Abhuday Mishra

I build the data pipelines and RAG systems behind climate-risk tools for power utilities. The kind that have to keep working for 100+ tenants, long after the demo is over.

I'm a backend engineer at AiDash in Gurgaon, working between distributed systems and AI infrastructure. I also write about what breaks when AI systems meet production.

§1 Selected work

CRIS 2.0 a climate-risk ingestion pipeline

CRIS shows power utilities where wildfire and weather risk is highest on their network. This is the service that feeds it. I have worked on CRIS since its inception and owned its backend architecture as it grew from 1 to 50+ enterprise tenants.

  1. schedule
  2. detect
  3. plan
  4. ingest
  5. summarise
  6. complete
Fig. 1. Each stage hands off to the next through a queue, so no stage waits on another.
Read the case study →
Tenants
1 → 50+
Throughput
320k+ records / hour
New tenant
Configuration only, no code changes
Built with
Java 21, Spring Boot, RabbitMQ, PostgreSQL

WMP Copilot multi-tenant RAG on AWS Bedrock

A RAG pipeline that lets utility companies ask questions of their own wildfire mitigation plans. I designed and deployed it for 100+ tenants, across a Java and Python microservices architecture.

  1. documents
  2. chunk
  3. embed
  4. retrieve
  5. answer
Fig. 2. The first three stages run once per document. The last two run on every question.
Read the case study →
Tenants
100+
Cost
$0.019 / query
Cold start
< 2 s on 128 MB pods
First evaluation
Retrieval 3.06 / 5, generation 3.77 / 5
2023 – 2025Serverless data archivalRDS storage: 400 GB → 3 GB
2023 – 2025Multi-tenant ingestion on LambdaVolume: 300k+ records / 6 hours
All work →

§2 Writing

§3 Record

Apr 2025 – nowSoftware Engineer 2, AiDASH
Jul 2023 – Mar 2025Software Engineer 1, AiDASH
Nov 2022 – Jun 2023Software Engineer Intern, AiDASH
Jun 2019 – May 2023B.Tech, Computer Science and Engineering, SRM Institute of Science and Technology, ChennaiGPA 9.17

Day to day: Java and Spring Boot, Python and FastAPI, on AWS (Lambda, SQS, S3, EKS, Fargate, Bedrock). PostgreSQL, Cassandra, Redis and DynamoDB underneath.