Associate Architect · Applied AI

Production AI systems
for complex,
real-world problems.

I work the full path from ambiguous problem to production: understanding the problem, designing the system, building it, deploying it, and iterating once people are using it.

Siddharth Deshpande

12+

years shipping

3

client engagements in parallel

5

production AI systems shipped

300+

US facilities live

30%

cloud spend reduced

What I Build

Four kinds of problem
keep landing on my desk.

Enterprise AI

People who need an answer cannot get it, because the answer lives behind SQL, five admin screens, or someone else’s calendar.

Production RAG, GraphRAG, agent orchestration, and LLM applications that run against live business data.

Multi-Agent Conversational AI

Data & Knowledge Systems

The knowledge exists, but it is spread across thousands of unstructured documents with no schema and no shared vocabulary.

Large-scale document processing, entity and relationship extraction, graph-based retrieval, and vector search.

GraphRAG Knowledge Engine

Production Systems

A system the whole company runs on, all day, where an hour of downtime means shipments stop.

Cloud architecture, distributed systems, APIs, data pipelines, and the observability to know when they degrade.

Secure Logistics ERP

Secure AI

An AI system that can read the database can read the wrong tenant’s data. The access model has to be part of the design.

Permission-aware generation, post-generation query rewriting, read-only validation, and enterprise access control.

Permission rewrite on generated SQL

Case Studies

Systems I took from
problem to production.

Enterprise AI

Multi-Agent Conversational AI

Ask a building a question in plain English — five specialist agents over a 4 TB operations database, instead of five admin screens.

Problem
4 TB database with no usable natural-language interface
Hardest constraint
Generated SQL runs against live production data, so read-only validation and post-generation permission rewrite are non-negotiable
Approach
Supervisor agent routes to 5 specialized agents — never answers itself

Key decision Supervisor pattern, not a single monolithic agent

Data & Knowledge Systems

GraphRAG Knowledge Engine

Turning 20K unstructured support tickets into an answerable knowledge base.

Problem
Recurring tickets solved from scratch every time
Hardest constraint
No usable schema: free-text tickets with author-dependent vocabulary for the same concepts
Approach
Two-stage ingest pipeline with graph extraction

Key decision Two-stage pipeline: seconds-to-searchable, minutes-to-graph-enriched

Production Systems

Cloud Cost Intelligence Agent

Finding out why the cloud bill moved — every night, before anyone has to ask. Identified 30% savings across the Azure estate.

Problem
Cloud spend growing unchecked month over month
Hardest constraint
Attribution has to be defensible: a wrong cost claim sends an engineer down a multi-day dead end
Approach
19 collectors across 3 dependency phases — six Azure APIs, SQL DMVs, and the app database

Key decision Deterministic answers first, LLM only where reasoning is required

All case studies

Experience

Where I've made an impact

Apra Labs

Associate Architect · previously Senior Software Engineer

Aug 2019 – Present

Built the AI and data platform layer for a unified facility management product serving 300+ US facilities.

  • Virtual Credentials — facility entry/exit across 300+ US buildings
  • Reporting platform — 1000s of reports per hour across 300+ tenants
  • Analytics platform from scratch — facility operations monitoring
300+ facilities served
30% cloud costs reduced
10→55 team growth
4 more, and the leadership work

MildlyClassic

Engineering Team Lead

May 2016 – May 2019

Built and scaled a mission-critical logistics ERP from scratch to 2,500 daily users handling 70K dockets/month.

  • End-to-end ERP — Finance, Ops, Booking, Hub Management, CRM, Route Planning for PAN India secure logistics
  • Clients: large jewellery manufacturers shipping daily from manufacturing to retail
  • Bulk docket creation via upload, 70K dockets/month
70K dockets/month
2.5K daily users
7 engineers hired
2 more, and the leadership work

UXgage

Co-Founder & CTO

Oct 2015 – Apr 2016

Took an idea from zero to a shipped product in 6 months — won a ₹5L cash prize from Sandbox Startups, with office space and Azure infrastructure granted separately.

  • Core product architecture — PHP, Neo4j, Cassandra
  • JS instrumentation engine capturing user interactions and behavioral data
  • Data pipeline for large-volume user interaction storage
0→1 product shipped
₹5L cash prize won
View More
Full work history

Open Source

Code other people run in production

All open source

Get in Touch

Let's build
something great.