Thinking
Technical articles on the WithPraxis platform
Technical insights into the WithPraxis platform, including data, models and decision workflows.
The WithPraxis platform is built around the data, models and decision workflows that support pricing, inventory and fulfilment decisions in production. These articles cover how the platform is architected: the unified data layer beneath it, the model behaviours used for live decisions, and the orchestration patterns that let capabilities run alongside existing ERP, commerce and CRM systems. Read these to understand how the platform is designed for operational decision-making, how its components fit together, and what to consider when integrating it with your own technical environment.
Autonomous Decisions: The Governance Framework Mid-Market Distributors Need Before Deployment
Autonomous agents can accelerate decisions and reduce costs in B2B commerce. But most mid-market distributors lack the governance frameworks to deploy them safely. Without audit trails, decision boundaries, escalation rules, and performance monitoring, autonomous systems become liabilities. This article maps the four control pillars required before autonomous decision-making goes into production—and the practical roadmap for implementing them without killing velocity.
Build vs Buy vs Partner: The AI Vendor Selection Framework for Mid-Market Distributors
Mid-market distributors face three paths when deploying AI: pre-built vendor models, custom development, or third-party APIs. Most lack a clear framework to evaluate them. The wrong choice delays implementation by 6-12 months and wastes £50,000-£200,000. This decision matrix maps implementation timeline, cost structure, and risk profile for each approach. Pre-built models deploy in 8-12 weeks at lower cost but limited customisation. Custom development takes 16-24 weeks with full control and competitive advantage. Third-party APIs offer middle ground at moderate cost and configuration flexibility. The right choice depends on data maturity, technical capacity, and competitive urgency. A distributor with clean data and a 6-month runway can pursue custom development. A distributor with fragmented systems and a 10-week deadline cannot. Four questions determine the viable path: data quality, timeline urgency, competitive differentiation, and internal technical capacity.
Real-Time Commerce Operations: Moving Beyond Static Dashboards
Most distributors manage operations through yesterday's reports. Morning meetings review exceptions, investigate anomalies, and plan interventions — all based on data that's already 12-18 hours old. Real-time operational intelligence transforms decision-making from reactive problem-solving to proactive opportunity capture.
Customer Lifetime Value Intelligence: Predicting Profit Per Relationship
Most B2B distributors calculate customer lifetime value by adding up historical purchases, missing predictive factors that signal churn risk and growth opportunities. True CLV intelligence uses behavioural patterns, payment data, and market context to guide resource allocation decisions before customer value changes become obvious in purchase history.
Multi-Depot Fulfilment Routing: When Driver Knowledge Isn't Enough
Manual fulfilment routing costs building materials distributors 18% in unnecessary expenses. Smart routing systems optimise multi-depot operations while preserving driver expertise.
Inventory Velocity Intelligence: How AI Accelerates Stock Turn Without Stockouts
Fifteen per cent of your working capital sits in stock that hasn't moved in six months. AI transforms this from reactive clearance to proactive velocity management, predicting turn rate decline 60–90 days before it shows up in traditional reports.