Things we’ve built, and what changed after. No invented metrics.

• Hospital Management

  A 180-bed private hospital, Delhi NCR

  Billing cycle (OPD)

  Same-day

  Billing cycle (OPD)

  Pharmacy revenue leakage

  −68%

  Pharmacy revenue leakage

  Nurse admin time saved

  40 min/shift

  Nurse admin time saved

  The problem

  OPD registration was done on paper. Pharmacy dispensing wasn't tied to patient records, so medicines went out on the ward and never made it to the bill. Lab results were printed and carried to doctors by hand, and now and then a result reached the treating doctor after the patient had already gone home. Closing the revenue cycle took 18–22 days after discharge, because the billing team had to piece together what had actually happened from three systems that didn't talk to each other.

  Outcome

  82% of OPD cases now close billing the same day. Revenue lost to unbilled pharmacy dispensing fell by 68% in the first quarter after launch. Ward nurses got back about 40 minutes a shift that used to go on paperwork. The hospital's COO put it simply: 'the first system that made the billing team and the clinical team actually talk to each other.'

  • Next.js
  • Node.js
  • PostgreSQL
  • Redis
  • +3 more

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• Education / School Management

  A chain of 3 schools, Noida

  Fee collection improvement

  +31%

  Fee collection improvement

  Teacher monthly admin time

  20 min (was 5 hrs)

  Teacher monthly admin time

  Parent queries handled online

  65%

  Parent queries handled online

  The problem

  Three schools meant three Excel files for attendance, three fee receipt books, and a central office that had no idea what was happening on any campus until someone called. Fee reminders went out as phone calls from the front desk, one parent at a time. Teachers compiled monthly attendance registers by hand, which ate 4–5 hours at the end of every month. Parent queries made up roughly 30% of the front desk's calls.

  Outcome

  Fee collection went up 31% in the first two months, mostly because automated reminders replaced phone calls. End-of-month attendance work for teachers fell from 4–5 hours to under 20 minutes. The parent portal now answers about 65% of the queries that used to need a call to the office. The central admin's verdict on the multi-campus view: 'something we didn't know we needed until we had it.'

  • Next.js
  • Node.js
  • PostgreSQL
  • Razorpay
  • +2 more

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• Pharmacy / Healthcare Retail

  A 12-outlet pharmacy chain, Delhi NCR

  Near-expiry write-offs

  −58%

  Near-expiry write-offs

  GST prep time

  2 hrs (was 2 days)

  GST prep time

  Purchase cost reduction

  ~11%

  Purchase cost reduction

  The problem

  Every outlet ran its own billing software, and none of them were connected. Head office couldn't see stock across the chain, so purchasing decisions were made by messaging outlet managers on WhatsApp. Near-expiry drugs only surfaced during physical stock counts, by which time the write-off was already locked in. GST returns meant exporting 12 separate sales files and reconciling them in Excel. Two days of work, every month.

  Outcome

  Near-expiry write-offs fell 58% in the first six months. GST prep went from two days a month to under two hours. Procurement started placing consolidated orders for the whole group, which brought average purchase cost down by roughly 11% through volume deals. Outlet managers now spend their time on customers instead of fielding stock queries on WhatsApp.

  • Next.js
  • Node.js
  • PostgreSQL
  • GST e-invoice API
  • +2 more

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• Manufacturing / Warehouse Operations

  A manufacturing company with 4 warehouses, Noida

  Mis-pick rate

  0.8% (was 6%)

  Mis-pick rate

  Monthly discrepancy investigations

  5 hrs (was 40 hrs)

  Monthly discrepancy investigations

  Daily manual Tally entry

  Eliminated

  Daily manual Tally entry

  The problem

  Stock moving between warehouses went invisible for days. Goods marked dispatched from one site wouldn't show as received at the other until a manager picked up the phone to ask. Mis-picks were driving a 6% customer return rate, and the operations head couldn't trace the cause because nobody recorded who picked what. Every count was manual, so investigating a discrepancy meant physically recounting whole bays.

  Outcome

  Mis-picks fell from 6% to under 0.8% in the first two months. Transfer discrepancy investigations that used to eat 40 hours a month now take under 5. The Tally sync made the manual entry role unnecessary, and that person moved on to more useful work. The operations head can see stock by location across all four warehouses on one dashboard, without calling anyone.

  • Next.js
  • Node.js
  • PostgreSQL
  • Tally TDL integration
  • +2 more

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• NGO / Social Sector

  A Delhi-based NGO managing 6 livelihood programmes

  Grant report generation time

  Same day (was 5 days)

  Grant report generation time

  Donor 80G letter turnaround

  24 hrs (was manual)

  Donor 80G letter turnaround

  Beneficiary records digitised

  100%

  Beneficiary records digitised

  The problem

  Donors lived in Excel, beneficiary files in paper folders, and grant utilisation in yet another spreadsheet tracked by hand against budget heads. Each quarterly grant report took 5 days, most of it spent digging through filing cabinets and matching disbursements to programme milestones manually. The previous year's FCRA compliance audit had flagged missing donor acknowledgement letters. And there was no way to tell whether a beneficiary had finished a programme or was stuck halfway.

  Outcome

  The quarterly grant report now gets done the same afternoon instead of over 5 days. 80G letters go out automatically within 24 hours of a donation being recorded, which closes the FCRA gap the previous audit flagged. Every beneficiary record across all 6 programmes is digitised. The programme director's team now uses the data to spot beneficiaries who've stalled mid-programme, instead of finding out at the end of the cycle.

  • Next.js
  • Node.js
  • PostgreSQL
  • PDF generation
  • +2 more

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• Hospitality / Hotel Management

  A 45-room boutique hotel, Rajasthan

  Overbooking incidents

  Zero

  Overbooking incidents

  Average checkout time

  Under 4 min (was 12)

  Average checkout time

  Housekeeping visibility

  Real-time

  Housekeeping visibility

  The problem

  Bookings arrived from three OTAs, phone calls and walk-ins, with no single availability grid. The hotel overbooked twice in one month, and one of those times a guest was turned away after a 4-hour drive. Housekeeping had no live view of which rooms were vacant, checked out or under maintenance; the supervisor ran it all off a whiteboard. Checkout meant pulling charges from three places (room, restaurant, mini-bar), so the front desk had queues every peak morning.

  Outcome

  No overbookings since the first month. Average checkout went from 12 minutes to under 4. The housekeeping supervisor wiped the whiteboard clean after week one and hasn't needed it since. Morning briefings now use live occupancy numbers instead of last night's spreadsheet export.

  • Next.js
  • Node.js
  • PostgreSQL
  • Channel manager API (Siteminder)
  • +2 more

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• Diagnostics / Healthcare

  A mid-size diagnostics lab, Delhi NCR

  Sample-to-report time

  −55%

  Sample-to-report time

  Audit failures (post-launch)

  Zero

  Audit failures (post-launch)

  Record accuracy

  Audit-grade

  Record accuracy

  The problem

  Sample tracking ran on paper registers plus Excel sheets kept by the front desk. Internal audits kept finding mismatches between intake records and test results. With ISO 15189 accreditation on the table, the manual setup had gone from inconvenient to genuinely risky.

  Outcome

  Zero audit failures across two back-to-back internal audit cycles after go-live. Sample-to-report turnaround dropped by roughly 55%. The front desk team called it 'the first system that matches how the lab actually works'.

  • Next.js
  • Node.js
  • PostgreSQL
  • PDF generation
  • +1 more

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• Real Estate

  A residential plot developer, Haryana

  Double-booking incidents

  Zero

  Double-booking incidents

  Sales rep availability check

  Instant (was phone call)

  Sales rep availability check

  Walk-in closing speed

  Improved

  Walk-in closing speed

  The problem

  Plot availability lived in an Excel file that someone updated by hand and passed around on WhatsApp. The sales team double-booked plots twice in six months, and one of those ended in a legal dispute. The developer had over 400 plots across three phases and no dependable way to show a walk-in customer what was actually available.

  Outcome

  No double-bookings since launch. Reps show live availability on a tablet during site visits instead of ringing the office. The developer reports walk-in leads are closing noticeably faster.

  • React
  • Next.js
  • Node.js
  • MySQL
  • +1 more

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• Logistics / Last-Mile Delivery

  A last-mile logistics company, NCR

  Billing disputes/month

  2 (was 12)

  Billing disputes/month

  Billing cycle

  3 days (was 15)

  Billing cycle

  WhatsApp coordination

  Retired

  WhatsApp coordination

  The problem

  They were running a dispatch operation on Salesforce, a tool designed for B2B sales teams. It was a bad fit: Salesforce thinks in pipelines, and they had trips. The real coordination happened in a WhatsApp group, so management couldn't see key decisions and billing disputes were common, with no record to settle them. Billing ran 12–15 days behind operations.

  Outcome

  The WhatsApp coordination group was retired within three weeks of go-live. Billing disputes fell from roughly 12 a month to 2. The billing cycle went from 12–15 days to 3. The ops manager called it 'the first time we've had an actual record of what happened on any given day'.

  • Node.js
  • React
  • MySQL
  • Tally export integration
  • +1 more

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• Healthcare / Multi-Specialty Clinic

  A 6-doctor clinic, South Delhi

  No-show rate

  9% (was 23%)

  No-show rate

  Front desk scheduling calls

  −40%

  Front desk scheduling calls

  Follow-up system added

  Post-launch extension

  Follow-up system added

  The problem

  Every appointment was booked over the phone. Front desk staff took the call, typed it into a spreadsheet and sent SMS reminders by hand. No-shows hovered around 23%. Three front desk staff spent roughly 60% of their day on scheduling instead of helping patients in the clinic. The clinic had already tried two off-the-shelf booking platforms; both were built for single-doctor practices and couldn't cope with each doctor having their own availability rules.

  Outcome

  No-shows dropped from 23% to 9% in the first month. Scheduling calls to the front desk fell by about 40%, and the three staff now spend that time with patients instead of on the phone. The clinic has since extended the system so doctors can book follow-ups themselves.

  • Next.js
  • Node.js
  • WhatsApp Business API
  • PostgreSQL
  • +1 more

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• Fashion / E-commerce

  A D2C apparel brand, Delhi

  Inventory discrepancy rate

  Under 1% (was 8%)

  Inventory discrepancy rate

  Returns processing time

  Same-day (was 3 days)

  Returns processing time

  Annual plugin cost saved

  ₹18,000

  Annual plugin cost saved

  The problem

  The brand ran Shopify with three inventory plugins that kept drifting out of sync with each other. Returns were handled by hand: after each return was inspected, someone updated stock manually. At around 800 orders a month, the inventory discrepancy rate had hit 8%, and customers were complaining about ordering items that turned out to be out of stock.

  Outcome

  The inventory discrepancy rate fell from 8% to under 1% within two months. Returns now get processed the same day instead of taking 2–3 days. And dropping the three plugins cut their Shopify app bill by ₹18,000 a year, which was a nice bonus.

  • Node.js
  • Shopify API
  • PostgreSQL
  • Webhook architecture
  • +1 more

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  Get in touch and we’ll share what’s relevant.

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Every case study here is anonymised at the client’s request, so names, exact locations and other identifying details have been blurred. The outcomes are real. If you want more detail on a project in your industry, get in touch and we’ll share what’s relevant.