Vaibhav

Vaibhav

Jul 30

Straight-Through Processing Is a Confidence Problem, Not an Automation One

#architecture #automation #ai #insurtech

2 min read

Vaibhav

Jul 30

Model Risk Management for ML: Reproducibility and Lineage Are the Whole Game

#mlops #machinelearning #compliance #insurtech

3 min read

Vaibhav

Jul 30

Data Labeling Is the ML Work Nobody Budgets For (And Why Projects Stall Without It)

#machinelearning #mlops #ai #insurtech

3 min read

Vaibhav

Jul 29

Stop Baking Domain Knowledge Into Your Model's Weights. Retrieve It.

#rag #ai #llm #insurtech

2 min read

Vaibhav

Jul 29

Synthetic Data for ML: Genuinely Useful, and Quietly Dangerous

#machinelearning #ai #dataengineering #insurtech

2 min read

Vaibhav

Jul 29

How Do You Test AI That Never Gives the Same Answer Twice?

#testing #ai #llm #insurtech

3 min read

Vaibhav

Jul 28

One Giant LLM Won't Run Your Business. A Team of Narrow Agents Might.

#ai #agents #architecture #insurtech

1

2 min read

Vaibhav

Jul 28

Data Observability: Catching the Silent Break Before It Reaches Production

#dataengineering #observability #dataquality #insurtech

2 min read

Vaibhav

Jul 28

Data Contracts: Ending the "Someone Changed a Field Upstream" Outage

#dataengineering #dataquality #python #insurtech

2 min read

Vaibhav

Jul 28

Knowledge Graphs Beyond Fraud: The Substrate Insurance AI Actually Needs

#database #ai #dataengineering #insurtech

3 min read

Vaibhav

Jul 28

Prompt Injection Is a Claims Problem: Securing AI That Reads Documents You Don't Control

#ai #security #llm #insurtech

3 min read

Vaibhav

Jul 25

Model Monitoring in Production: Catching Drift Before It Hits the Bottom Line

#mlops #machinelearning #monitoring #insurtech

2 min read

Vaibhav

Jul 25

Geocoding to the Postcode Centroid Is Silently Costing You (A Data Problem)

#geospatial #dataengineering #gis #insurtech

1

2 min read

Vaibhav

Jul 25

Your Fraud Model Raises a Flag. The Expensive Part Is Everything After.

#machinelearning #dataengineering #insurtech #fraud

2 min read

Vaibhav

Jul 25

Feature Stores and Point-in-Time Correctness: The Bug That Silently Ruins ML Models

#mlops #machinelearning #dataengineering #insurtech

2 min read

Vaibhav

Jul 25

Do You Actually Need a Vector Database? A Reality Check Before You Add One

#rag #database #ai #insurtech

1

2 min read

Vaibhav

Jul 24

Telematics and IoT: You Collected Billions of Data Points to Make One Decision

#iot #dataengineering #insurtech #ai

2 min read

Vaibhav

Jul 24

Data Lineage for Insurance ML: You Capture It While Data Flows, or Not at All

#dataengineering #mlops #insurtech #compliance

3 min read

Vaibhav

Jul 24

RAG Over Insurance Policy Documents: What Works and What Quietly Breaks

#rag #ai #insurtech #dataengineering

3 min read

Vaibhav

Jul 21

Embedded Products: Why the API Is the Easy Part

#api #architecture #dataengineering #webdev

3 min read

Vaibhav

Jul 21

Your Data Warehouse Didn't Fix Anything (And Why That's Not a Failure)

#dataengineering #architecture #database #datascience

3 min read

Vaibhav

Jul 21

The Math That Explains Why Your Automation Rate Is Stuck at 35%

#architecture #dataengineering #automation #programming

3 min read

Vaibhav

Jul 21

Entity Resolution: Why "Show Me Everything About This Customer" Is So Hard

#dataengineering #database #architecture #ai

3 min read

Vaibhav

Jul 21

Building a Document Intelligence Pipeline (Or: 80% of Your Data Is in PDFs)

#dataengineering #ai #python #architecture

3 min read

Vaibhav

Jul 18

Why Fraud Rings Are a Graph Problem (And Your SQL Database Can't See Them)

#database #dataengineering #security #insurtech

4 min read

Vaibhav

Jul 17

Snowflake or Databricks? An Honest Comparison (From 200+ Migrations)

#snowflake #databricks #dataengineering #architecture

1

3 min read

Vaibhav

Jul 17

Real-Time vs Batch: Which Insurance Data Actually Needs to Be Live

#dataengineering #architecture #streaming #insurtech

3 min read

Vaibhav

Jul 17

Why Your Insurance Chatbot Failed (And What AI Agents Do Differently)

#ai #insurtech #chatbot #dataengineering

4 min read

Vaibhav

Jul 16

Deepfakes Broke Insurance Fraud Detection — And the Fix Isn't a Better Image Detector

#insurtech #ai #security #dataengineering

3 min read

Vaibhav

Jul 15

The 2026 Insurtech Data Stack: A Reference Architecture

#insurtech #dataengineering #architecture #ai

3 min read

Vaibhav

Jul 15

The NAIC Model Bulletin and the EU AI Act, Explained for Data and Engineering Teams

#insurtech #ai #compliance #dataengineering

3 min read

Vaibhav

Jul 14

Why 80% of Insurance AI Projects Stall — And It's Not the Model

#insurtech #ai #dataengineering #data

3 min read

Vaibhav

Jul 14

Building an AI Claims-Adjuster Agent: Architecture, Guardrails, and the Data It Actually Needs

#insurtech #ai #dataengineering #machinelearning

4 min read

DEV Community

Badges

Writing Debut

Straight-Through Processing Is a Confidence Problem, Not an Automation One

Model Risk Management for ML: Reproducibility and Lineage Are the Whole Game

Data Labeling Is the ML Work Nobody Budgets For (And Why Projects Stall Without It)

Stop Baking Domain Knowledge Into Your Model's Weights. Retrieve It.

Synthetic Data for ML: Genuinely Useful, and Quietly Dangerous

How Do You Test AI That Never Gives the Same Answer Twice?

One Giant LLM Won't Run Your Business. A Team of Narrow Agents Might.

Data Observability: Catching the Silent Break Before It Reaches Production

Data Contracts: Ending the "Someone Changed a Field Upstream" Outage

Knowledge Graphs Beyond Fraud: The Substrate Insurance AI Actually Needs

Prompt Injection Is a Claims Problem: Securing AI That Reads Documents You Don't Control

Model Monitoring in Production: Catching Drift Before It Hits the Bottom Line

Geocoding to the Postcode Centroid Is Silently Costing You (A Data Problem)

Your Fraud Model Raises a Flag. The Expensive Part Is Everything After.

Feature Stores and Point-in-Time Correctness: The Bug That Silently Ruins ML Models

Do You Actually Need a Vector Database? A Reality Check Before You Add One

Telematics and IoT: You Collected Billions of Data Points to Make One Decision

Data Lineage for Insurance ML: You Capture It While Data Flows, or Not at All

RAG Over Insurance Policy Documents: What Works and What Quietly Breaks

Embedded Products: Why the API Is the Easy Part

Your Data Warehouse Didn't Fix Anything (And Why That's Not a Failure)

The Math That Explains Why Your Automation Rate Is Stuck at 35%

Entity Resolution: Why "Show Me Everything About This Customer" Is So Hard

Building a Document Intelligence Pipeline (Or: 80% of Your Data Is in PDFs)

Why Fraud Rings Are a Graph Problem (And Your SQL Database Can't See Them)

Snowflake or Databricks? An Honest Comparison (From 200+ Migrations)

Real-Time vs Batch: Which Insurance Data Actually Needs to Be Live

Why Your Insurance Chatbot Failed (And What AI Agents Do Differently)

Deepfakes Broke Insurance Fraud Detection — And the Fix Isn't a Better Image Detector

The 2026 Insurtech Data Stack: A Reference Architecture

The NAIC Model Bulletin and the EU AI Act, Explained for Data and Engineering Teams

Why 80% of Insurance AI Projects Stall — And It's Not the Model

Building an AI Claims-Adjuster Agent: Architecture, Guardrails, and the Data It Actually Needs