Enabling AI to assist user complete the legacy data standardisation process

Enabling AI to assist user complete the legacy data standardisation process

Enabling AI to assist user complete the legacy data standardisation process

Enabling AI to assist user complete the legacy data standardisation process

Enabling AI to assist user complete the legacy data standardisation process

Designing an AI-driven API Connector Builder for Innovaccer's Data Platform - Gravity

My Role

Sr. Product Designer - Product Strategy, User Flows, Prototyping, Visual Design

Team

Avinash Gatreddy (PM)
Risav C. (EM)
Aakash Srivastava, Shivam D. (Devs)

Overview

At Innovaccer, raw data ingestion is only the first step.

The real value is unlocked through Data Standardisation, the process of transforming disparate formats into a unified data model that powers 10+ downstream analytics, quality & population health apps.

It's the backbone of the analytics ecosystem, ensuring every app operates on consistent & reliable data.

About Innovaccer

HealthTech | Indian Unicorn 🦄 | Last round raised: Series F

Every healthcare organization wants to deliver personalized care at lower costs. This is difficult to do with so much information scattered across different systems.

That’s where Innovaccer comes in, which works with healthcare org. - like CommonSpirit Health, Kaiser Permanente etc., to supercharge their existing software with true intelligence. Innovaccer activate the power of their data to create connected, digital experiences across the continum of care.

About the problem

Raw healthcare data is inconsistent by design. Different source systems comes with varying schema structures, clinical concepts & customised standards, which increases duplications

Without standardisation, metrics varied across applications & clinical definitions broke across data workflows due to which every downstream app team had to rebuild transformation logic independently

The challenge wasn’t simply mapping fields rather it was creating a scalable system that:

  • Harmonizes multi-source healthcare data into a unified model

  • Preserves traceability from raw to standardized layers

  • Powers multiple applications without redefining logic repeatedly

Thus, Data Standardisation became the invisible infrastructure that ensured analytical consistency across the entire product ecosystem.

Our Objectives

Our Objectives

1

HMW unify fragmented healthcare data into a scalable, interoperable model?

1

HMW unify fragmented healthcare data into a scalable, interoperable model?

1

HMW unify fragmented healthcare data into a scalable, interoperable model?

1

HMW unify fragmented healthcare data into a scalable, interoperable model?

1

HMW unify fragmented healthcare data into a scalable, interoperable model?

2

HMW ensure transparency and traceability across transformation layers?

2

HMW ensure transparency and traceability across transformation layers?

2

HMW ensure transparency and traceability across transformation layers?

2

HMW ensure transparency and traceability across transformation layers?

2

HMW ensure transparency and traceability across transformation layers?

3

HMW make sure that the current legacy process doesn't break while introducing new intelligence?

3

HMW make sure that the current legacy process doesn't break while introducing new intelligence?

3

HMW make sure that the current legacy process doesn't break while introducing new intelligence?

3

HMW make sure that the current legacy process doesn't break while introducing new intelligence?

3

HMW make sure that the current legacy process doesn't break while introducing new intelligence?

Impact & accomplishments

Impact & accomplishments

Reducing the Support Ticket count by 65%

that took 2-3 months time over email threads to get resolved

Increased Avg. Process Completion Rate by 50%

within 3 months of release

Intrigued? Want to see more…?

Since this project is covered under NDA, please reach out to me personally if you have any questions regarding my work.

©KartikeyShandilyaPortfolio

©KartikeyShandilyaPortfolio

©KartikeyShandilyaPortfolio

©KartikeyShandilyaPortfolio

©KartikeyShandilyaPortfolio

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