AI Deploy Network
Shivam Verma

AI Deploy Network / Builder

Shivam Verma

AI Engineer | Agentic AI, RAG, Voice AI & Generative AI

IndiaYamunanagarSeniorAvailable Now

Published evidence

3 AI Deployments

3 publicly identified

01

About Shivam

AI Engineer and Full Stack Developer with 3+ years of experience building and deploying production AI systems across agentic AI, RAG, voice AI, and generative AI.

Currently, I work as an AI Engineer at Panj Solutions, where I build and operate production AI Chat, Call, and SMS Agents across four US-market platforms. My work includes LangGraph-based agent orchestration, RAG, LLM tool calling, intent detection, workflow automation, voice interactions, and human-agent handoff.

Read more

Previously at Valuefy Solutions, I architected the Valuefy Data Copilot using LangGraph and LangChain, enabling users to interact with live wealth-management data through natural language and reducing dependency on the data team by approximately 90% for supported workflows.

I am also the founder and primary engineer behind BhaShaVox, a production multilingual AI platform covering translation, speech AI, voice cloning, and audio/video localisation across 125+ languages.

My focus is on taking AI from prototypes to production systems with real integrations, workflows, infrastructure, and measurable business outcomes.

Professional profile

Location
Yamunanagar, India
Time zone
Asia/Calcutta
Work mode
Hybrid, Remote
Availability
Available Now
AI experience
3+ years
Industry experience
3+ years
Languages
English, Hindi
Working hours
Flexible
Typical response
Within 24 hours
Travel
Occasional travel

02

Proven on the network

Implementation records and publicly available work, where published.

3 AI Deployments delivered, including 3 publicly identified implementations available to inspect.

03

What Shivam builds

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

Specialisations

AI Agents

AI Infrastructure

Multi-Agent Systems

RAG Systems

Voice AI

Builder-listed deployment types

  • AI Agent
  • Customer Support Agent
  • Document Processing
  • Internal Business Automation
  • Personalization Engine
  • RAG System
  • Sales Agent
  • Workflow Automation

04

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

BhaShaVox — Multilingual AI Translation, Voice & Video Platform

Built and deployed a multilingual AI platform for translation, voice generation, voice cloning, dubbing, subtitles and audio/video localization across 125+ languages.

Media & Entertainment · AI Agent · Document Processing · Personalization Engine · Workflow Automation

View Deployment
02 / AI DeploymentPublished record

Valuefy Data Copilot

Built a multi-tenant AI Data Copilot using LangGraph, LangChain and RAG, enabling users to query live portfolio, transaction, holdings and client data through natural language.

FinTech · AI Agent · Internal Business Automation · RAG System · Workflow Automation

View Deployment
03 / AI DeploymentPublished record

Production AI Chat, Call & SMS Agents

Built and deployed production AI Chat, Call, and SMS Agents across four US-market platforms for lead qualification, inventory collection, customer information management, booking workflows, and human-agent handoff.

Software & SaaS · AI Agent · Customer Support Agent · Sales Agent · Workflow Automation

View Deployment

05

Implementation capabilities

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

Evidence-supported

  • AI Agent3 records
  • Customer Support Agent1 record
  • Document Processing1 record
  • Internal Business Automation1 record
  • Personalization Engine1 record
  • RAG System1 record
Show all evidence-supported capabilities
  • Sales Agent 1 record
  • Workflow Automation 3 records

Builder declared

  • AI Agents
  • AI Infrastructure
  • Multi-Agent Systems
  • RAG Systems
  • Voice AI

06

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

  • Docker1 record
  • FastAPI3 records
  • Gemini 3.1 Flash-Lite2 records
  • LangChain2 records
  • LangGraph2 records
  • MongoDB2 records
  • Next.js1 record
  • Node.js2 records
  • OpenAI GPT3 records
  • OpenAI Whisper1 record
  • Pinecone1 record
  • Plivo1 record
  • Python3 records
  • Ragie2 records
  • Redis2 records

Builder declared

  • Claude Fable 5.1
  • LiteLLM
  • Model Context Protocol
  • OpenAI Agents SDK
  • PostgreSQL
  • pgvector

07

Industry experience

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

FinTech

1 published Deployment

Media & Entertainment

1 published Deployment

Software & SaaS

1 published Deployment

Banking

Builder declared

Telecommunications

Builder declared

08

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

Professional record and further evidence

Client Portfolio

Diverse industry experience
  • Panj Solutions Pvt. Ltd.

    ai • Software & SaaS

    United States2026

    Built and deployed production AI Chat, Call, and SMS Agents across four US-market platforms. Implemented LangGraph-based agent orchestration, RAG, LLM tool calling, intent detection, workflow automation, AI voice interactions, and human-agent handoff for lead qualification, inventory collection, customer information management, and lead-booking workflows.

    1 AI Deployment
  • Valuefy Solutions

    AI Engineering / Generative AI / RAG • FinTech

    India2024

    Architected the Valuefy Data Copilot using LangGraph and LangChain, enabling relationship managers, operations teams, and users to query live portfolio, transaction, holdings, and client data through natural language. The multi-tenant AI system reduced dependency on the data team by approximately 90% for supported workflows and was deployed across 100+ live tenants.

    1 AI Deployment
  • MountBlue Technologies

    Software Development • IT Services & Systems Integration

    India2023

    Worked as a Java Software Engineering Intern, contributing to application development, debugging, testing, and deployment workflows. Gained hands-on experience with backend development, APIs, databases, and software engineering practices while working in a professional product-development environment.

Professional Certifications

Well credentialed
  • Model Context Protocol (MCP) – Introduction

    Anthropic Academy

    Verified Credential

    Issued Jul 2026

  • Introduction to Model Context Protocol

    Anthropic Academy

    Verified Credential

    Issued Jul 2026

  • Introduction to Agent Skills

    Anthropic Academy

    Verified Credential

    Issued Jul 2026

  • Claude Code in Action

    Anthropic Academy

    Verified Credential

    Issued Jul 2026

  • Claude Platform 101

    Anthropic Academy

    Verified Credential

    Issued Jul 2026

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