0110 guided workflowsRetrievalSales AIGuardrails
Sales Knowledge Engine
A guided AI workspace that turns scattered sales knowledge into account briefs, proposals, meeting prep, and CRM-ready actions.
Explore systemSystems architect · Applied AI builder
AI that worksin the real world.
I'm Suhas Bhairav. I design reliable agentic systems, knowledge infrastructure, and production AI workflows for complex products.
15+ years building systems9 peer-reviewed papersMasters from TU Darmstadt
Models
Tools
Knowledge
Human judgment
Python
JavaScript
Next.js
FastAPI
PostgreSQL
Redis
Docker
AWS
Azure
GCP
LangChain
LlamaIndex
PyTorch
Hugging Face
01Agentic workflows
02Knowledge systems
03AI reliability
Selected systems
Practical prototypes for real revenue, operations, and knowledge workflows.
Practical AI. Built for real work.
0110 guided workflows
02Hours → minutesRAGCitationsEnterprise
Document Intelligence Copilot
A source-grounded copilot that helps teams find answers across RFPs, proposals, and sales collateral in minutes.
Explore system
03Human-in-the-loopAgentsSupport OpsEvaluation
Support Ticket Intelligence
A multi-agent workflow for triage, root-cause summaries, SLA risk, and governed customer-response drafting.
Explore systemThe Bhairav Show
Conversations with builders.
Dr. Oliver Borchers
Production AI Systems, AI Agents, and Why AI Projects Fail with Dr. Oliver Borchers
Production AI Systems · AI Project Failure
Suhas Bhairav
AI Agents for SMEs: 10 Practical Use Cases Beyond ChatGPT
AI Agents for SMEs · Customer Support Assistance
Suhas Bhairav
How to Build a Simple AI Workflow for Customer Support
Customer Support AI Workflow · AI Ticket Classification
What I build
From uncertain idea to dependable system.
I work where AI meets real organizational complexity—legacy systems, sensitive data, human decisions, and the need to prove that something actually works.
01
Agentic systems
Designing observable workflows where models, tools, data, and human judgment work together safely.
- Workflow architecture
- Tool orchestration
- Human oversight
02
Knowledge infrastructure
Building retrieval and graph layers that make enterprise knowledge useful, traceable, and maintainable.
- RAG systems
- Knowledge graphs
- Source grounding
03
Reliable AI delivery
Taking AI beyond the demo with evaluation, failure-mode thinking, security, and production discipline.
- AI evaluation
- Guardrails
- Systems reliability
Completely open source
AI Chief of Staff for company intelligence.
An independent MIT-licensed project to upload department metrics, generate current-data JSON, and turn finance, sales, product, marketing, HR, and operations into CEO-ready recommendations.
Operating principles
How I think about AI delivery.
The most valuable systems are understandable, governable, and quietly useful in ordinary work.
Useful before autonomous
Start with a real decision or workflow. Earn autonomy through evidence.
Visible before magical
Expose sources, reasoning boundaries, approvals, and failure paths.
Systems before prompts
The model is one component. Data, interfaces, evaluation, and operations make it work.
Research foundation
9publications
Security and reliability are not afterthoughts.
My research in IoT security, static analysis, fuzzing, and graph complexity still shapes how I build AI systems today.
Security2020
OVER: Overhauling vulnerability detection for IoT through automated static analysis
ACM SAC
IoT2019
PIT: A probe into IoT by comprehensive security analysis
IEEE TrustCom
Reliability2018
Security testbed for Internet-of-Things devices
IEEE Transactions on Reliability
Best paper2017
Complexity Reduction in Graphs: A User Centric Approach
IARIA