Live at lexify.health · No login required
From Policy to Proof — within minutes.
Lexify translates any medical or clinical policy document into 7 production-ready outputs — SQL, logic specifications, test cases, QC reports, Python code, structured policy metadata, and a plain-language narrative summary — automatically.
Minutes
vs. 4–16 hrs manually
7
Output types generated
8
SQL dialects supported
4–16 hrs
Saved per policy
1st Place — 2026 HeatMap Hackathon
Emmanuel Fle Chea, founder of Lexify, won first place as Team 13 lead out of 19 teams and 90+ participants at the HeatMap Hackathon hosted by BData and the American Burn Association at the University of Minnesota — March 2026.
The Problem
Clinical policy translation is broken.
Every health system, prior authorization company, and clinical AI platform faces the same bottleneck: turning a policy document into executable SQL requires a skilled clinical data scientist working manually for hours or days.
Time per policy
4–16 hrs
A single medical policy — with its criteria, time windows, unit conversions, and exclusion logic — takes a senior clinical data scientist 4 to 16 hours to translate manually into production SQL.
Annual cost per health system
$500K–$2M
Health systems have 100–500+ active clinical policies. At $120,000–$160,000 per clinical data scientist, a significant portion of every salary is spent on repetitive manual translation.
Prior auth requests annually
35 million
Prior authorization volume in the US is growing. Every coverage decision is driven by clinical policy logic that must be operationalized in SQL — and updated every time policy changes.
Cost of a consultant
$200–$400/hr
Outsourcing clinical SQL to consultants is expensive, non-repeatable, and produces no standardized audit trail. Every engagement reinvents the same work.
The 6 manual steps that Lexify eliminates
01Read and interpret the clinical policy — understanding ICD-10 codes, LOINC lab thresholds, temporal windows, and exclusion criteria buried in dense policy language.
02Extract the measurable logic — identifying every threshold, time window, unit, and edge case that must be captured in code.
03Map to the target data schema — translating abstract clinical concepts to actual table names, column names, and concept IDs in your EHR or data warehouse.
04Write production SQL — implementing every rule, handling null values, unit conversions, deduplication, and temporal windows correctly.
05Document every assumption — creating a human-readable specification that clinical reviewers and compliance auditors can trace back to the source policy.
06Build test cases — covering normal scenarios, boundary conditions, null values, exclusion criteria, unit conversions, and temporal edge cases.
The Solution
One input. Seven production-ready outputs.
Paste or upload any clinical policy — including PDFs and Word documents with embedded tables, charts, and flowcharts. Select your SQL dialect. Lexify generates a complete, auditable clinical intelligence package within minutes.
SQL Output
Production-ready SQL with inline audit comments explaining every threshold, unit conversion, and exclusion criterion.
Logic Spec
Complete human-readable specification of every extracted clinical criterion — citable for compliance audits and peer review.
Test Cases
Automated test suite covering normal cases, boundary values, nulls, exclusion criteria, and temporal edge cases.
QC Report
Pass/warn/fail badges for null handling, unit normalization, temporal logic, exclusion logic, and overall complexity.
Python Wrapper
Dialect-aware pandas/SQLAlchemy execution class for teams building Python-based clinical data pipelines.
Policy Metadata
Structured JSON extraction of every non-SQL rule — documentation requirements, facility requirements, step therapy, non-covered indications, and coverage restrictions.
Narrative Summary
Plain-language summary of what the policy covers, who it applies to, and its key effective dates — ready to share with stakeholders.
How It Works
Three steps. Within minutes.
STEP 01
Paste or Upload
Paste policy text directly or upload a PDF or Word document — including documents with embedded tables, charts, decision trees, and flowcharts.
→
STEP 02
Select Dialect
Choose your SQL environment from 8 supported dialects. Configure table and column names to match your data schema.
→
STEP 03
Generate & Download
Click Generate. All 7 outputs appear sequentially in real time. Download the complete package as a ZIP — ready for review and deployment.
SQL Dialect Support
One policy. Any SQL environment.
Lexify generates dialect-correct SQL for every major healthcare data platform — not generic SQL that you then have to adapt. The right functions, syntax, and schema patterns for your environment, automatically.
OMOP CDM
Observational research · Academic medical centers
Epic Clarity
SQL Server · Most widely deployed US EHR
Snowflake
Leading cloud data warehouse for healthcare
Google BigQuery
Cloud analytics · Standard SQL
Databricks SQL
Spark SQL · Large health systems and pharma
Microsoft SQL Server
T-SQL · Health system data warehouses
PostgreSQL
Open source · Health tech startups
Oracle Health
Cerner Millennium · Oracle SQL
Before & After
What changes when you use Lexify.
WITHOUT LEXIFY
4–16 hours of manual SQL writing per policy
Inconsistent implementations across data scientists
No standardized audit trail or logic documentation
Test cases written ad hoc or skipped entirely
Every policy update requires starting over from scratch
Visual content — tables, charts, flowcharts — missed entirely
Different SQL for each EHR environment requires separate rewrites
WITH LEXIFY
7-output clinical intelligence package generated within minutes
Deterministic, reproducible outputs every time
Logic spec and QC report generated automatically
Comprehensive test suite covering all edge cases
Policy updates regenerated within minutes, not hours
Tables, charts, and flowcharts read and translated by AI vision
8 SQL dialects — one input, any environment
Structured policy metadata — documentation, facility, and step therapy rules extracted automatically
Plain-language narrative summary ready for stakeholder briefings
Who It's For
Built for the people doing this work.
Lexify is designed for the clinical data professionals who translate policy into code every day — not as a replacement for their expertise, but as infrastructure that eliminates the manual burden.
Health Systems
Clinical data science teams at hospitals and health systems implementing quality measures, care gap rules, and clinical decision support logic across OMOP CDM and Epic Clarity environments.
Prior Authorization Platforms
Clinical AI companies and prior auth technology platforms operationalizing payer coverage criteria into automated decision logic — at scale, across thousands of policies.
Clinical AI Companies
Health tech startups and clinical AI platforms embedding validated clinical logic into their products — needing production SQL that is auditable, dialect-correct, and testable.
Market Opportunity
A large, underserved market.
Total Addressable Market
$4.2B
Clinical data engineering services market — health systems, prior auth companies, CROs, pharma, and health tech.
Serviceable Market
$800M
Organizations actively building SQL-based clinical pipelines with data teams that translate policy to code today.
Year 3 Target
$8M ARR
200 paying clients at an average of $3,300/month — a realistic target given the size and distribution of the market.
The Founder
Built by someone who lived the problem.
EC
Emmanuel Fle Chea
Founder & CEO — Lexify Health · Minneapolis, MN
Emmanuel is a clinical data scientist with 7+ years of hands-on experience building healthcare data pipelines, automated QC systems, and clinical AI tools across health system EHR environments, claims databases, and research datasets. He holds a Master of Public Health in Public Health Data Science from the University of Minnesota School of Public Health and a Bachelor of Arts in Physics, with minor in Mathematics from Wells College, New York.
Lexify was built from direct, sustained experience doing the work it automates. Over the course of his career, Emmanuel has personally translated dozens of complex clinical policies into production SQL — implementing KDIGO AKI criteria, Sepsis-3 logic, HbA1c monitoring rules, and quality measures across multiple SQL environments and data schemas. He has built QC frameworks, written test suites, and created audit documentation for clinical pipelines serving millions of patient records.
That depth of hands-on experience is embedded in every output Lexify generates — the clinical thresholds, the unit conversions, the temporal logic, the exclusion criteria, and the QC checks that generic AI tools consistently miss. Lexify is not a general-purpose code generator. It is a domain-specific tool built by a practitioner who understands why clinical SQL fails in production and what it takes to get it right.
Lexify was built from direct, sustained experience doing the work it automates. Over the course of his career, Emmanuel has personally translated dozens of complex clinical policies into production SQL — implementing KDIGO AKI criteria, Sepsis-3 logic, HbA1c monitoring rules, and quality measures across multiple SQL environments and data schemas. He has built QC frameworks, written test suites, and created audit documentation for clinical pipelines serving millions of patient records.
That depth of hands-on experience is embedded in every output Lexify generates — the clinical thresholds, the unit conversions, the temporal logic, the exclusion criteria, and the QC checks that generic AI tools consistently miss. Lexify is not a general-purpose code generator. It is a domain-specific tool built by a practitioner who understands why clinical SQL fails in production and what it takes to get it right.
MPH — Public Health Data Science, UMN
7+ Years Clinical Data Science
EHR Data Engineering
Claims Analytics
Clinical AI
Published Researcher
HeatMap Hackathon Winner 2026
Start translating policies today.
Lexify is live and free to use. No login required. No credit card. Paste a policy and see a complete, production-ready clinical package within minutes.