP and finance systems firsthand.

Built into the systems you already use

AI that only works in a separate demo screen doesn't change how work actually gets done. We build it to run inside the ERP, groupware, and accounting systems your team already opens every day.

We build and operate our own AI

Nora develops and operates 'discov', a sales-meeting AI, along with AI-matched golf course booking. We design from problems we've hit while operating AI, not from slide decks.

What We Cover

We focus on the areas where domain expertise matters — closing, cash, HR, and internal documentation.

Accounting & Closing Automation

We extract transaction data from supporting documents to draft journal entries and suggest accounts. Anything that fails the rules is never posted automatically — it goes to a reviewer queue so ledger integrity holds.

Finance & Cash Reporting

We build reporting that answers plain-language questions from executives by aggregating ledger data with its basis attached, traceable down to the source journal entry.

HR & Payroll Automation

We automate application screening support, anomaly detection in attendance and payroll, and responses to internal HR policy questions. Areas that require human judgment, such as evaluation and hiring decisions, are deliberately left out of scope.

Internal Knowledge AI

We structure policies, manuals, and past contracts into a searchable form, so the assistant answers while citing the source document. Existing access rights by team and role are applied as-is.

Repetitive Workflow Automation

We consolidate work that bounces between email, spreadsheets, and approvals into a single automated flow — settlement reconciliation, data cleanup, and first-draft reporting.

AI Agents & System Integration

We build the integration layer between your core systems and AI, designing the data flow even in legacy environments with no public API.

Our Process

We diagnose what is worth automating first, validate it with a PoC, then connect it to your existing systems.

  1. 01

    Work Diagnosis

    We map how work actually flows across teams, its volume, and where recurring errors occur. Ruling out work that is a poor fit for automation is just as much the goal of this step.

  2. 02

    Use-Case Selection & Impact Estimate

    We prioritize by frequency, clarity of rules, and verifiability, then estimate the expected impact.

  3. 03

    PoC

    We validate a single workflow against your real data, agreeing on accuracy targets and failure criteria before we start.

  4. 04

    Process Redesign & Rule Definition

    We split what gets handled automatically from what a person confirms, and define the exception rules. Skip this and your teams simply will not trust the output.

  5. 05

    Integration & Build

    We integrate with your existing ERP and groupware so it runs inside the screens and flows your staff already use.

  6. 06

    Operations & Accuracy Tuning

    We collect mishandled cases and refine the rules and prompts. With AX, accuracy improves through operation — not at go-live.

How We Handle Your Data

Because this involves accounting and HR data, deployment location and access rights are settled before any build begins.

  • Deployment inside your own cloud account or on-premises network is offered as the default option
  • Engagements are structured so your input data is not used to train external models
  • Access scope follows the permission model of your existing ERP and HR systems
  • Processing history for accounting and HR data is recorded so it can be reviewed after the fact

AI We Operate Ourselves

Nora develops and operates 'discov', a sales-meeting AI that turns a recorded customer interview into meeting notes, requirements, and proposals. It came out of automating the document work we repeated across our own SI projects — and we apply the same standard when scoping AX work for clients.

Explore discov →

Frequently Asked Questions

How is AX different from traditional RPA?

RPA repeats a fixed screen and sequence, so it breaks the moment a form changes or an exception appears. AX interprets documents and context to handle work that requires judgment — and the core of the project is defining those judgment criteria and exception rules together with the people who do the work.

Is it safe to connect accounting and HR data to AI?

Deployment inside your own cloud account or on-premises network is offered as the default option, and engagements are structured so your input data is not used to train external models. Access rights follow the permission model of your existing ERP and HR systems.

Which work should we start with?

Start where the work is frequent, the rules are clear, and a person can verify the result — document reconciliation, journal entry drafting, and internal policy questions are typical. Areas requiring human judgment, such as evaluation and hiring, are left out of the early scope.

Can it integrate with our existing ERP and groupware?

Yes. Nora has built and operated ERP and finance systems firsthand, and designs the data flow and integration approach even in legacy environments with no public API.

How are timeline and cost estimated?

We scope per use case after the work diagnosis. A PoC targeting a single workflow typically runs 4 to 8 weeks, with scope and duration adjusted based on what the diagnosis finds.