About FSB Solutions

FSB Solutions is a specialist consultancy helping organisations adopt data-driven ways of working and integrate AI into core processes. We combine senior-level strategy with hands-on engineering to move projects from ideation to production, focusing on measurable business value, operational reliability and long-term capability building.

Our approach balances short-term impact and sustainable change: we rapidly validate high-value use cases through focused pilots, then industrialise successful pilots into resilient, observable systems. We apply principled model governance and data stewardship to ensure solutions are compliant with European regulations and aligned with your risk tolerance.

What we offer

• Rapid discovery workshops and feasibility assessments to prioritise use cases with clear ROI.
• End-to-end delivery: data platform design, model development, MLOps and product integration.
• Operational excellence: monitoring, alerting, cost governance, and runbooks for incident response.
• Governance & compliance: privacy-by-design, GDPR alignment, and model explainability processes.

Engagement models

We adapt to organisational needs with flexible engagement patterns:

• Short pilot (4–8 weeks): Rapid prototyping focused on a single, measurable KPI to demonstrate feasibility and value.
• Scale & production (3–9 months): Harden piloted solutions for production including MLOps, CI/CD and operational monitoring.
• Managed service: Continuous delivery and maintenance of AI services, SLA-backed operations and periodic optimization cycles.
• Capability build: Coaching, training and governance setup to transfer skills and enable internal teams.

Approval-ready project ideas

The following concise proposals are designed to be presented to stakeholders for rapid approval. Each includes a short objective, high-level deliverables and expected business impact.

• Inventory Forecast Pilot (Retail): Objective — reduce stockouts and overstocks. Deliverables — 6-week pilot, probabilistic forecasts, measurable reduction in stockdays. Impact — lower carrying costs and improved availability.
• Predictive Maintenance Proof (Manufacturing): Objective — reduce unplanned downtime. Deliverables — sensor data integration, anomaly detection model, 3-month pilot with KPI tracking. Impact — reduced downtime and maintenance costs.
• Document Automation MVP (Finance): Objective — accelerate document processing. Deliverables — NLP-based document classification and extraction pipeline, integration to downstream systems. Impact — faster processing, fewer manual errors.
• MLOps Quick-Win (Platform): Objective — reduce model deployment time. Deliverables — CI/CD templating, model registry and a deployment playbook. Impact — faster time-to-production and lower operational risk.
• Data Quality & Governance Sprint (Compliance): Objective — prepare for GDPR audits. Deliverables — data lineage, access controls, pseudonymisation guidelines. Impact — improved audit readiness and lower compliance risk.

Success metrics we track

We recommend aligning pilots with a small set of measurable metrics (business + technical):

• Business KPI improvement (e.g., % reduction in stockouts, % increase in throughput).
• Model performance (accuracy, precision/recall where relevant) and calibration.
• Operational readiness (deployment time, mean time to recovery, uptime).
• Data quality (completeness, freshness and lineage coverage).