“What will AI actually cost us?” is the first real question for most Indian businesses — and the honest answer is that the licence price is rarely the biggest number. Here’s a grounded breakdown in ₹ terms. (dgm implements osFoundry, a separate company’s platform — dgm is an independent integration partner, not osFoundry. General information, not financial advice; figures vary by scope.)
The four cost components
- Platform — per-seat SaaS or a flat-fee / self-hosted platform.
- Integration — connecting AI to your systems and data (usually the biggest line).
- Model / usage — per-token charges (often modest for typical business volumes).
- Ongoing operation — maintenance, monitoring, change management.
For most Indian businesses, integration and licensing dominate — not model costs.
Per-seat vs flat-fee economics
This is where the numbers diverge:
- Per-seat SaaS (~$20–30/user/month) is predictable per user but scales linearly — at 200 users, roughly $48,000–72,000/year ongoing, before renewals (see the pricing reviews).
- Flat-fee integration (e.g. dgm’s $3,999/month) doesn’t scale with seats — often cheaper for larger user bases; for a handful of users, per-seat tools may be cheaper.
Model your own numbers — there’s no universal winner.
The hidden costs (where India projects overrun)
- Data preparation — cleaning and structuring your data.
- Integration complexity — legacy systems, Tally, ERPs.
- Change management — getting staff to actually use it (see change management).
- Maintenance — keeping it working as systems change.
Over-focusing on token costs (usually small) while under-budgeting these is the classic overrun.
How dgm prices
dgm is transparent: a $399 one-time assessment and $3,999/month implementation on osFoundry, no per-seat fees (INR approximate; USD authoritative; 18% GST domestic). Model/usage costs and your own infrastructure are separate and depend on your workload. See also AI ROI and consulting cost.
General information, not financial advice. Costs vary by scope — get a scoped estimate for your use case.