Try it out? Free Gen AI tool for health insurance

They have an agent driven model. You can book a slot with an agent. Found ditto useful for the purchase step, but still found a lot of gaps in the selection and understanding parts pre-transaction. I personally bought a policy via ditto but learnt a lot more about my policy via this tool we built😅 still not sure if the policy i bought was truly the best fit for me which is a limitation of human-led sales

Okay. Cool idea You should have posted this on Indian Startup channel instead of Fitness

1. No Restoration Benefit: Unlike some other policies, this policy does not provide the restoration benefit. Restoration benefit allows for the full cover to be restored even after you have claimed part of it during the same year if you are hospitalized again. This can be helpful when multiple members of your family are hospitalized in the same year. 2. Limited Coverage for Certain Treatments: Some modern treatments may have limits imposed on them by this policy. The specific treatments and their limits will depend on the progressive order specified in Section 3.9 of the policy documents. 3. Room Category Limitation: If you choose a room category in a hospital that is higher than the eligible limit specified for your insured person, then associated medical expenses will be pro-rated as per applicable limits mentioned in Section 3.1. 4.Deductible: The deductible, if applicable, will be applied to all claims paid or payable under this policy once the aggregate amount exceeds the deductible limit within the same Policy Year. 5.Delayed Claim Intimation or Documentation: It is important to notify and submit claim documents within stipulated time frames mentioned in Sections 8.5 and Claims Process section regarding e-Consultation (Section 8). Failure to do so may result in delays or rejection of your claim unless delay reasons beyond control can be provided.

@Sreekanth thanks for the inputs. Asked the same question and got the reply above. This product is about 1 week of effort on our end on the AI part so its barely an MVP. How it works is we auto parse the pdfs of the policy documents and label each text section. When a question is asked, we have a custom piece of software that picks up relevant parts of the policy text and then feeds the question and policy text to an LLM with some prompting. We can tweak it by training better on things like how a top up can differ from a regular policy to get more useful answers Do check other policies and let us know via the feedback tab! :)