THE INTERACTIVE LAB

Try the work.
See the logic.

Explore the thinking behind a SaaS dashboard and an enquiry automation. Change the data. Follow the decisions. See what happens next.

Fictional samples. Real interactions.
01 / A SMALL SAAS WORKSPACE

A clearer view
of the moving parts.

Filter projects, update a status, or complete a task. Every number and chart is calculated from the sample data currently in view.

Demo data only. These invented projects, estimates and dates are not client results, revenue or performance claims.
Projects in view5 / 8

Match the current filters

Open pipeline value₹2,67,000

Fictional project estimates

Tasks complete65%

13 of 20 visible tasks

Tasks remaining7

Across the current results

Completed tasksFiltered sample projects · past 30 days
Completed sample tasks over the past 30 daysOldest interval first. 25 to 30 days ago: 1 tasks. 20 to 25 days ago: 2 tasks. 15 to 20 days ago: 3 tasks. 10 to 15 days ago: 2 tasks. 5 to 10 days ago: 1 tasks. 0 to 5 days ago: 4 tasks. Counts update with filters and task changes.4025 to 30 days ago: 1 tasks125d20 to 25 days ago: 2 tasks220d15 to 20 days ago: 3 tasks315d10 to 15 days ago: 2 tasks210d5 to 10 days ago: 1 tasks15d0 to 5 days ago: 4 tasks4Now
Older activitySample period ends 26 Oct 2026
Fictional project workspace. Select a project to manage its tasks.
ProjectEstimate / updatedStatus
₹62,0003 days ago
₹48,0006 days ago
₹85,00012 days ago
₹36,00019 days ago
₹72,00026 days ago

5 fictional projects shown. Select a project to explore its tasks.

02 / FOLLOW THE FLOW

An enquiry comes in.
A useful record comes out.

Step through an n8n style workflow with Python style processing. Inspect the input, validation, scoring and duplicate handling as they happen.

This runs entirely in your browser. No n8n workflow, Python runtime or external API is executed. No CRM is connected and no message is sent.
INPUT / FICTIONAL ENQUIRY

Use fictional details only. Editing the payload starts a fresh run. The included addresses use the reserved .example domain.

See the Python style scoring rules
email = enquiry["email"].strip().lower()
name = " ".join(enquiry["name"].split())
score = 40
score += 30 if budget >= 50000 else (
    15 if budget >= 25000 else 5
)
score += 20 if service == "automation" else 10
score += 10 if len(message) >= 30 else 0
priority = "high" if score >= 75 else "standard"

Illustrative Python. Equivalent JavaScript runs the calculation in this browser. These rules are sample business choices, not a prediction of lead quality.

PROCESS / INSPECT EACH STEP
  1. 01Sample enquiryNext step
  2. 02ValidateWaiting
  3. 03Normalise & scoreWaiting
  4. 04Sample CRMWaiting
  5. 05Notification previewWaiting

Workflow output

Browser simulation
{
  "status": "waiting_for_sample_input",
  "external_requests": 0
}

Ready. Choose a scenario, then step through the workflow or run it all.

1 sample CRM record in this run. Reset restores one seeded contact. Notification output is a preview only.

Simulation ready. No external services are connected.

FROM A SAMPLE TO YOUR SYSTEM

The interface is one part.
The decisions make it useful.

A production build adds your actual data model, access rules, integrations, validation and monitoring. This lab is a small, inspectable example of how I approach the pieces.

Talk through your idea