Data & AI platform by Data Analytics
Which signals in your business data deserve attention before you ask a question? ENABLE is developing proactive improvement opportunities: suggestions with sources, context and explicit assumptions. This capability is planned and in development, not live in the ENABLE client portal. The first version is intended for decision support, not automatic execution.
The examples on this page are hypothetical situations, not customer cases.
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Planned / in development · V1 without execution
Hypothetical design of three suggestions below the Overview greeting. Not an actual product screen, client data or proven outcomes.
01 / Hypothetical suggestion
Planned status: to investigate · no action executed
02 / Hypothetical suggestion
Planned status: to investigate · no action executed
03 / Hypothetical suggestion
Planned status: to investigate · no action executed
Planned V1 next steps: View all opportunities · Investigate something else · Dismiss. This example performs no analyses or actions.
01
AI improvement opportunities from business data do not start with an isolated recommendation. A suggestion must be traceable to authorised sources and a reviewable analysis. The planned proactive AI analysis could highlight a change in payment behaviour or unusual inventory development. Users assess whether the signal is valid and investigate its context before making a decision.
Automatic business analysis here describes an analysis and signalling direction, not a promise of flawless predictions. Each card must show its title, sources, investigated period, analysis time and assumptions. Expected impact is explicitly labelled as an estimate; missing data and uncertainty remain visible. No outcomes from this future functionality have been demonstrated.
02
The planned starting point sits below the user greeting on Overview: ‘Opportunities for your organisation’. At most three evidence-backed suggestions keep the overview manageable. In the design, ‘View all opportunities’ leads to the full list and ‘Investigate something else’ allows a custom analysis question. Examples on this page are hypothetical designs, not a product screen or actual client notifications.
An empty state should explain that no sufficiently supported opportunity is available rather than invent a suggestion. Stale source data require a visible freshness warning. Sections such as ‘Awaiting your approval’ and ‘Ongoing actions’ are optional designs for later phases; V1 does not start execution.
03
The intended topics are independent of industry or client: revenue, costs, cash flow, capacity, inventory and data quality. Revenue analysis requires different definitions from a capacity question. Semantic mapping is therefore needed: what do invoice, order, customer, product and employee mean in your organisation? Source fields from systems such as Exact or Business Central must first be mapped and validated against these concepts. A connection alone does not establish that the meaning is correct.
AI decision support for SMEs can begin with a scoped question and reliable data. In the Netherlands and Belgium, configuration differs by administration and workflow, not because a generic AI recommendation is automatically locally correct. Data quality, ownership of definitions and permissions determine which analysis is responsible.
04
V1 is planned/in development and limited to suggestions, supporting evidence, further investigation and dismissal or status tracking. Users can assess an opportunity and indicate that it is not relevant. This version does not execute payments, inventory changes, client messages or other actions. An investigation is not approval to change a source system.
Permissions must be enforced per role and client environment when reading sources and displaying evidence. A user must not see another client's data through a recommendation. Logging and periodic permission reviews are design requirements. MCP does not automatically inherit source permissions, RLS or OLS: the selected integration must actually apply the correct identity, scope and controls.
05
The future workflow is: substantiate → investigate → prepare → approve → execute through authorised MCP → follow up. Approval, MCP writeback, application generation and outcome measurement belong to later phases, not V1. Protection against double execution and a reviewable action history must then be explicitly designed and tested. This page does not promise a delivery date.
Want to explore which business data could support an initial analysis? Discuss your sources, definitions and boundaries in an ENABLE demo, or start with the MCP Readiness Scan. The demo helps distinguish the existing platform approach from the planned roadmap. A demonstration of dashboards or a client portal is not evidence that proactive improvement opportunities are already available.
No. This capability is planned and in development, not live in the ENABLE portal. The examples are hypothetical; no delivery date is promised.
That depends on the analysis question. Invoices, orders, customers, products, employees and planning need mapping to validated business concepts. Only sources the user is authorised to access may be used.
No. Planned V1 only includes suggestions, evidence, investigation and dismissal/status. Approval and execution through authorised MCP belong to future phases.
Impact is an estimate based on sources and assumptions, not a guarantee. Source period, analysis time, uncertainty and freshness must be visible. Users validate the evidence before making a decision.
The design requires role- and client-based checks for both data reading and evidence display. MCP does not provide these automatically. Integration and isolation must be configured and tested, including logging and access revocation.
The planned design shows a clear empty state or freshness warning. Insufficient evidence should not result in an invented opportunity. New source data must first be checked.
Which sources, users and checks does your application need? Discuss your question in an ENABLE demo.
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