Case Studies Book a 30-minute discovery call
SamaCare product interface
Our work / Staff Augmentation

A sixty five percent drop in manual effort per PA submission

Resourcifi embedded a dedicated pod of one full stack developer and two data engineers to deliver prior authorization automation, NPS reporting, and LLM tooling across SamaCare.

65% Less effort per PA submission
Stanford DOW Snak King Narda Proximity Learning Nextgen Living University of Guelph Lenze iAutomation Emory University IKEA
600+ projects 95% repeat clients 4.9 on Clutch
Industry
Healthcare, AI Prior Authorization
Engagement
Dedicated engineering pod
Platform
Snowflake, Airflow, dbt, Superset, DataHub, Pendo
Services delivered
8 workstreams
Timeline
Oct 2025 to Ongoing, about 7 months
The challenge

What SamaCare needed to solve.

SamaCare delivers AI native intelligence for specialty practice workflows in medical prior authorization, working with one of the largest real world data sets in the space. The platform needed deeper data engineering and full stack support to scale prior authorization automation, NPS reporting, and LLM tooling. Manual PA submissions, an unmaintained dbt data dictionary, and inaccessible NPS data were slowing the team down.

Goals
  • Cut the manual effort spent on each prior authorization submission
  • Make NPS reporting data queryable for the SEO and CS teams
  • Automate dbt data dictionary maintenance with LLM tooling
  • Improve the AI prior authorization engine and fix false positive analysis
The solution

A three engineer pod built prior authorization automation, an NPS reporting pipeline, and an LLM driven data dictionary while hardening the SamaCare AI engine and web app.

How we worked

How the embedded team delivered.

01

NPS reporting pipeline

Built a Pendo to Snowflake to Superset pipeline for the SEO and CS teams.

02

Fathom ingestion

Loaded Fathom AI meeting notes into Snowflake via an Airflow DAG.

03

LLM data dictionary

Built an LLM wrapper to auto maintain the dbt data dictionary with DataHub integration.

04

AI engine fixes

Repaired AI prior authorization engine data, denial response fields, the gender value bug, and false positive analysis.

05

PA automation

Built and maintained Python Playwright automation for submitting prior authorizations across payer portals.

SamaCare case study
The results

Measurable workflow gains across data engineering and full stack

Sprint velocity, story point growth across sprintsStory point velocity for the data engineering and full stack pod climbed from 22 points in sprint one to 46 points by sprint twelve, tracked in Jira.
22 pointsS1
25 pointsS2
27 pointsS3
32 pointsS5
37 pointsS8
43 pointsS10
46 pointsS12
Outcomes

The numbers the work moved.

65%
Less effort per PA submission
3.6%
False-positive rate identified
3
Dedicated engineers
7mo
Embedded engagement

Across an ongoing engagement that began in October 2025, a three engineer pod cut PA submission effort by 65 percent, made NPS data queryable, and automated data dictionary maintenance with LLM driven PR generation.

The stack

The tools behind the work.

Data engineering

Snowflake, dbt, Airflow

Warehouse, transforms, and orchestration powering NPS reporting and the data dictionary

Full stack

React, Node.js, GraphQL, PostgreSQL

SamaCare web app frontend and backend changes for PA workflows

Automation and QA

Playwright, Python, TypeScript

Prior authorization portal automation, form filling, and test coverage

Analytics and metadata

Superset, DataHub, Pendo

Dashboards, data cataloging, and product analytics ingestion

Related case studies
Ready when you are

Book a Staff Augmentation roadmap call to scope a dedicated engineering pod.