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Learn before you build
What software really costs, how long it takes, how to pick a partner, and how to put AI tools to work — for startups, SMBs and enterprises.
How Vahak Onboarded 800K Trucks Without a Sales Team
Vahak's supply-side unlock wasn't a slicker signup flow — it was rebuilding trust and verification to run asynchronously, so a truck owner could transact before a single document was fully verified. Here's the architectural call and what generalizes.
5 Mistakes Teams Make When Digitizing a Paper-Based Supply Chain
Supply chain digitization rarely fails at go-live. It fails in the six weeks after, when the paper shadow system quietly outcompetes the new software. Here are the five mistakes we see teams make — and how to recover before adoption collapses.
5 Mistakes Teams Make When Migrating a Live Transport Marketplace
Re-architecting a live freight marketplace while trucks are mid-route is a different problem from a standard platform migration. Here are the five mistakes we see engineering teams make — and the in-flight trip state trap that causes most of them.
How HealthPotli Fulfilled 500K Orders Without a Warehouse
A deep engineering walkthrough of the HealthPotli fulfillment stack — how partner-pharmacy inventory, prescription verification, and expiry-aware dispatch were architected to survive 500K real orders. Written for pharmacy operators evaluating what to build before they sign a vendor contract.
5 Mistakes Teams Make When Automating a Lending Operations Back Office
Most lending back-office automation projects don't fail at go-live. They fail six months in, when the exception queue quietly becomes the whole business. Here are the five patterns behind that drift — and how to recover.
How KarroFin Automated Credit Scoring for 250K Borrowers
A deep walkthrough of how KarroFin built an automated credit scoring pipeline for 250,000 borrowers — what the team tried first, why the model wasn't the bottleneck, and how the feature layer unlocked everything.
5 Mistakes Teams Make When Digitizing a Pharmacy
Most pharmacy digitization projects fail after launch, not before it. Here are five specific mistakes we see teams make when moving prescriptions, inventory, and fulfillment online — and how to recover once cracks appear.
How GimBooks Scaled GST Filing to 3M Users Without a DBA
GimBooks handled normal load fine but crashed every GST deadline cycle. Here's the architectural call that fixed it — and why horizontal scaling alone would have made the problem worse.
How Vahak Onboarded 800K Trucks Without Burning the Database
Vahak's onboarding pipeline scaled from hundreds to hundreds of thousands of trucks without breaking live matching queries. The unlock wasn't sharding or caching — it was separating write and read paths at the data model level.
5 Mistakes Teams Make When Digitizing a Transport Marketplace
Freight marketplace platforms rarely fail because of matching algorithms. They fail because the supply side was modeled as passive inventory. Here are the five mistakes we see mid-sized brokerages make when digitizing, and how to recover from each.
5 Mistakes Teams Make When Automating Loan Collections
Most collections automation projects ship faster outreach without modeling why borrowers actually miss payments. Here are the five mistakes we see NBFCs and digital lenders make — and how to recover before roll rates get worse.
5 Mistakes Teams Make When Automating Pharmacy Operations
Most pharmacy automation projects fail not because the software is bad, but because it was configured against an idealized workflow no pharmacist on the floor actually follows. Here are the five mistakes we see most often, and how to recover from each.
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