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Agentic Systems

Staged AI workflows with explicit handoffs, verification and human control.

I build AI systems for work where being wrong is expensive. Sixteen years in enterprise procurement architecture taught me the costly failure is the one nobody notices — so every system here has a stage whose only job is to catch it, and a human gate where judgement belongs.

Specialists

Domain-focused agents for specific tasks

Explicit Handoffs

Well-defined transitions between agents

Verification

Automated checks at each stage

Human Gates

Human review at critical points

Built & Running

Real problems. Working systems.

Proposal Response Engine

Extract
Structure
Verify
Draft
Audience:
Consultants, bid teams, SIs and procurement leads
Outputs:
Requirements register, clarification questions, response structure, drafted module answers.
Document IntelligenceStructured ExtractionCoverage Gate

Assessment Paper Engine

Learn
Generate
Verify
Deliver
Audience:
Teachers, tutors, education platforms, training teams
Outputs:
Question paper PDF, explained answer key, validation report.
Evaluator–OptimizerBlind ValidationPython-Solved Answers

Social Content Engine

Plan
Research
Verify
Publish
Audience:
Product marketers, content teams, founders
Outputs:
Approved weekly topic, researched content brief with sources, finished post copy, rendered social assets.
Content PlanningResearch ValidationHuman-in-the-Loop

Procurement Knowledge Agent

Ask
Search
Reason
Answer
Audience:
Consultants and solution architects who need a sourced answer fast — on a client call, or while prepping a bid.
Outputs:
Cited answer, session transcript, running log of questions asked.
LangGraphMCPDynamic Orchestration

Have a complex workflow that AI should make simpler?

Open to enterprise AI, procurement transformation, product collaboration, MVP building, and agentic workflow design.

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