Solutions

From fragmented systems to a governed AI operating layer.

Five connected capabilities. Most engagements start with one operating challenge and extend once AI is resolving it in production.

Fragmented systems to governed AIIllustrative

Fragmented systems
- ERP & finance
- CRM & quoting
- Service desk
AI operational layer
- Shared definitions
- Risk thresholds
- Agent authority
Prioritised risks
- Margin exposure
- Delivery risk
Workflow actions
- Reprice
- Re-plan

Scope

Decision-first

Control

Human approval

Solution navigator

Select a capability.

Each capability is described by the problem it addresses, what AWF builds, and the business effect you should expect.

Capability A

Executive Intelligence

The problem

Leadership reviews the business through functional reports that disagree with each other. By the time finance, operations and commercial numbers reconcile, the window to act on them has closed.

What AWF builds

A single cross-functional view built on shared definitions, so one number means one thing in every function.
Risk signals tied to thresholds the executive team sets — margin erosion, delivery slippage, concentration exposure.
Decision records that capture what was decided, on what evidence, and what happened next.

Expected business effect

Executive reviews spend their time on judgment rather than reconciliation.
Emerging risk reaches the people who can act on it while options remain open.
Decisions can be revisited with their original context intact.

Full reference

All five capabilities in detail.

The same content, laid out for reading and linking.

Executive Intelligence

A cross-functional command view of the business, with traceable decisions.

Leadership reviews the business through functional reports that disagree with each other. By the time finance, operations and commercial numbers reconcile, the window to act on them has closed.

What AWF builds

A single cross-functional view built on shared definitions, so one number means one thing in every function.
Risk signals tied to thresholds the executive team sets — margin erosion, delivery slippage, concentration exposure.
Decision records that capture what was decided, on what evidence, and what happened next.

Expected effect

Executive reviews spend their time on judgment rather than reconciliation.
Emerging risk reaches the people who can act on it while options remain open.
Decisions can be revisited with their original context intact.

Operations Intelligence

Bottlenecks, service delivery, capacity and exceptions, in operational time.

Operations knows where work is stuck, but that knowledge lives in spreadsheets, inboxes and individual experience. Constraints are diagnosed after they have already cost delivery.

What AWF builds

A flow model of how work moves through the business, with stage-level constraints and ownership made explicit.
Capacity and demand modelling against real committed work rather than annual assumptions.
Exception handling that routes the deviation to the right operator with the context needed to resolve it.

Expected effect

Constraints are visible while they can still be re-sequenced.
Escalation stops depending on who happens to notice.
Operational knowledge becomes institutional rather than personal.

Commercial Intelligence

Pipeline quality, pricing and margin discipline, retention risk.

Pipeline volume is reported; pipeline quality is not. Pricing decisions are made without the delivery cost that follows them, and churn signals surface after the renewal conversation.

What AWF builds

Pipeline scoring grounded in delivery history and fit, not stage age alone.
Price and margin analysis that connects quoted work to what it actually costs to deliver.
Retention signals assembled from service, usage and commercial behaviour rather than sentiment.

Expected effect

Commercial effort concentrates on work the business can profitably deliver.
Discounting decisions carry their margin consequence at the point of the decision.
Account risk is raised early enough to change the outcome.

AI Workflow Automation

Governed copilots and agents with approvals and audit trails.

AI pilots run beside the business rather than inside it. Nobody can state what a model is permitted to do, who approved it, or how to reverse it — so nothing reaches production.

What AWF builds

Copilots scoped to defined operational tasks, reading from the governed model rather than ad-hoc exports.
Agents with explicit authority limits, mandatory human approval on consequential steps, and safe failure paths.
Complete audit trails: inputs, model version, approver, action taken and result.

Expected effect

AI moves from demonstration into supervised production work.
Risk, legal and audit can answer what the system is allowed to do.
Automation expands on evidence rather than enthusiasm.

Data Foundation

Source integration, the semantic model, quality and access control.

Data exists in every system and is trusted in none. Definitions differ by department, quality issues are discovered downstream, and access is managed per tool rather than per person.

What AWF builds

Integration of the source systems that matter to the decisions in scope — not a full estate migration.
A semantic and operational model encoding entities, metrics, thresholds and business rules in one place.
Quality checks, lineage and role-based access enforced at the model rather than in each interface.

Expected effect

Downstream work stops re-litigating definitions.
Data quality problems surface where they originate.
Access and governance hold as new use cases are added.

Which decision is costing you the most?

We scope from the decision backwards — never from the technology forwards. See how the work is sequenced on the approach page.

Book a 30 minutes free consultation See our approach