Portfolio
Projects and case studies
Each project is written up as problem, method, technology and outcome. Client projects and demonstrations are labelled so you always know which is which.
Built by DataClyroX
Systems we built and run ourselves, and working demos on example data. They show how we work; they are not client projects.
Meera: an AI assistant that answers visitors and books calls, without inventing anything
A website assistant that answers from the company's own content, refuses off-topic and risky requests, books calls in the visitor's time zone and passes leads to the sales team. Running on this website now.
Read the case study →Built by DataClyroXA lead engine that finds people asking for help, and ignores everyone selling
An engine that reads public posts and job listings, finds the few written by real buyers, scores them and drafts a first message for a person to send. It feeds DataClyroX's own sales pipeline every day.
Read the case study →Built by DataClyroXCreatorOS: business intelligence for YouTube creators
A working platform that shows a creator their whole business in one place: which videos earn, which brands to pitch, what each sponsorship is worth and what profit is left after expenses. Demonstrated with a complete synthetic channel.
Read the case study →Built by DataClyroXFinance and payroll automation: invoices, taxes and reminders in one place
A finance workspace that turns won deals into draft invoices, tracks GST, TDS and payroll deductions, sends payment reminders and prepares payroll for approval. DataClyroX runs its own finance on it.
Read the case study →Built by DataClyroXSales automation: no enquiry forgotten, no follow-up missed
A sales workspace where website enquiries become leads automatically, follow-ups are scheduled when nobody replies, quiet deals are flagged and each salesperson gets a morning to-do email.
Read the case study →Built by DataClyroXDemand forecasting you can try: a weekly forecast with an honest range
An interactive example of what a forecast looks like each morning: orders so far, the next six weeks predicted, and a likely range instead of a single guess. On our homepage, built on example data.
Read the case study →Have a problem your data could help with?
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