The two base models, and why the difference matters more than the number
Almost every LIS in the Indian market prices one of two ways: per-report (you pay a fixed amount for every report generated, no matter how many) or fixed monthly (you pay a flat fee for a bundled report allowance, users, and branches). Some vendors blend both into tiered plans.
The two models don't just differ in price — they differ in what happens when your volume changes. Per-report pricing scales linearly with cost and never runs out. Fixed monthly pricing is cheaper per report at volume, but only within its cap; cross the cap and you're either blocked or paying overage.
The actual breakeven math (using Dr.Lably's published plans as an example)
You don't need a spreadsheet consultant for this — it's one calculation: flat monthly fee ÷ per-report rate = the report volume where fixed pricing starts winning. Below that volume, pay-per-report is cheaper. Above it, the flat plan is cheaper, and stays cheaper as volume climbs further.
Using Dr.Lably's own published pricing (visible at /pricing without a sales call) as a concrete worked example:
| Plan | Price | Report allowance | Breakeven vs ₹1/report | Best fit |
|---|---|---|---|---|
| Wallet (per-report) | ₹1 / report | Unlimited, pay as you go | — | New or low-volume labs, no monthly commitment |
| Growth (monthly) | ₹399 / month | Up to 500 reports | ~399 reports/month | Small labs past the startup phase |
| Scale (monthly) | ₹999 / month | Up to 1,500 reports | ~999 reports/month | Growing multi-branch labs (up to 2 branches) |
| Premium (monthly) | ₹1,499 / month | Up to 3,000 reports | ~1,499 reports/month | High-volume labs wanting AI-assisted reporting |
Where hidden cost actually appears
The sticker price rarely tells the full story. In practice, the gap between quoted price and actual 12-month cost shows up in a small, predictable set of places:
- Onboarding and data migration fees charged separately from the subscription
- Per-user or per-branch charges once you exceed the plan's included count
- Report caps that trigger either a hard block or an overage fee mid-cycle
- "Core" features gated behind a higher tier that wasn't obvious during the sales pitch (custom templates, multi-branch support, integrations)
- Support tiers where fast response is itself a paid upgrade
Build a 12-month model before you commit
Put recurring fees, one-time fees, and your expected report volume into a single sheet, then project three scenarios: current volume, 2x growth, and your busiest seasonal month. This reveals whether a plan's economics hold up as your lab changes, not just how it looks on day one.
For per-report pricing, the risk is linear cost growth with no ceiling — fine if volume stays low, expensive if you scale hard. For fixed plans, the risk is the cap: model what happens the month you exceed it, and confirm in writing whether that means a hard stop, an automatic upgrade, or an overage charge.
Choose for stability, not just the lowest number today
A plan that's ₹200 cheaper today but has an unclear overage policy can cost more by month six than a slightly higher plan with a predictable ceiling. Predictable cost also has a second-order benefit: it makes hiring, outreach, and expansion planning easier, because your software line item isn't a variable you have to re-forecast every quarter.