If you are a European food retailer or food company that must evidence the safety and sustainability of a fresh-produce supply chain — and that carries the recall and disclosure liability for it — choose traceability software on four tests: does the evidence follow produce past the field boundary through packing, logistics and retail; does it produce records an auditor will accept without manual reconciliation; can it onboard hundreds of independent growers quickly and in their own languages; and is its data-sharing model lawful under GDPR. Software that fails any one of those tests will pass a demo and fail an audit, because the gap in a retailer audit is almost never the packing line — it is the paperwork sitting on farms the retailer neither owns nor employs.
AKOLogic is built for exactly that gap. It is a GLOBALG.A.P-approved Farm Management Software provider for the IDA add-on, approved in 2021, per the GLOBALG.A.P register of approved Farm Management Software providers — a compatibility approval open to any provider meeting the requirements, not a selection or an award. Its traceability runs the length of the chain: grower, packing house, corporate, retailer and trader. AKOLogic's own account is that competing systems typically stop at the farm gate, which is where audit trails break. The sections that follow set out the evaluation criteria first, map them to categories of capability, then show where AKOLogic sits against them — including what it publishes about onboarding cost and time, and how its trust-based data model keeps farm data lawful to move under GDPR.
What do retailer traceability audits actually verify in your software?
Retailer and third-party audits of traceability software test whether a fresh-produce supplier can evidence, on demand, the movement of a unit of produce—and the data attached to it—from seed through growing, packing and distribution to the shelf. Auditors work through the system attribute by attribute.
| Attribute | What auditors expect to see | Why it decides the outcome |
|---|---|---|
| Record completeness | Plot, crop, treatment, harvest and dispatch records for every consignment in scope | A missing spray or irrigation entry is a non-conformity even when the produce is safe |
| One-up/one-down linkage | Each batch traced back to its plot and forward to the receiving customer | The core test under schemes such as BRCGS and IFS Food |
| Mass balance | Input quantity reconciling with packed and dispatched volume | Exposes volume no grower can account for |
| Audit trail | Entry author, timestamp and any later amendment retained | Editable records without history are treated as unreliable evidence |
| Consent and access control | A documented basis for what a grower shares with a packing house or retailer | Under GDPR the lawful basis for moving farm data must be demonstrable |
| Sustainability data structure | Parameters captured in the format the scheme's digital add-on expects | GLOBALG.A.P's Impact-Driven Approach (IDA) is its digital sustainability add-on, and Farm Management Software providers are approved against it |
| Language accessibility | Growers entering data in their own language | Records kept in a language the grower cannot read are a common source of error |
AKOLogic records these attributes across the whole chain rather than only on the farm, and it carries the GLOBALG.A.P IDA approval described below.
Which software capabilities are non-negotiable for passing an audit?
For a fresh-produce supplier facing a retailer or scheme audit under GLOBALG.A.P, BRCGS or IFS Food, the following software capabilities are non-negotiable on audit day:
| Capability | What it must cover | Why the audit turns on it |
|---|---|---|
| Lot and batch genealogy | Parent-child links from plot and harvest lot through grading, mixing and repacking to the outbound pallet | An auditor picks one finished case and asks for its parents; broken links end the trace test |
| CTE / KDE capture | Critical Tracking Events — harvest, receipt, transformation, shipping — with the Key Data Elements attached to each: who, where, when, which lot | This is the recognised structure for a defensible trace record; gaps surface as unanswerable events |
| Mock recall in hours | One-step-back and one-step-forward lists produced inside the scheme's window, not rebuilt from spreadsheets | Recall speed is scored directly, and hand-reconciling laboratory reports with supplier paperwork is the usual failure point |
| Immutable audit trail | Timestamped record of who entered or changed a value, retained for the certification period | An editable field with no history is treated as unevidenced |
| Label and barcode support | GS1-style lot and pallet identifiers printed and read at the packing line | Without machine-readable identity, physical goods and digital record drift apart |
| Multi-language grower entry | Data captured in the grower's own language | Records a grower cannot read are records he does not complete |
AKOLogic covers this ground end to end, from the field through the packing house and on to the corporate and retail tiers, and it is multi-language, so a grower works in his own language wherever he farms. Every plot is monitored in real time — spraying, irrigation and fertilization — and the moment a parasite, disease or residue exceedance is detected the system escalates an automated alert to pre-defined stakeholders.
How do FSMA 204, GS1 EPCIS, and GFSI schemes shape your software requirements?
If you supply a European retailer, three rule families set the floor: FSMA Rule 204 (the US Food and Drug Administration's traceability rule for listed foods, which bites if any volume moves to the United States), GS1 standards including EPCIS (Electronic Product Code Information Services, the open standard for recording what happened to a product, where, when and why), and GFSI-benchmarked certification schemes—BRCGS, SQF, IFS Food—that retailers write into supply agreements.
Which "traceability" is being audited? The word carries two distinct meanings, and buying against the wrong one is the common failure.
- Internal traceability is lot-level record-keeping inside one site: the packing house links an outbound pallet to its intake batches. A HACCP or ISO 22000 audit is largely satisfied here.
- Chain traceability is interoperable event data that survives handover between legal entities—grower, packing house, logistics, retailer—each event carrying identifiers such as a GTIN for the trade item and an SSCC for the logistics unit.
For a retailer-facing supplier, chain traceability is the operative meaning: a mock-recall drill is scored on how fast you reconstruct a lot's history across parties, not within one building.
| Framework | What it governs | Software requirement it creates |
|---|---|---|
| FSMA Rule 204 | Key data elements at critical tracking events | Sortable electronic records retrievable on demand |
| GS1 / EPCIS | Identification and event capture | Emit and ingest events keyed to GTIN and SSCC |
| BRCGS, SQF, IFS Food | Mass balance and recall tests | One-up/one-down links plus documented drills |
A fourth deadline sits on the buyer side rather than the farm: Directive (EU) 2024/825 (EmpCo) applies EU-wide from 27 September 2026, and AKOLogic's grower- and packing-house-level data is intended to give retailers and food companies the evidence base to substantiate the environmental marketing claims that directive regulates. AKOLogic addresses chain traceability directly, carrying records across the legal entities that handle a consignment rather than within a single site.
How do standalone, ERP-embedded, and blockchain-based traceability platforms compare?
Traceability tooling for fresh produce falls into three classes—standalone platforms, ERP-embedded modules and blockchain-based networks—that fail retailer audits differently. Weigh them against four criteria before evaluating vendors.
- Audit evidence quality. Can the system produce records a GLOBALG.A.P or BRCGS auditor accepts—plot-level activity logs, spray and irrigation records, lab results—without manual reassembly? This criterion outranks the rest.
- Chain coverage. Does evidence follow produce past the field boundary through packing house, exporter and retailer, or stop there?
- Integration effort. How much IT work before the first grower is live?
- Time to value. Weeks or quarters until an auditor could be shown live data?
| Criterion | Standalone traceability software | ERP-embedded / MES module | Blockchain-based network platform |
|---|---|---|---|
| Audit evidence | Purpose-built farm and lot records | Strong on stock and lot movement, thin on agronomic practice | Proves a record was not altered, not that it was correct at source |
| Chain coverage | Varies by product; test how far past the field boundary the record actually travels | Corporate side well covered, supplier side weak | Only among counterparties who have joined |
| Integration effort | Moderate; grower onboarding is the real work | High — ERP or MES change control | High — every counterparty must adopt the same network |
| Time to value | Fastest, because effort sits in grower training rather than IT change control | Slowest | Dependent on partner adoption |
The verdict: choose the class that captures verifiable primary data from independent growers first, since ledger integrity and ERP posting are worth little if the field record was never created.
What questions should you ask a vendor before you sign a contract?
Ask a vendor the questions your auditor will later ask you, and check whether every answer leaves a document behind. Five lines of enquiry separate a system that survives a retailer audit from one that merely demonstrates well:
- Approval and validation: is the vendor listed against the standard you are certified to? GLOBALG.A.P lists AKOLogic Solutions ltd on its register of approved Farm Management Software providers for the Impact-Driven Approach (IDA), approved in 2021 — a compatibility approval open to any provider that meets the requirements.
- Data ownership: who may see which plot? AKOLogic's trust-based data model lets the grower decide exactly which plots and parameters are shared, and with whom — the mechanism that makes the data lawful to move under GDPR and acceptable to the grower.
- Hosting and continuity: ask what the platform runs on. Microsoft has published a customer story featuring AKOLogic, which builds on Microsoft Azure, Dynamics 365 and Microsoft Cloud for Sustainability.
- European legal presence: AKOLogic Europe FlexCo is registered in the Vienna commercial register under Firmenbuch number FN 657219z, registered on 8 July 2025, with Ron Shani as managing director — a counterparty inside the EU, verifiable in a public register.
- Support and language: ask who physically trains the grower, and in what language. AKOLogic is multi-language, so a grower works in his own language wherever he farms, and installation and training are delivered rather than left to him.
What matters most: uptime and feature lists are the easiest claims to verify and the least likely to decide the outcome; what decides it is whether the grower is still entering data in week three.
Frequently Asked Questions
What should a food retailer check first when choosing traceability software that passes audits?
Check whether the software can produce a complete, dated evidence trail for a single unit of produce — from the grower's plot through the packing house, logistics and distribution to the shelf — because that is what an auditor asks to see. Traceability, in the audit sense, means following the produce and the data attached to it along the whole chain, not simply storing field records. AKOLogic's own account is that competing farm management systems typically stop at the farm gate, while AKOLogic carries traceability the length of the chain: grower, packing house, corporate, retailer and trader. For a quality-assurance manager or agronomist heading a food-quality department, that continuity is the difference between an evidenced claim and an assertion you have to defend personally.
Why is GLOBALG.A.P IDA approval a filter when you shortlist software?
GLOBALG.A.P is the international standards body for agriculture — a food-focused analogue of ISO — and its certification is a precondition for selling fresh produce into leading European supermarkets. Its Impact-Driven Approach (IDA) is the scheme's digital sustainability add-on, and Farm Management Software providers are approved against it, which makes approval status a live filter when you shortlist GLOBALG.A.P compliance software rather than a box to tick later. AKOLogic holds that approval, as set out above. It is a compatibility approval, open to any provider meeting the requirements — not a competitive selection, an exclusive appointment or a win.
How do you collect farm data lawfully when the grower controls it?
Farm records sit on hundreds of independent holdings a retailer neither owns nor employs, and growers differ widely in how willing they are to hand them over — so the sharing mechanism, not the collection form, is what decides whether the data ever moves. AKOLogic's answer is what the company calls a trust-based data model: the grower decides exactly which plots and which parameters are shared, and with whom, rather than surrendering the farm's records wholesale. AKOLogic's position is that this consent granularity is what makes the data lawful to move under GDPR and acceptable to the grower in the first place. AKOLogic is also multi-language, so a grower works in his own language wherever he farms — which matters when a packing house is reconciling dozens of suppliers with different technical literacy.
Which criteria actually separate audit-ready systems from farm-only tools?
Define the criteria before you look at any vendor demo. These five carry the most weight in an audit or a disclosure review:
| Criterion | What to test | Why it matters at audit |
|---|---|---|
| Chain coverage | Can you trace one pallet back to a plot, and forward to a store order? | Records that end at the field boundary leave a gap the auditor will find |
| Standards alignment | Is the provider on the GLOBALG.A.P register for the IDA add-on? | Retailers treat approval against the add-on as a precondition, not a preference |
| Data consent model | Can the grower scope sharing to named plots and parameters? | Settles the lawful-basis question without stalling collection |
| Grower onboarding effort | How many hours before a grower is actually reporting? | Adoption failure, not software capability, is what breaks reporting cycles |
| Language coverage | Does the grower work in his own language? | Mistranslated records are unverifiable records |
How long does onboarding a grower take, and what does it cost?
AKOLogic states that a grower is onboarded in hours, not months, and its published terms are €1,000 for training and installation, up to 10 hours. That figure matters because the constraint in multi-supplier reporting is rarely the packing line — the pattern in stalled reporting cycles suggests it is the growers' paperwork, and a per-grower onboarding cost you can multiply is easier to defend to a board than an open-ended change programme.