Adentris (YC P25)
Find mistakes in your medical records
Details
- External ID
- 47617852
- Source
- HN
- Company
- —
- Product
- —
- Website domain
- —
- Launched
- April 2, 2026
- Cohort
- —
- Upvotes
- 16
- Upvotes percentile
- 0.7197943444730077
- Tags
- —
- Fetched at
- Sept. 7, 2026, 9:26 p.m.
- Updated at
- Sept. 7, 2026, 9:26 p.m.
Description
Hey HN! We’re Dmitry, Sergey, and Alex, co-founders of Adentris (https://www.adentris.com/).In one sentence: we built a free product that allows patients and providers to upload medical charts in PDFs and automatically identify issues before they turn into treatment mistakes or denied insurance claims.Create a free account:https://app.adentris.comStep-by-step interactive demo for patients:https://app.arcade.software/share/snXezdUhG0zGh5JxZNeBStep-by-step interactive demo for providers:https://app.arcade.software/share/bxuXt2mwsz2UabvghFFKA year ago, we initially launched our demo on HN (https://news.ycombinator.com/item?id=44063000), and since then, we've developed a full audit product that integrates with Electronic Medical Records (EMR) systems via API across multiple clinics and hospitals.Why is this important?Medical records are crucial, but they are also susceptible to mistakes. As the Office of National Coordinator on Healthcare Technology notes, reviewing your own records is vital because "you may have forgotten to tell your healthcare provider something or they may have forgotten to write it down. The staff in your provider’s office are busy people who make mistakes just like everyone else." For Patients: Reviewing your records helps ensure their accuracy, which can prevent potential issues—for example, an empty "Allergies" field could be disastrous in an emergency room visit. The Health Insurance Portability and Accountability Act (HIPAA) guarantees your right to review and request corrections for errors you find. Our free tool allows anyone, regardless of medical knowledge, to flag potential discrepancies (like a mismatch in date of birth, medications, or allergies) to discuss with their provider. (See the official government guide: https://healthit.gov/get-it-check-it-use-it/check-it/ and this article: https://californiahealthline.org/news/check-your-medical-rec...). As an example, I (Dmitry) used the analysis on 800 pages of my own 5-year medical history and identified three issues to discuss with my primary care physician: mismatched medications, allergies, and outdated vaccinations. For Healthcare Providers: The product is a significant time-saver, automating the quality and compliance review that often takes dozens of hours of manual "scrubbing" each month. The free version includes two specialized rule libraries for providers: Acute care and Substance Use Disorder treatment.OUR ASK:We value community feedback on what we're building, especially from healthcare providers. We want to demonstrate how efficient and time-saving automated review is compared to manual chart scrubbing.Please share a link to our provider-specific interactive demo with the doctors and nurses in your network. It could save them a lot of time that they could spend with patients. To help the doctors and nurses in your network save valuable time that they could be spending with patients, please share the link to our provider-specific interactive demo with them.https://app.arcade.software/share/bxuXt2mwsz2UabvghFFKThank you.
Enrichment
- Theme
- health tracking and medical tools
- Vertical
- Healthcare
- Function
- Vertical SaaS
- Audience
- B2B
- AI stance
- AI-native
- Project type
- Commercial product
- Normalized one-liner
- identify errors in medical records
- Manually corrected
- False
Could you build this?
Partial Building the PDF upload UI and LLM prompt wrapper is simple, but reliably cross-referencing complex clinical medical records, medical billing codes (ICD-10/CPT), and insurance denial guidelines without hallucination requires clinical domain modeling and HIPAA compliance.
What it would actually take: The architecture requires a HIPAA-compliant ingestion pipeline (OCR with medical entity extraction via AWS Comprehend Medical or fine-tuned biomedical models), an accurate knowledge graph of insurance denial policies and ICD-10/CPT billing guidelines, and deterministic validation rules layered over LLM extraction to prevent medical hallucinations. It requires clinical informatics expertise and healthcare regulatory compliance.
Discussion
4 comments analyzed.
Competitors
Other products that read as similar to this one — 42 launches clear the similarity bar, closest 8 shown.
Attention rank: #12 of 43 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 112 days after the earliest competitor.
- DoseLucid · ph · 2026-09-18 · 1 upvotes · similarity 0.41
- YourDoc · ph · 2026-09-28 · 2 upvotes · similarity 0.41
- VidaRecord — Tu historial médico · ph · 2026-09-12 · 1 upvotes · similarity 0.40
- Medicalink · ph · 2026-09-10 · 1 upvotes · similarity 0.38
- Dr. Ralph · hn · 2026-01-06 · 5 upvotes · similarity 0.37
- Clinicwide · ph · 2026-09-26 · 1 upvotes · similarity 0.37
- ClaimAppeal AI · ph · 2026-09-18 · 1 upvotes · similarity 0.36
- I built a health protocol cheatsheet from expert recommendations · hn · 2026-02-09 · 10 upvotes · similarity 0.35
Other launches for this product
- No other launches for this product.
Same idea, different domain
Nobody's really built a vertical saas tool for Insurance yet.