What we solve
The problems behind everyday decisions
Where data is fragmented, ownership is unclear, and confidence is low.
These are not strategic exercises or future plans. They are the day-to-day decisions that shape cost, service, risk, and performance.
This is not strategic planning, transformation programmes, or future visioning. It focuses on decisions that already exist and are already being made.
Why organisations choose WithPraxis
Employee-owned, not VC-backed
No pressure to upsell services or chase quarterly targets. Long-term relationships over short-term revenue.
Work on real decisions, not transformation theatre
We focus on specific decisions that already exist and are already being made. No roadmaps that sit on shelves.
Platform-agnostic and independent
No vendor partnerships, no technology bias. We integrate with what you already have.
Built from operational experience
This work comes from repeated experience inside complex organisations, not academic theory or consulting frameworks.
The problems we see
Across many organisations, the same issues appear again and again:
- Decisions sit between teams, systems, and responsibilities
- Data exists in many places, but people don't know what to trust
- Different teams work from different numbers
- Accountability is unclear or shared
- Questions get revisited instead of resolved
- AI and automation are discussed before decisions are stable
These are not technology problems.
They are decision problems.
The kinds of problems we solve
We work on practical decision challenges such as:
- Knowing where to look for reliable information
- Bringing together data that lives across multiple systems
- Understanding who customers actually are
- Identifying gaps, duplication, or missing data
- Making sense of performance without trawling reports
- Supporting decisions that need to be made quickly and repeatedly
How we solve them
We solve these problems by designing and building focused, AI-driven applications that support real decisions.
This includes:
- Dashboards that bring together fragmented data into one clear view
- Tools that identify gaps or inconsistencies in customer and product data
- Custom middleware that anchors customer identity across systems
- Applications that support campaigns and personalised journeys with reliable data
- Intelligent search and discovery that understands products, images, and intent
- Visual tools that help people see outcomes before they commit
- Automated enrichment of product data, content, and supporting narratives
This is not workshops, roadmaps, or platform selection. It happens inside live operations, not alongside them. One decision at a time.
Each application is built around a specific decision, not generic reporting.
See what this looks like in 'practice'.
Real examples of decision-support applications we've built.
View examplesWhat makes this different
We don't start with platforms, tools, or AI for its own sake.
We start with:
- A real decision that matters
- The people responsible for it
- The information they need to decide well
Technology is used only where it genuinely helps.
Where this work happens
We began in commerce and digital operations because:
- Decisions are frequent and visible
- Data already exists, but is fragmented
- The impact of better decisions is immediate
From there, the same approach applies to decisions in:
- Finance
- Branches and stores
- Operations and logistics
- Marketing and commercial planning
One decision at a time.
How we work
In practice, this means:
- Identifying a decision that genuinely matters
- Understanding how it is made today
- Clarifying ownership and success criteria
- Bringing the right data together
- Designing and building a focused application to support it
- Testing it in real use and improving it over time
This work happens alongside real operations, not in workshops.
A practical place to start
Most organisations begin with one decision and one application.
That is usually enough to prove value, build confidence, and decide what comes next.
What this means in practice
What this means in practice
What problems does WithPraxis solve?
WithPraxis solves operational decision problems in pricing, inventory and fulfilment where ownership is shared, data is fragmented across ERP and commerce systems, and outcomes are inconsistent. These typically include pricing changes, stock allocation, fulfilment routing and exception handling for distributors and commerce businesses.
Why are these problems hard for distributors and commerce teams to fix?
They are hard because the decisions sit between systems and teams rather than inside any single one. Pricing data lives in the ERP, stock data in the WMS, customer data in the commerce platform, and the actual decision still depends on manual judgement.
Why does better reporting not solve this?
Reporting tells you what already happened, but it does not change how the next pricing, inventory or fulfilment decision is made. The fix is structuring how the decision is owned, what inputs it uses and how its outcome is measured.
Where does a typical engagement start?
It starts with one live operational decision that already affects margin or service, such as a pricing rule, a stock allocation policy or a fulfilment routing choice. We make that single decision measurable and repeatable before scaling.
What kind of impact does this produce?
Typical results include improved gross margin from better pricing decisions, fewer stock imbalances across locations, and faster fulfilment response. The impact comes from making decisions consistent rather than from new technology.