PANKAJ PRAMANIKData & AI Engineer, home
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03 / Services

Build reliable data.Make better decisions.

Start with the data behind your business. I help connect sources, build dependable pipelines, and turn information into useful reporting and analysis, with cloud and AI engineering where they fit.

Explore services See the work
Bar and pie charts on a laptop beside a tablet on a desk.
  1. Engineering
  2. Analytics
  3. Cloud
  4. AI

01 / Service explorer

Start with the data.Build from there.

Pick an area to see the problems it solves, what you get, the tools involved and related work.

Service area / 07

Make room for better work.

Connect applications and automate repetitive tasks with observable workflows, clear boundaries and useful failure recovery.

Hand-drawn workflow sketches in an open notebook with pens.

Typical problems

  • People copy data between tools all day
  • Leads and requests fall through the cracks
  • Existing automations fail without anyone knowing

What you get

  • Mapped workflows with owners and edge cases
  • Integrations with retries, logging and alerts
  • Handoff notes and a recovery playbook

Tools

  • n8n
  • Make.com
  • Zapier
  • GoHighLevel
  • Retell AI
  • HubSpot
  • APIs
Discuss Automation Read the full service
  1. Data EngineeringPrimary career direction
  2. Data AnalyticsPrimary career direction
  3. AI SecurityGrowing focus
  4. CloudSupporting infrastructure
  5. AI EngineeringApplied systems

I’m building my long-term career around Data Engineering and Data Analytics. Alongside my current work, I’m developing a deeper focus on AI Security, supported by cloud infrastructure and AI engineering.

02 / System architecture

From raw datato trusted decisions.

Most services plug into the same platform. Scroll through its four steps, or pick a stage to see what it does.

  1. Databases, APIs, files and SaaS tools land in a raw layer exactly as received, so the original is always there to check against.

  2. Data is cleaned, tested and modelled. Quality checks run on every load, so problems surface before anyone sees a report.

  3. Agreed metrics are defined once and reused by every dashboard, analysis and AI feature, so the numbers match everywhere.

  4. Orchestration, lineage and monitoring wrap every run, so each number can be traced, explained and trusted.

Modern data platform

Control planeData plane

Raw layer

Control plane

Unified data plane

Hover a stage to inspect it

03 / All services

Every service page,grouped by area.

Data Engineering

Data EngineeringScalable data engineering that turns raw data into reliable pipelines, structured systems and actionable business insights.AI-Powered Data PipelinesIntelligent data pipelines that combine ETL/ELT, machine learning, vectorization and automation to turn raw data into real-time insights and actions.Bioinformatics Data Engineering & AnalyticsGenomics data pipelines, ETL, big data processing, AI/ML, and healthcare analytics.

Data Analytics

Data Analytics & VisualizationTurn raw data into clear, actionable insights with advanced analytics, dashboards, forecasting and AI-powered reporting.

Cloud / Production

Cloud & DevOps for AIDeploy, scale and secure AI applications, models, agents and data systems with modern cloud and DevOps infrastructure.AWS Serverless AppsServerless applications on AWS that combine Lambda functions, event sources, APIs and databases, defined with the AWS Serverless Application Model (SAM).AI-Based Software DevelopmentFull-stack, AI-native products - LLM and ML capabilities designed into the architecture, not bolted on afterwards.Chat App DevelopmentElevate conversations with expert Chatting App Development. Hire a Full Stack Web Developer for seamless, innovative communication solutions.DSA Problem SolvingEfficient, scalable solutions to complex technical problems using algorithms, system design and backend logic.

AI / ML

Data Science & Machine LearningExplore a spectrum of services designed to meet your unique requirements. From software development to data science and beyond, we provide bespoke solutions for your every project need.Deep Learning SolutionsExplore cutting-edge Deep Learning Solutions tailored for unparalleled advancements. Artificial intelligence with our expertise, shaping the future of technology.Natural Language ProcessingRevolutionize your projects with (NLP) Natural Language Processing excellence. Hire skilled professional, ML integration, and domain-specific applications.

GenAI / RAG

LLM & RAG SystemsLLM-powered and RAG-based applications that deliver accurate, context-aware answers through retrieval pipelines, vector search and prompt orchestration.Vector Database IntegrationSemantic search, RAG and AI retrieval systems built on scalable vector database integrations, embeddings and LLM workflows.LangChain DevelopmentLangChain-powered AI applications that connect LLMs with APIs, databases, vector stores and business logic to reason, retrieve and automate real workflows.Prompt EngineeringPrompt engineering for LLMs, chatbots, RAG systems, agents and automation workflows that improves accuracy, consistency, safety and real-world usefulness.

Agentic AI

Agentic AI DevelopmentAutonomous, tool-using AI agents and multi-agent systems that plan, act, and complete real business workflows end to end.Forward-Deployed Engineer (FDE)Embedded engineering: I work directly with your team to turn AI capabilities into deployed, business-ready systems on the ground.AI Chatbots & AgentsIntelligent AI chatbots, voice assistants and action-capable agents powered by LLMs, RAG, memory, APIs and automation workflows for real business use.AI Voice AssistantsAI voice assistants that speak, listen, understand and take action across phone-based workflows: support, lead qualification, appointment booking and intake.

Automation

AI AutomationEnd-to-end workflow automation across n8n, GoHighLevel, Retell AI, HubSpot, Filevine, Zapier, Make.com, and Google Sheets - connecting your tools into intelligent, self-running systems.AI & GaaS for Law Firm AutomationAI agents for client intake, CRM integration, appointment scheduling, document processing, and follow-ups.n8n Workflow Automationn8n workflows that connect apps, APIs, CRMs, AI tools and internal systems to reduce manual work and improve response speed.

LLMOps / MLOps

LLMOpsProduction operations for LLM apps: evaluation, prompt versioning, observability, guardrails, cost control, and continuous improvement.MLOpsHire a skilled MLOps developer to streamline machine learning operations, automate infrastructure, and deploy scalable models seamlessly.

04 / FAQ

Questions peopleask first.

What does Pankaj Kumar Pramanik do?

Pankaj Kumar Pramanik is an AI and data engineer with 8+ years of engineering experience. He builds data pipelines, analytics and dashboards, RAG applications, AI agents and workflow automation, and takes them to production with MLOps, monitoring and cloud infrastructure.

Which industries do you work with?

Mostly legal, healthcare, industrial, e-commerce and SaaS businesses. For law firms that means intake, document and voice automation; in healthcare and bioinformatics, clinical and genomic data pipelines and medical RAG with citations; in industrial settings, sensor data pipelines, monitoring dashboards and predictive maintenance.

Can you automate work for a law firm?

Yes. I build automation for client intake, document drafting and review, scheduling and follow-ups, plus AI chat and voice assistants that answer common questions. A person reviews anything that carries legal judgement, and every automated step is logged so the firm can see what happened.

Do you work with healthcare and bioinformatics data?

Yes. I build pipelines that validate and model clinical and genomic data, analytics on top of them, and retrieval-augmented assistants that answer from medical documents with citations. Access controls, audit logs and the compliance requirements that apply, such as HIPAA, are agreed before any data moves.

Do you work remotely with international clients?

Yes. I work remotely with teams worldwide, as a contractor on a defined project or embedded with an engineering team. Meetings are booked in your own timezone, and work is shared through your repositories, documentation and regular demos.

How does a project start?

It starts with a short call about the goal, the data and the constraints. I then reply with questions and a practical first step, usually a small, measurable piece of work, before anything larger is planned. You can book the call online or send a project brief.

Not sure yet?

Not sure which service fits?Tell me what you’re building.

Describe the goal and what’s in the way. I’ll suggest where to start - even if it’s smaller than you expected.

Let’s chat