Aaditya Hammad | AI Builder | AI Deploy Network

About Aaditya

Ai Software Developer with expertise in Java, Spring Boot, and React, with hands-on experience building AIpowered applications using Python, Agentic RAG, LangGraph, Neo4j, pgvector, and Gemini LLMs. Experienced in developing scalable REST APIs, repository-aware AI systems, JWT Authentication, Docker, and CI/CD.

Strong foundation in DSA, OOPs, DBMS, and AI-driven software engineering.

Professional profile

Location: Bangalore, India
Time zone: Asia/Calcutta
Availability: Available Now

Proven on the network

Implementation records and publicly available work, where published.

1 AI Deployment delivered, including 1 publicly identified implementation available to inspect.

Reported business outcomes

Hours Automated250 hours
period not specified
Automated 250 hours (period not specified)

Builder-reported outcomes, recorded on deployment and case study records that AI Deploy Network reviewed before publication. AI Deploy Network does not currently capture a measurement basis or calculation methodology for reported outcomes, so none is shown.

What Aaditya builds

Implementation domains listed on this profile. Evidence-supported items are identified separately below.

Specialisations

AI Agents

AI Infrastructure & Platforms

Autonomous Agents

Knowledge Assistants

Multi-Agent Systems

Builder-listed deployment types

AI Agent
Business Intelligence
Data Enrichment
Document Processing
Employee Self-Service
Onboarding Assistant
Question Answering
RAG System
Semantic Search
Task Automation

Show all deployment types

Semantic Search
Task Automation

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

[AI Legacy Bridge] — AI-Powered Legacy Code Intelligence Platform

Legacy codebases are hard to onboard onto — new developers spend weeks manually tracing thousands of lines of undocumented code just to understand how things work. AI Legacy Bridge solves this by letting developers analyze, visualize, and query unfam

250 hours automated / per week

Software & SaaS · AI Agent · Business Intelligence · Data Enrichment · Document Processing · Employee Self-Service · Onboarding Assistant · Question Answering · RAG System · Semantic Search · Task Automation

View Deployment

Implementation capabilities

Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.

Evidence-supported

AI Agent1 record
Business Intelligence1 record
Data Enrichment1 record
Document Processing1 record
Employee Self-Service1 record
Onboarding Assistant1 record
Question Answering1 record
RAG System1 record
Semantic Search1 record
Task Automation1 record

Show all evidence-supported capabilities

Question Answering 1 record
RAG System 1 record
Semantic Search 1 record
Task Automation 1 record

Builder declared

AI Agents
AI Infrastructure & Platforms
Autonomous Agents
Knowledge Assistants
Multi-Agent Systems

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

Atomic Agents1 record
FastAPI1 record
Java1 record
JavaScript1 record
LangChain1 record
LangGraph1 record
PostgreSQL1 record
Python1 record
React1 record
Spring Boot1 record
pgvector1 record

Builder declared

Agent Skills
Angular
BGE Embeddings
Chroma
Gemini 3.1 Flash-Lite
Gemini Embedding 2
Gemini Fine-tuning
GitHub Actions
Inngest
Jenkins
LiteLLM
MySQL
Ollama
Playwright
Postman
Pydantic AI
Ragie
Selenium
pytest

Industry experience

Published Deployments support the listed counts. Other industries are Builder declared.

Software & SaaS

1 published Deployment

IT Services & Systems Integration

Builder declared

Trust & verification

A closer look at how this profile and its evidence are reviewed.

Community Member

Published evidence is reviewed against the AI Deploy Network Evidence Standard.

How verification works

Community

Verified Builder

Independently reviewed by AI Deploy Labs against the platform Evidence Standard.

How this is verifiedWhat the platform has established, and what remains builder-declared.

Identity and organisation: Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
AI Deployments: An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
Business outcomes: Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
Evidence: Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
Currency: Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
Traceability: Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.

The platform does not independently audit client systems or financial records. How this is verified

Ready to discuss your AI implementation?

Tell Aaditya Hammad what you are trying to automate and the outcome you need. Your message goes directly to the builder, with a copy kept in your Organisation Workspace.