The solution is pre-trained on a representative sample of your own data before go-live, so it arrives calibrated rather than cold. Clients typically see ~85% straight-through accuracy from day one, rising to 93–95% for the majority of transactions within four weeks as the context layer refines on real interactions and operator feedback.

We deliver ~85% accuracy from day one, rising continuously as the system learns from operator feedback and real transaction data. Clients typically start with human review across all cases, then progressively move individual transactions onto autopilot as their confidence score crosses the recommended threshold of 93–95%. Within four weeks, 80–90% of cases reach that threshold — meaning the vast majority of your volume can be running on full autopilot within a month.

Every operator action — corrections, approvals, escalations — is captured as a "decision trace" and fed back into the context layer. This continuously sharpens the system's accuracy for your specific data patterns, supplier behaviour, and business rules, without requiring manual retraining or any IT involvement.

It draws on a proprietary combination of extraction certainty, contextual match quality, rule-compliance signals, and historical per-sender accuracy — calibrated specifically to each use case rather than applied as a generic threshold. This means items are only surfaced for human review when the system has genuine uncertainty, making the human-in-the-loop handoff reliable rather than arbitrary.

Yes, without limitation. Large documents are decomposed into parallel processing units, so a 100-page PDF or a multi-tab Excel file is handled with the same throughput and accuracy as a single page. Non-standard layouts, mixed languages, and complex formatting are supported natively.

We integrate with all major ERP systems — SAP, Oracle, Microsoft Dynamics, and others. Rather than prescribing a fixed approach, we define the integration strategy together with your IT team upfront, selecting the right connectivity method (middleware, OData/REST, IDoc/EDI, or direct APIs) based on your existing landscape and governance requirements. Our forward-deployment team then owns the full implementation. From your side, we need an initial architecture alignment session, relevant system access, and security approvals — typically 1–3 hours per week during setup only.

Yes, fully. When an exception is detected — for example, a price discrepancy between a PO and its confirmation — the system can route it automatically to the responsible team based on your defined escalation logic. Once resolved, the feedback is captured and downstream steps resume automatically: no manual re-entry required.

There is no practical upper limit. Active deployments range from a few hundred to several hundred thousand article numbers within a single use case, with no impact on processing speed or accuracy at scale.

Yes. We treat this as a long-term partnership, not a one-off implementation. Non-fundamental changes — new business rules, adjusted escalation thresholds, or minor process updates — are implemented free of charge as part of the ongoing engagement.

Every client is assigned a dedicated Customer Success Manager as a permanent point of contact. SLA response times are contractually defined, and check-in meetings can be scheduled at whatever cadence suits your team — including regular post-launch syncs.

Requirements are minimal by design: 1 Project Manager (~1–2 hrs/week), 1–2 Process Owners from the relevant business unit (~1 hr/week), and 1–2 IT contacts (~1–3 hrs/week depending on integration approach) for the duration of the project. No dedicated project team or new infrastructure is needed on your side. Typical project duration is between 6–8 weeks, depending on complexity of the use case.

Speed, cost certainty, and domain depth. An in-house equivalent typically requires 6–18 months and a dedicated engineering team, with no guarantee of achieving enterprise-grade accuracy. GeneralMind goes live in 6–8 weeks, backed by a team that has already solved these exact supply-chain coordination problems across many deployments — at zero upfront development cost.

A comparable in-house build — covering extraction, ERP integration, confidence scoring, and a human-in-the-loop interface — typically requires €500K–€1.5M in initial engineering spend, plus a sustained team for maintenance and iteration. GeneralMind’s transaction-based model has no upfront cost; total cost of ownership over three years is typically 60–80% lower than a self-built equivalent.

Based on the volume of documents processed monthly. No per-seat licensing, no setup fees. The model is designed so your ROI is clear from day one — we walk through a detailed proposal tailored to your volumes during the Deep Dive.

Yes. EU-hosted infrastructure, SOC 2 Type II certified, ISO 27001 compliant, fully GDPR compliant. Your data is never used to train models or shared with other customers. All processing happens in isolated, encrypted environments.

Any format your suppliers or customers send — emails, PDFs, Excel, fax-to-email, scanned documents. Non-standard layouts, mixed-language documents, and complex formatting are supported natively. 14+ business languages including English, German, French, Spanish, and more.

Absolutely. Most customers start with a single workflow — such as sales orders or invoice processing — and expand to additional use cases once they see results. The platform is designed for incremental rollout with no rework required.

GeneralMind handles the unstructured-to-structured gap that RPA and rule-based tools can’t. It complements existing automation by handling the messy, variable-format inputs that require understanding — not just pattern matching. It integrates alongside your current stack, not instead of it.