Client/Industry
A nutritional genetics company leveraged DNA insights to automate personalized dietary recommendations and wellness management.
A digital platform that uses Claude Haiku 4.5 to read lab reports and extract blood biomarker information to turn them into structured data for personalized nutritional supplement formulation.
Request a DemoA nutritional genetics company leveraged DNA insights to automate personalized dietary recommendations and wellness management.
Over 88% of consumers have reportedly made dietary changes to improve their health, yet most still rely on broad nutrition guidance that does not reflect their individual biology.
GenoPalate wanted to make its personalized nutrition recommendations more accurate by adding blood biomarker data to its existing DNA and diet model. The challenge was that members uploaded lab reports as regular PDFs from different labs, so the formats, labels, and measurement units were not consistent.
AkshatMedTech Digital Health built an AWS-based processing pipeline to handle these reports automatically. The system de-identifies PHI and uses Claude Haiku 4.5 through Amazon Bedrock to read the lab reports and extract the clinical values GenoPalate needs.
Those biomarker results are then mapped to GenoPalate’s nutrient model. The pipeline is live in production today and handles the lab reports GenoPalate members upload through the product, giving GenoPalate another source of individual health data to use when creating personalized supplement formulations for each member.
Inconsistent Lab Report Formats Members submitted bloodwork from many different laboratories, with different layouts, labels, units, and document structures.
01Limited Report Compatibility The existing system worked with predictable report formats, but new ones required new rules to read and extract the data correctly.
02Sensitive Health Data Protection Lab reports contained PHI, which had to be detected and removed to meet HIPAA requirements before the document could move through the AI workflow.
03Inconsistent Biomarker Data Usage Processing lab reports inconsistently made it difficult to use their biomarker data reliably in GenoPalate’s personalization model.
04Lack of Third-Party Integration Billing systems & external health tools (e.g., wearables, EHRs, or fitness apps) remained disconnected from the main system.
05Claude Haiku 4.5 runs through the Claude API on Amazon Bedrock and reads the lab report content.
It extracts the clinical biomarker values GenoPalate needs from reports with different layouts, labels, and units, reducing reliance on format-specific parsers.
Learn MoreThe extracted values are converted into structured biomarker data and mapped to GenoPalate’s nutrient model.
This allows blood test results to become part of the information used to create personalized nutritional supplement formulations.
Learn MoreWe built a HIPAA-compliant platform with an event-driven AWS pipeline that validates uploaded lab PDFs, detects and redacts PHI, and prepares Markdown for further processing.
This gives GenoPalate a consistent way to prepare reports from different laboratories before sending the required information to the AI workflow.
Learn More# Lab ReportGlucose: 92 mg/dLHbA1c: 5.3 %Vitamin D: 34 ng/mLFerritin: 71 ng/mLOur HIPAA-compliant platform’s try-before-you-subscribe option allows users to experience personalized nutrition insights before committing to supplement subscriptions.
For continued guidance, a six-month subscription includes optional consultations with a resident dietitian.
Learn MoreAdoption of GenoPalate’s lab report processing feature has increased 8× since the Claude-powered pipeline went live.
Supplement formulations can use blood biomarker data alongside DNA and dietary information, giving GenoPalate a more complete picture of the member’s biology.
Members can upload their lab report, have the required biomarkers extracted, and use those results as part of their personalized supplement formulation.
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