Enterprise AI Consulting
Identifying and designing AI use cases that are genuinely worth building — scored on value, feasibility and risk.
- Use-case discovery & prioritisation
- AI adoption roadmap
- Build-vs-buy guidance
- Responsible AI considerations
Available for corporate training, college bootcamps & AI consulting
Abhishek Gupta
GenAI & Data Architect.
AI Consultant & Corporate Trainer.
16+ years architecting cloud data platforms and AI systems — 12 years training and 8 years consulting, with 200+ programs delivered across corporates, universities and colleges in GenAI, LLMs, RAG, Agentic AI, Azure, Databricks and Cloud Data Engineering.
Business Problem→
Architecture→
Technology→
Implementation→
Practical Learning
- 16+Years total experience
- 12Years training experience
- 8Years consulting experience
- 200+Trainings delivered
Industry experience & alumni network
MicrosoftAdobeAmerican Express
United Health GroupCapgeminiHSBC
SapientLTIZensarStandard Chartered
Technologies taught & architected
Azure AI FoundryDatabricksLangChainLangGraph
Apache SparkPySparkPythonSQL
RAGAgentic AIMCPVector DB
Azure Data FactorySynapseAWS SageMakerUnity Catalog
N8NHadoopKafkaTensorFlow
Azure AI FoundryDatabricksLangChainLangGraph
Apache SparkPySparkPythonSQL
RAGAgentic AIMCPVector DB
Azure Data FactorySynapseAWS SageMakerUnity Catalog
N8NHadoopKafkaTensorFlow
01 — Professional Profile
The differentiator is the combination.
Most trainers teach a tool. Most consultants ship a deck. Abhishek does both — because the same person architected the GenAI platforms at Sapient, the data platform at Adobe and the regulatory pipelines at HSBC, then taught 200+ programs on exactly those systems.
01
16+ Years Industry
Banking, healthcare, retail, marketing tech and AI platforms.
02
8 Years Consulting
Framing the business problem before reaching for a model.
03
Data & AI Architecture
Designs that survive security, scale and cost reviews.
04
Hands-on Engineering
Code written live — LangGraph, PySpark, Azure AI Foundry.
05
12 Years Training
200+ programs across corporates, universities and colleges.
06
Mentoring
Long-term capability, not a one-day certificate.
Training programs are built around real-world use cases, architecture walkthroughs, live demonstrations, hands-on development and end-to-end projects — aligned with how enterprises now measure learning: by observable, applied outcomes.
02 — Technical Skills
The full stack, from raw data to reasoning agents.
Seven practice areas built over 16 years of production delivery — and taught the same way they were built.
Generative AI
Grounded, evaluated, enterprise-ready GenAI — not chat demos.
Generative AILLMsRAG PipelinesPrompt Engineering
EmbeddingsVector DatabasesSemantic Search
Azure OpenAIOpenAIGroqHuggingFace
LangChainAzure AI Foundry
Fine-Tuning (LoRA & QLoRA)Guardrails & Safety
EvaluationEnterprise GenAI Architecture
Agentic AI
Multi-agent systems with reasoning, memory, tools and guardrails.
Agentic AIMulti-Agent SystemsLangGraphStateGraph
AgnoTool CallingAgent MemoryReasoning
MCP ServerAzure AI Foundry AgentsN8N Workflows
NLP2SQLGuardrailsAgent EvaluationAgent Observability
Machine Learning & Data Science
Classical ML and deep learning, end to end.
Supervised LearningRegressionClassification
Deep LearningANNRNNTime Series
Hyperparameter TuningFeature EngineeringEDA
Predictive AnalyticsNumPyPandasScikit-learn
TensorFlowMatplotlibAWS SageMakerModel Deployment
Data Engineering & Architecture
The foundation every AI programme quietly depends on.
Big DataApache SparkPySparkScala
HadoopHDFSHiveSqoopMapReduce
YARNKafkaETL / ELTData Warehousing
Data ModellingMedallion ArchitectureDelta Lakehouse
Data PipelinesDataStageData Governance
Performance Tuning
Cloud Platforms
Azure-first, Databricks-deep, AWS-capable.
Azure Data FactoryAzure SynapseADLSAzure Blob
Azure Data Explorer (ADX)CosmosDBAzure AI Foundry
Azure DevOps
Databricks NotebooksDelta Live TablesUnity Catalog
Auto LoaderDelta TablesDatabricks SQL Warehouse
AWS EC2AWS EMRAWS S3AWS Glue
AWS AthenaAWS LambdaAWS SageMaker
Languages & Databases
Fluent across the query and scripting surface.
PythonSQLScalaKQLUnix Shell
HQLPostgreSQLOracleDB2
NoSQLHBaseKustoDBHive
AI Engineering & DevOps
Shipping AI: CI/CD, traceability, monitoring and release management.
GitAzure DevOpsCI/CDJenkinsJira
Release ManagementMonitoringObservability
TraceabilityData SecurityPyCharmEclipse
Power BIData VisualizationAgile / ScrumSprint Management
03 — Consulting
From "where do we even start" to a working system.
Consulting engagements that produce artefacts teams can act on: use-case maps, reference architectures and working proofs of concept.
Solution Architecture
Reference architectures that hold up in front of security, platform and finance stakeholders.
- AI & Enterprise GenAI architecture
- Data & cloud architecture
- Integration architecture
- Agentic AI solution design
AI Proofs of Concept
Rapid POCs that answer the uncomfortable questions early — before budget is committed.
- Business value validation
- Technical feasibility
- Architecture validation
- User experience & AI capability testing
Data Engineering Consulting
The unglamorous layer that decides whether the AI layer works at all.
- Data platforms & lakehouse design
- ETL / ELT and pipelines
- Databricks & Spark
- Cloud data solutions
04 — Corporate Training
Building an AI-ready workforce.
One organisation, four very different audiences. Each track is scoped to the decisions that audience actually makes — so nobody sits through content they can't use.
Leadership & Business Teams
Outcome: confident, realistic AI decision-making.
- Generative AI Awareness
- Enterprise AI Opportunities
- AI Adoption & AI Strategy
- AI Use Cases
- Responsible AI Concepts
Architects & Technical Leads
Outcome: defensible AI architectures.
- Enterprise GenAI Architecture
- RAG Architecture
- Agentic AI Architecture
- AI Solution Design
- AI Evaluation & Observability
Developers & Engineers
Outcome: ship an AI feature, not a notebook.
- Generative AI Development
- RAG Applications
- AI Agents
- Azure AI Foundry
- Microsoft Agent Framework & MCP
- FastAPI & AI Application Development
Data Professionals
Outcome: data teams that can carry AI workloads.
- Data Engineering
- Python & SQL
- Databricks & Spark
- Azure Data Engineering
- Data + AI & Data Architecture
Delivery formats
Instructor-led (onsite)
Virtual live
Half-day executive briefings
2–5 day bootcamps
Multi-week cohorts
Hackathon / capstone
Mentoring retainers
05 — College & University Programs
Bridging the gap between education and industry.
Positioned around industry readiness rather than a syllabus. Students leave with a project they can demo, explain and defend in an interview.
Generative AI Bootcamp
From "what is an LLM" to a working, grounded AI application.
- GenAI fundamentals
- LLMs
- Prompt Engineering
- RAG
- AI applications
- Practical projects
Agentic AI Bootcamp
Students build agents that use tools and coordinate with each other.
- AI Agents
- Tool-using agents
- RAG agents
- Multi-agent workflows
- Agent applications
Data Engineering Program
The most reliably hireable skill set in the data market.
- Python & SQL
- ETL
- Data Warehousing
- Spark & Databricks
- Cloud Data Engineering
Azure AI Program
Enterprise AI on the platform most employers already run.
- Azure AI
- Azure AI Foundry
- AI application development
- AI Agents
- Enterprise AI concepts
Portfolio-firstEvery learner finishes with a deployable project.
Industry framingTaught with real enterprise use cases, not toy datasets.
Interview-readyArchitecture reasoning, not just syntax recall.
Faculty enablementTrain-the-trainer sessions for lasting departmental capability.
06 — Credentials & Clients
Certified, and trusted by enterprises and universities.
Certifications
- ✦AWS Solutions Architect — ProfessionalAmazon Web Services
- ✦Generative AI LeadershipGoogle Cloud (GCP)
- ✦Azure DatabricksMicrosoft / Databricks
- ✦Apache Spark FrameworkCertified
- ✦Apache Hadoop EcosystemCertified
Education
- 🎓B.E. — EngineeringPune University · 2009
Enterprise clients
MicrosoftAdobeAmerican Express
United Health GroupHSBCStandard Chartered
CapgeminiLTIZensarSapient
Tridat Technologies
Academic institutions
JIITSanskriti UniversityD.Y. Patil College & University
and many more
200+ training programs delivered across corporates, universities and colleges — classroom, web-based and recorded — including overseas programs and workshops in Cloud Data Engineering, Data Science and GenAI technologies.
07 — Training Philosophy
Theory is the shortest part of the session.
Every program follows the same arc, whether it's a half-day executive briefing or a multi-week cohort.
-
1
Real-world use case
Start from a problem the audience recognises from their own work.
-
2
Architecture first
Draw the system before writing the code. Understand the trade-offs.
-
3
Live demonstration
Watch it work — including the parts that break and why.
-
4
Hands-on development
Participants build it themselves, with guidance at the sticking points.
-
5
End-to-end project
Finish with something complete, evaluated and demonstrable.
Who this is for
🏢
Corporates
Build an AI-ready workforce across leadership, architecture, engineering and data teams — with training tied to real internal use cases.
Request a corporate proposal →
🎓
Colleges & Universities
Industry-readiness bootcamps in GenAI, Agentic AI, Data Engineering and Azure AI, plus faculty enablement.
Plan a campus program →
🚀
Students & Professionals
Cohort bootcamps and mentoring that convert into projects, portfolios and role transitions.
Join the next cohort →
08 — Let's talk
Ready to make your team AI-capable?
Share your audience, timeline and outcome — you'll get a tailored curriculum outline, delivery format and project plan. No generic catalogues.
Start a conversation
Training, consulting, solution architecture, a proof of concept or mentoring — tell me what you're trying to achieve and you'll get a tailored plan, not a catalogue.