How should you evaluate an AI healthcare ERP?
Evaluate it on four axes rather than on the presence of AI. First, task specificity: which named tasks does a model perform, and what still happens deterministically? A vendor who cannot list the tasks is describing marketing. Second, review design: is a qualified human required to confirm every clinical output before it is saved, and is that confirmation attributed in an audit trail? Third, data handling: which provider receives the data, is it used for model training, is anything retained, and is that in writing? Fourth, cost and failure behaviour: is AI usage metered and bounded, and does the system still work when the model provider is unavailable? A product that answers all four concretely is a different proposition from one that answers none.
The AI healthcare software category is at the stage where the label carries no information. A rules engine, a search box and a language model are all being sold under the same adjective, and buyers have no way to tell them apart from a brochure.
The way through is to stop asking whether a product has AI and start asking what specifically it does with it. A vendor who can name the tasks, describe who reviews the output and say where the data goes is describing something real. A vendor who answers in adjectives is not.
These are the ten questions we would ask, phrased so a vague answer is visible as one. They apply to MedKit Care as much as to anyone else, and our own answers are on the AI healthcare software page.
Side by side
| MedKit Care | What a weak answer looks like | |
|---|---|---|
| Which specific tasks does the model perform? | A named, closed list: voice-to-prescription extraction, prescription drafting, lab-result suggestion, purchase-document extraction, payroll summary. | "AI is used throughout the platform to improve efficiency." No list, because there is no list. |
| What stays deterministic? | Billing, GST, bed allocation, bed-day accrual, stock arithmetic, receivables ageing, occupancy. Stated explicitly. | No answer, or a claim that AI improves the billing — which should worry you rather than impress you. |
| Who reviews clinical output? | A qualified user must confirm before anything is saved, dispensed or released, and the confirmation is attributed in the audit trail. | "The AI is highly accurate." Accuracy is not a review process. |
| Which provider receives the data? | Google Gemini over the API, DeepSeek as fallback. Named, with pinned model versions. | "Enterprise-grade secure AI." No provider named, so no assessment is possible. |
| Is data used to train models? | No. Sent only to answer the immediate request. | Silence, or terms that permit it in a clause you have to find. |
| Is audio or source material retained? | Consultation audio is not retained permanently; the confirmed structured data and transcript stay on the patient record. | Unspecified retention, which means indefinite. |
| How is AI priced? | Metered per organisation within plan limits, so the ceiling is visible. | Per-call billing with no cap, or "included" with an undisclosed fair-use limit. |
| What happens when the provider fails? | Second provider configured; if both are down the AI feature is unavailable and manual entry continues. | No fallback, so a vendor outage becomes your outage. |
| Does it work in Indian consultation conditions? | Built for Hindi-English code-mixing and phonetic drug names, matched against your own stock catalogue. | Demonstrated only on clean English dictation, which is not how Indian OPD sounds. |
| Can AI be turned off? | Yes — the platform is a complete clinic and hospital system without it. | The product is a thin wrapper around a model, so removing AI leaves nothing. |
When you should not switch
Cases where the honest answer is that MedKit Care is not the right choice right now.
- Your documentation load is genuinely light. AI-assisted documentation pays back in proportion to how much you write; at fifteen patients a day the return is small.
- You need the software to work with no connectivity at all. AI features require a connection even when the rest of the system does not.
- Your team has no capacity to review output carefully. A drafting tool used without review is worse than no tool, and that is a staffing question, not a software one.
- You are being sold AI as the entire product. If turning the model off leaves nothing usable, you are buying a demo rather than a system.
Frequently asked questions
What should I ask an AI healthcare software vendor first?+
Ask which specific tasks the model performs and which parts of the system stay deterministic. A vendor who can answer with a closed list is describing engineering; one who answers with adjectives is describing marketing.
Is it a red flag if a vendor will not name their AI provider?+
Yes. You cannot assess data handling, jurisdiction or reliability without knowing whose model is being called. "Enterprise-grade secure AI" is not an answer to that question.
Should AI ever calculate billing or stock?+
No. Those are rule-based calculations whose value is that they reproduce and audit. A model would make them probabilistic and remove the property that makes an ERP worth having.
How do I know AI output is being reviewed?+
Ask to see the review step in a live demo, and ask whether the confirmation is recorded against a named user in the audit trail. If output can reach a patient record without a human action, that is a design decision you should decline.
Is AI in healthcare software regulated in India?+
There is no single AI-specific healthcare software regime in India today; obligations come from professional conduct rules for prescribing and from data protection law for personal data handling. Practically, this means the prescribing doctor remains responsible for what is issued, so any tool that positions itself as replacing that judgement is a problem regardless of its accuracy. Confirm your own position with your professional body and legal advisor.
Read next
How our AI works, and who provides it
MedKit Care's AI features run on Google's Gemini models accessed over the API, with DeepSeek as a fallback provider. MedKit Care is an independent Indian company and is not affiliated with, endorsed by, or a partner of Google, OpenAI, Anthropic or Apple, and does not use ChatGPT or Claude in the product. No patient data is used to train any third-party model.
This page compares MedKit Care against a way of working rather than a named competitor product. We can describe our own system accurately and cannot verify another company's current features or pricing, so we do not publish claims about them.
Judge it against your own workflow
Twenty minutes, using your clinic or hospital's actual process. Ask us the hard questions on this page.