AI Feasibility & Validation Consulting -
Risk-Controlled AI Investment

An AI feasibility study is a structured 2-4 week analysis that determines whether a proposed AI use case is technically possible, economically viable, and strategically aligned. It produces an objective go/no-go decision basis covering: data readiness assessment, technical architecture options, vendor/build comparison, ROI modelling, risk register, and a fixed-price implementation plan if go-decision is reached.

AI verification answers 'are we building the system right?' (does it meet technical specifications and pass QA tests). AI validation answers 'are we building the right system?' (does it solve the actual business problem and produce intended outcomes in production). Both are required for production AI under the EU AI Act. Alice Labs delivers both as part of every implementation.

Run a feasibility study when: (1) the use case is novel or unproven in your industry, (2) the investment exceeds €100,000, (3) data quality is uncertain, (4) the use case is high-risk under EU AI Act, (5) internal stakeholders disagree on viability. Skipping feasibility on these projects creates 60-80% failure rates. A €10,000 study can prevent a €500,000 mistake.

A complete AI feasibility study includes: (1) business problem framing and KPI definition, (2) data audit — availability, quality, governance, (3) technical feasibility — model options, infrastructure, integration paths, (4) vendor vs build vs hybrid comparison, (5) cost-benefit ROI model with sensitivity analysis, (6) risk register with mitigation plans, (7) regulatory assessment (EU AI Act, GDPR), (8) phased implementation roadmap with fixed-price proposal.

A focused single-use-case feasibility study takes 2-4 weeks. Portfolio-level feasibility (3-5 use cases prioritised against each other) takes 4-6 weeks. Enterprise AI capability assessments take 6-8 weeks. We provide a complete deliverable — not a slide deck — including all data, models, and decision artifacts you need to commit budget with confidence.

Single-use-case feasibility: €10,000-€20,000 fixed price (2-4 weeks). Portfolio feasibility (3-5 use cases): €25,000-€45,000 (4-6 weeks). Enterprise AI capability assessment: €50,000-€80,000 (6-8 weeks). The fee is credited against full implementation if you proceed with Alice Labs as your delivery partner — making it effectively risk-free for committed buyers.

Production AI testing and validation includes: model performance testing (accuracy, precision, recall, F1), bias and fairness testing across demographic segments, adversarial testing (prompt injection, edge cases), load and stress testing, drift monitoring (data and concept drift), A/B testing infrastructure, and continuous validation against ground truth. EU AI Act high-risk systems require documented validation — we deliver compliant evidence packages as standard.

Yes. We offer independent AI validation and verification services for systems built in-house or by third-party vendors. Our independent assessment covers technical performance, bias and safety, security, compliance with EU AI Act and GDPR, and production readiness. Independent validation is increasingly required for AI procurement, board reporting, and regulatory submissions.

AI problem management consulting addresses AI systems that are underperforming, drifting, generating incidents, or failing to deliver business value. We diagnose root causes (data, model, integration, change management), prescribe remediation (retraining, architecture changes, governance, user adoption), and implement fixes. Common engagements: chatbot accuracy decline, recommendation quality drop, vision system false positives, generative AI hallucination control.

Yes. Post-deployment, we offer managed AI validation services from €5,000/month per system: continuous performance monitoring, drift detection, scheduled retraining, incident response, EU AI Act compliance reporting, and quarterly executive validation reviews. This is required for any production AI system you intend to operate at scale, especially in regulated industries.