FlowSharp - use cases, case studies and examples

A collection of practical scenarios for explaining FlowSharp to customers, stakeholders and operational teams.

How to read these scenarios

Each scenario shows:

• the operational problem;
• how FlowSharp represents it;
• which features are involved;
• what to show in a demo;
• which metrics to observe.

The goal is not to describe every button, but to help explain product value.

1. Order to Cash

Problem

The commercial process starts in CRM, then crosses internal approvals, document generation, legal review, project kickoff and billing. Often each department sees only its own part.

How FlowSharp models it

• Process Map to show the whole path.
• Offer approval Flow to manage commercial evaluation and approval.
• Contract document as an operational step.
• Manual Legal review to make human control visible.
• Project kickoff Flow as the next phase.
• Events to connect approval and project opening.
• Analytics to measure review time, task cost and potential savings.

Recommended demo

1. Open the "Order to Cash" Process Map.
2. Show CRM, offer flow, contract, legal review and kickoff.
3. Enter the "Offer approval" Flow.
4. Show an AI status for risk/amount analysis.
5. Open a real item and show tasks, data, origin and timeline.
6. Go to Analytics and show average time in review plus ROI of an automatable task.

Message

"FlowSharp connects sales, back office, documents and automation in one governed process."

2. New customer onboarding

Problem

Customer onboarding requires data collection, document verification, internal approval, system setup and communications. If something is missing, the process gets stuck in a way that is often hard to see.

How FlowSharp models it

• Flow with phases: request, data collection, verification, setup, activation.
• Data Gate to block progress when required data is missing.
• Manual tasks for document checks.
• Webhook tasks to create the customer in CRM/ERP.
• AI task to classify risk or priority.
• Events to notify following teams.
• Calendar view for deadlines and scheduling.

Recommended demo

• Show the item creation form.
• Show an item in "Waiting for data".
• Fill missing data and advance the process.
• Show the AI task working only when data is present.

Useful metrics

• average time waiting for data;
• number of blocked items;
• manual tasks per onboarding;
• time from request to activation.

3. Complaints and escalation

Problem

A complaint can start from a portal, email or CRM. It must be classified, assigned, handled, possibly escalated and closed with evidence.

How FlowSharp models it

• API trigger or external event to create the item.
• Flow phases: received, classification, assignment, handling, escalation, closure.
• AI task to classify urgency and category.
• Manual tasks for customer contact and outcome verification.
• Timeout to avoid complaints staying idle too long.
• Event task to notify other flows or systems.
• Complete history for audit.

Recommended demo

1. Create a complaint from trigger or UI.
2. Show AI classification.
3. Show at-risk items in the dashboard.
4. Escalate through a transition.
5. Close with outcome and feedback.

Message

"The complaint does not stay in an inbox: it enters a tracked, measured and assigned process."

4. Purchase requests and approvals

Problem

Purchase requests involve budget, amount, manager, administration and suppliers. Rules can change depending on thresholds and categories.

How FlowSharp models it

• Flow with automatic rules for amount and category.
• Manual tasks for manager approval.
• Optional AI task for coherence or anomaly checks.
• Events to notify ERP or accounting.
• Custom roles to separate managers, administration and observers.
• Analytics for human cost and approval time.

Example user logic

• under 500 euros: fast approval;
• above 5,000 euros: double approval;
• critical category: compliance review;
• missing data: waiting for data.

Useful metrics

• average approval time;
• number of rejected requests;
• human cost per task;
• estimated savings from automating repetitive checks.

5. Document management with human control

Problem

Contracts, forms and documents require collection, verification, signature, archiving and communication. Many steps are semi-manual and difficult to measure.

How FlowSharp models it

• Process Map to connect document, flow, external systems and review.
• Flow with manual review tasks.
• Data Gate to require attachments or mandatory fields.
• AI task to extract or check information.
• Data Shield to protect sensitive fields.
• Events to start archiving or notification.

Recommended demo

• Show the document as a node in the Process Map.
• Open the item and show structured data plus history.
• Show manual review task and AI output.
• Show the final audit trail.

6. Maintenance and technical support

Problem

Technical interventions include request, scheduling, diagnosis, intervention, spare parts, customer confirmation and closure. Field work and administrative work are often disconnected.

How FlowSharp models it

• One item for each intervention.
• Calendar view for planned dates.
• Manual tasks for technician and back office.
• Webhook task toward management or ticketing system.
• Events to update customer or systems.
• Timeout for SLA.
• Analytics for average time and bottlenecks.

Useful metrics

• late interventions;
• average diagnosis time;
• time waiting for spare parts;
• percentage of tasks completed within SLA.

7. AI governance in processes

Problem

Companies want to use AI, but worry about sensitive data, untracked decisions and lack of human control.

How FlowSharp models it

• AI tasks inside explicit statuses.
• Data Shield on sensitive fields.
• Data minimization toward providers.
• Data Gate to avoid AI on empty data.
• Item history audit.
• Manual tasks before/after AI for human validation.
• Assistants configured for specific purposes.

Recommended demo

1. Show an AI provider with Data Shield.
2. Show a Flow with an AI status.
3. Show sensitive fields in the data contract.
4. Start an item with complete data.
5. Show AI output and history.
6. Explain that AI does not decide outside the process.

Message

"FlowSharp does not bring AI into operational chaos: it brings AI inside a governed process."

8. n8n as integration engine

Problem

n8n is excellent at connecting systems, but technical workflows often do not explain the business state of a process.

How FlowSharp models it

• FlowSharp governs status, rules, tasks and audit.
• n8n runs integrations and technical automations.
• Webhook tasks send data to n8n.
• Callbacks complete long tasks.
• Events connect steps and systems.
• Analytics measures automation value.

Recommended demo

• Show a webhook task in the designer.
• Show an item with a task running.
• Show the correlated n8n execution.
• Show the completed task and next transition.

Message

"n8n moves data. FlowSharp governs the process."

9. Browser extension for portal-based processes

Problem

Much operational work happens inside portals, web CRMs or SaaS business tools. Users do not want to copy data across tools all day.

How FlowSharp models it

• Browser extension to connect web context and FlowSharp.
• Side cockpit to view or start processes.
• Dedicated settings for activation and links.
• Links between external entity and FlowSharp item.

Recommended demo

• Open a customer or order page in a web system.
• Show the FlowSharp cockpit.
• Start or consult a linked item.
• Return to FlowSharp and show the same case in item detail.

10. Continuous improvement program

Problem

Companies want to improve processes, but struggle to choose priorities and prove results.

How FlowSharp models it

• Analytics to identify time, cost and bottlenecks.
• ROI simulator to compare automation candidates.
• Automation goals to track a program over time.
• Process Maps to align stakeholders.
• Flow versions to evolve processes without losing control.

Recommended demo

1. Start from Analytics.
2. Identify a slow manual task.
3. Estimate the ROI of automation.
4. Open the Flow and show where automation could enter.
5. Show the Process Map to explain the broader impact.

Message

"FlowSharp turns process improvement from opinion into measurable work."

11. From deviation to process improvement

Problem

A process can look linear on paper but still accumulate returns, escalations, waiting and out-of-standard cases in practice. Without a shared reference, a team only sees isolated problems and cannot tell where the journey is actually deteriorating.

How FlowSharp models it

• An expected path declared on the Flow, with deviations visible on items.
• OK/KO outcomes and scores to read quality alongside time and cost.
• A published Process Map, with health badges and Diagnostics to verify that links and start modes are still coherent.
• What-if to compare automation investment with potential savings, keeping measured data and estimates distinct.
• Map versions and a document PDF to make the decision easy to share.

Recommended demo

1. Open a published Process Map and show its health badge.
2. Enter a Flow, highlight the expected path and filter deviated items.
3. Open a deviated item: show its timeline, score and outcome.
4. Return to the map, start a What-if on a bottleneck and copy the summary.
5. Compare a new map version or generate the PDF for the review.

Message

"FlowSharp does not merely show where the process deviates: it helps decide which improvement is worth making and explain why."

Recommended screenshot set for demos

Prepare a small visual kit:

• Dashboard with active items and bottlenecks.
• Flow designer with statuses, tasks and rules.
• Item detail with timeline and transitions.
• Tasks view in kanban or calendar mode.
• Analytics with ROI.
• Process Map with systems, flows and manual steps.
• Trigger/API or n8n example for integration demos.
• AI/Data Shield screen for governance demos.
• Expected path, deviated item, What-if, map version and PDF for continuous improvement.
• Versioned SOP, task coverage and source citation for operating procedures.
• Candidates, initiatives, status and verified savings for the Automation Plan.
• Data Schema, item metrics, KPI cards, trend and goal for Flow KPIs.

Useful infographics in case studies

The most effective infographics are:

• from process to execution, to explain why Flow and Process Map coexist;
• human + automation + AI, to show the operating model;
• integration map, to position n8n, API, events, MCP and extension;
• ROI loop, to show measurement before automation;
• governance matrix, to show roles, audit and data controls.

These visuals help keep demos strategic without losing the operational substance.

12. Living procedures and controlled instructions

Problem

Operating instructions often live in PDFs or documents separated from the work. When a procedure changes, it is difficult to know which guides, tasks and Flows need review.

How FlowSharp models it

• Procedure Registry with immutable versions and content fingerprints.
• Citable sections linked to task guides.
• Bidirectional coverage between SOPs, Flows and tasks.
• Realignment warnings restricted to process maintainers.
• AI guide generation with mandatory human review.
• Governance of external domains embedded in instructions.

Recommended demo

1. Open a procedure and show its version timeline and coverage.
2. Enter the designer and link a task to a specific section.
3. Open the same task as an operator and show the guide and source citation.
4. Create a new SOP version and show the realignment warning in the designer.
5. Review the guide and mark the link as up to date.

Message

"The procedure is not a forgotten attachment: it is the versioned source of the work people perform."

13. From the automation portfolio to contractual savings

Problem

Automation opportunities are often recorded in presentations or backlogs disconnected from real costs. Even after a project starts, proving the savings and linking them to commercial terms remains difficult.

How FlowSharp models it

• Candidates derived from Process Map time and cost.
• What-if analysis that keeps measured data and estimates separate.
• Automation Plan with initiatives, investment, date and external reference.
• A system Flow governing the path through go-live.
• Verification of realized savings against the frozen cost.
• Immutable baseline and premium Saving Challenge with success fee.

Recommended demo

1. Open map Diagnostics and turn a candidate into an initiative.
2. Show the new item in the Automation Backlog Flow.
3. Open the Plan and compare expected savings, investment and status.
4. Return to the map, create and freeze a baseline.
5. Simulate terms, create a Challenge and show cumulative values, health and export.

Message

"FlowSharp connects the automation idea, the work needed to deliver it and the financial proof of the result."

14. Data contract and operational KPIs

Problem

Process data grows over time: forms, APIs, n8n and AI begin writing different fields, while dashboards and reports continue to depend on fragile definitions or external spreadsheets.

How FlowSharp models it

• Registry of declared and observed fields with provenance.
• Visible type conflicts and optional strict mode.
• Sensitive fields connected to Data Shield and protected exports.
• Per-Flow tables with payload columns and shared/personal views.
• Item metrics and aggregate KPIs with thresholds, goals and history.
• Internally calculated trends and forecasts.

Recommended demo

1. Open Data Schema and promote an observed field.
2. Mark a field as sensitive and show ReadOnly behavior.
3. Add the field to the table and save the team view.
4. Define an item metric and aggregate KPI with thresholds.
5. Show the card, trend, goal and forecast on the Flow dashboard.

Message

"Operational data becomes a governed contract and, in the same place, a process measurement system."