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GoBD-compliant §203 StGB-compliant Q2

Inventory Agent

Automate asset inventory - from target/actual comparison to inventory report.

Generates inventory lists from fixed asset accounting, reconciles target and actual balances.

Analyse your process
Airbus Volkswagen Shell Renault Evonik Vattenfall Philips KPMG

Rule-based target/actual reconciliation, impairment and disposal stay with humans

The agent automates the inventory reconciliation of target against actual via deterministic matching logic, flags shortages and double counts, and hands impairment and disposal decisions to the responsible specialist.

Outcome: Inventory cycle reduced from 3 weeks to 5 working days, asset-capture completeness above 98 percent, and audit-proof reconciliation record.

75% Rules Engine
0% AI Agent
25% Human

The 8 decision steps represent the inventory logic that used to live in manually maintained spreadsheets:

One in three register entries is a ghost asset

Between 10 and 30 percent of all entries in asset registers are so-called ghost assets - items that exist only on paper (source: CPCON Group, Fixed Asset Register Guide 2026). The annual physical inventory is meant to prevent exactly that. In practice, it often fails at the process level: manual counting across sites, spreadsheet-based reconciliation, weeks of follow-up. The Inventory Agent solves this problem by taking over the rule-based portion of the inventory entirely and stopping only where human judgement is required.

One in three assets on the register exists only on paper

Ghost assets accumulate gradually. A printer is replaced, but the disposal is never posted. A machine moves to another site without a master data update. After five years without a physical check, the asset register has drifted far enough from reality that the inventory becomes a clean-up project. The consequences are measurable: inflated insurance premiums calculated on overstated book values, unnecessary depreciation on assets long since scrapped, and in the worst case a qualified audit opinion because the statutory auditor cannot accept the gap between register and reality.

Manual inventory does not scale across locations

A mid-sized machinery manufacturer with four production sites and 8,000 assets knows the pattern: three weeks before the count date, coordination begins. Inventory teams are assigned, count sheets printed, scanners distributed. Each site counts at its own pace. Results come back by email - as spreadsheets in different formats. Central consolidation takes another two weeks. Shortfalls surface late, recounts delay the close. The result: the inventory consumes four to six weeks of labour, and doubts about completeness persist.

The agent separates counting from valuing

The Decision Layer divides the asset inventory into two categories of decisions. Rule-based steps - generating the inventory list from the ERP, capturing the actual count, performing the target/actual reconciliation, identifying shortfalls, preparing correction postings - run automatically. The agent matches book balances against physical counts and produces difference lists by site, cost centre and asset class.

Two decisions remain with the human: Has an asset lost value? Should it be disposed of? These valuation questions require inspection and judgement. The agent supplies the decision basis - age, remaining useful life, condition from the last capture - but the sign-off rests with the specialist department. The process stays audit-compliant without tying up human capacity on counting work.

RFID-based capture lifts accuracy above 95 percent

Manual inventory with barcode scanners typically achieves accuracy rates of 85 to 95 percent. RFID-based capture improves accuracy further and significantly shortens capture time. The Inventory Agent supports both technologies: where RFID tags are present, it captures the actual balance of a room in seconds rather than hours. Where only barcodes are available, it orchestrates the manual capture with site-specific lists and real-time progress tracking. The RFID infrastructure investment pays back in practice within a few years - not only through faster inventory, but also through better asset location tracking in daily operations.

Correction postings are ready on inventory day

The real goal of the inventory is not the count but a clean asset register. The Inventory Agent prepares correction postings as soon as a discrepancy is confirmed: disposal entries for missing assets, unscheduled depreciation for impaired assets, location corrections for relocated items. At the end stands an inventory report documenting the entire process - from the target list through the actual capture to the sign-off on every single correction. The statutory auditor receives not just a result but the complete decision trail. That accelerates the financial audit and reduces follow-up queries to the essentials.

Micro-Decision Table

Who decides in this agent?

8 decision steps, split by decider

75%(6/8)
Rules Engine
deterministic
0%(0/8)
AI Agent
model-based with confidence
25%(2/8)
Human
explicitly assigned
Human
Rules Engine
AI Agent
Each row is a decision. Expand to see the decision record and whether it can be challenged.
Generate inventory list Which assets must be inventoried? Rules Engine

Target balance from fixed asset accounting, complete list

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Capture actual balance Was the asset physically found? Rules Engine

Data capture via barcode scan or manual entry

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Perform target/actual reconciliation Does the actual balance match the target balance? Rules Engine

Numerical comparison, deterministic difference calculation

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Identify shortfalls Which assets are missing or surplus? Rules Engine

Difference list from target/actual reconciliation

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Assess impairment Is there an unscheduled impairment and how much? Human Auditor

Commercial judgement - physical condition, market development, technical obsolescence

Decision Record

Decider ID and role
Decision rationale
Timestamp and context

Challengeable: Yes - via manager, works council, or formal objection process.

Challengeable by: Auditor

Disposal decision Should the asset be disposed of and written off? Human Auditor

Commercial judgement - repairability, continued use, disposal

Decision Record

Decider ID and role
Decision rationale
Timestamp and context

Challengeable: Yes - via manager, works council, or formal objection process.

Challengeable by: Auditor

Prepare correction postings Which postings are required for identified differences? Rules Engine Auditor

Posting logic: unscheduled depreciation, disposal, write-up

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Challengeable by: Auditor

Create inventory report Is the report complete and correctly annotated? Rules Engine Auditor

Data rule-based (R), annotation and summary by LLM (A)

Decision Record

Rule ID and version number
Input data that triggered the rule
Calculation result and applied formula

Challengeable: Yes - rule application verifiable. Objection possible for incorrect data or wrong rule version.

Challengeable by: Auditor

Decision Record and Right to Challenge

Every decision this agent makes or prepares is documented in a complete decision record. Affected parties (employees, suppliers, auditors) can review, understand, and challenge every individual decision.

Which rule in which version was applied?
What data was the decision based on?
Who (human, rules engine, or AI) decided - and why?
How can the affected person file an objection?
How the Decision Layer enforces this architecturally →

Does this agent fit your process?

We analyse your specific finance process and show how this agent fits into your system landscape. 30 minutes, no preparation needed.

Analyse your process

Governance Notes

GoBD-compliant §203 StGB-compliant

Mixed decision distribution (2H / 5R / 1A). Human decisions for impairment and disposal - both require commercial judgement and are balance-sheet-relevant. HGB Paragraph 240 (inventory obligation), HGB Paragraph 253 Abs. 3 (unscheduled depreciation) as direct legal bases.

GoBD-compliant: inventory lists, actual captures and differences are archived as immutable documents. The inventory report is part of the annual statement documentation. During tax audits, proper inventory is a regular audit point. Paragraph 203 StGB relevant: fixed assets can reveal trade secrets.

§203 StGB-relevant data is encrypted end-to-end and never passed to AI models in plain text.

Process Documentation Contribution

The inventory documentation includes: target list (reporting date, source), actual capture (method, person, date), difference list, valuation decisions (impairment, disposal) with clerk's rationale, prepared and posted corrections, inventory report with summary. The complete documentation meets the requirements for a proper inventory per HGB Paragraph 240.

Assessment

Agent Readiness 71-78%
Governance Complexity 24-31%
Economic Impact 54-61%
Lighthouse Effect 14-21%
Implementation Complexity 26-33%
Transaction Volume Yearly

Prerequisites

  • Fixed asset accounting with complete master data and book values
  • Inventory capture system (barcode/RFID scanner or manual entry)
  • Access to physical locations of assets
  • Depreciation Agent for current accumulated depreciation

Infrastructure Contribution

The Inventory Agent uses the master data from the Asset Capitalisation Agent and accumulated depreciation from the Depreciation Agent. The target/actual reconciliation pattern is reused as a template for all reconciliation processes (bank reconciliation, intercompany matching). The valuation escalation (agent prepares, human decides) is the reference pattern for all Finance agents with discretionary decisions. Builds Decision Logging and Audit Trail used by the Decision Layer for traceability and challengeability of every decision.

What this assessment contains: 9 slides for your leadership team

Personalised with your numbers. Generated in 2 minutes directly in your browser. No upload, no login.

  1. 1

    Title slide - Process name, decision points, automation potential

  2. 2

    Executive summary - FTE freed, cost per transaction before/after, break-even date, cost of waiting

  3. 3

    Current state - Transaction volume, error costs, growth scenario with FTE comparison

  4. 4

    Solution architecture - Human - rules engine - AI agent with specific decision points

  5. 5

    Governance - EU AI Act, GoBD/statutory, audit trail - with traffic light status

  6. 6

    Risk analysis - 5 risks with likelihood, impact and mitigation

  7. 7

    Roadmap - 3-phase plan with concrete calendar dates and Go/No-Go

  8. 8

    Business case - 3-scenario comparison (do nothing/hire/automate) plus 3×3 sensitivity matrix

  9. 9

    Discussion proposal - Concrete next steps with timeline and responsibilities

Includes: 3-scenario comparison

Do nothing vs. new hire vs. automation - with your salary level, your error rate and your growth plan. The one slide your CFO wants to see first.

Show calculation methodology

Hourly rate: Annual salary (your input) × 1.3 employer burden ÷ 1,720 annual work hours

Savings: Transactions × 12 × automation rate × minutes/transaction × hourly rate × economic factor

Quality ROI: Error reduction × transactions × 12 × EUR 260/error (APQC Open Standards Benchmarking)

FTE: Saved hours ÷ 1,720 annual work hours

Break-Even: Benchmark investment ÷ monthly combined savings (efficiency + quality)

New hire: Annual salary × 1.3 + EUR 12,000 recruiting per FTE

All data stays in your browser. Nothing is transmitted to any server.

Inventory Agent

Initial assessment for your leadership team

A thorough initial assessment in 2 minutes - with your numbers, your risk profile and industry benchmarks. No vendor logo, no sales pitch.

30K120K
1%15%

All data stays in your browser. Nothing is transmitted.

Frequently Asked Questions

Does the agent also work with RFID-based inventory?

Yes. The agent accepts actual data from any capture system - barcode, RFID, manual entry. The interface is standardised and independent of the capture method.

How are missing assets handled?

The agent identifies missing assets automatically and escalates for a disposal decision. The clerk decides whether to search further, dispose of or correct the inventory list. Every decision is documented.

Can the inventory also be performed during the year (cut-off inventory, perpetual inventory)?

Yes. The agent supports cut-off inventory, shifted inventory and perpetual inventory. For perpetual inventory, sub-areas are checked on a rolling basis - the agent ensures every asset is captured at least once per year.

What Happens Next?

1

30 minutes

Initial call

We analyse your process and identify the optimal starting point.

2

1 week

Discover

Mapping your decision logic. Rule sets documented, Decision Layer designed.

3

3-4 weeks

Build

Production agent in your infrastructure. Governance, audit trail, cert-ready from day 1.

4

12-18 months

Self-sufficient

Full access to source code, prompts and rule versions. No vendor lock-in.

Implement This Agent?

We assess your finance process landscape and show how this agent fits your infrastructure.