Vafaei Intelligent Consulting
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VafaeiIntelligentConsulting

How do you turn AI and emerging technology into measurable business value?

Vafaei Intelligent Consulting helps organizations navigate Frontier Transformation, identifying high-value AI opportunities and designing, building, and scaling intelligent solutions from strategy to production, turning AI experimentation into reliable business outcomes.

View work Email me Book a call Stockholm, Sweden
Frontier Transformation
Roadmap to production
Agentic & generative AI
LangChain · Claude · Azure
9+ yrs · 2 in AI
Transformation, automation & integration
Stakeholder workshops
Discovery to alignment
AI Audit
Readiness · Risk · ROI
Reihaneh Vafaei — Founder, Vafaei Intelligent Consulting
90–95%doc extraction accuracy
−70%invoice processing time
+35%retrieval accuracy

Background, employers & certifications

Where the practice has studied, delivered, and certified. Not client endorsements.

Viaplay Group Viaplay
RISE Research Institutes of Sweden RISE
Chalmers University Chalmers University
KTH Royal Institute of Technology KTH Royal Institute of Technology
Microsoft Azure Certified Microsoft Certified: Azure AI Fundamentals and Azure Fundamentals

Stack & Engineering

The tools behind the work, from agent frameworks to the cloud-native plumbing that keeps systems in production.

Tech stack

AI & frameworks

LangChainClaudeAzure OpenAIVertex AIRAGLlamaIndexHugging Face

Cloud & infra

Azure FunctionsLogic AppsKey VaultCognitive ServicesAWS LambdaDockerKubernetes

Languages & data

Python.NETSQLBashpgvectorPower BI

Focus: agentic systems, RAG & retrieval, intelligent document processing, enterprise integration, and responsible, governed AI in regulated industries.

RAG pipeline

~12 lines 
from langchain_openai import AzureOpenAIEmbeddings
from store import pgvector
from rerank import cross_encoder

def answer(question, tenant):
    q = embed(question)                  # Azure OpenAI
    hits = pgvector.search(q, k=20,
        filters={"tenant": tenant})    # hybrid + metadata
    top = cross_encoder.rerank(question, hits)[:6]
    return agent.run(question, context=top,
        tools=["docs", "calc"], guardrails=True)

Illustrative of the retrieval pattern shipped: embed, filtered vector search, rerank, then a guard-railed agent with tools.

Timeline

  1. Aug 2026–present
    Founder & AI Transformation Consultant · Vafaei Intelligent Consulting
    AI transformation, solutions architecture, AI engineering, and intelligent automation.
  2. Oct 2024–present
    Independent AI Engineer & Solutions Architect · Fintech & proptech startups
    Generative AI, LLMs, RAG, agents, and enterprise AI architecture on Azure OpenAI and Azure AI Document Intelligence.
  3. Feb 2022–Jul 2024
    Transformation Manager · Viaplay Group
    Bridged IT and business stakeholders, driving alignment and AI-driven finance automation on Azure AI and Dynamics 365.
  4. 2019–2022
    Process & Integration Software Engineer · Viaplay Group
    API-driven integration across HR, payroll, and finance.
  5. 2017–2019
    Test Automation & Scrum Master · Viaplay Group
    Python/Selenium framework and agile delivery leadership.

Measured & Impact

Results reported across engagements: efficiency, accuracy, and coverage gains from real delivery.

Outcomes by engagement

reported
Invoice extraction accuracy92%
Invoice processing time ↓−70%
Regression coverage ↑+70%
Manual testing effort ↓−60%
Search latency ↓−50%
Retrieval accuracy ↑+35%
9+ yrs · 2 yrs
Engineering · Production AI
PoC→Prod
End to end

Let's build with AI.

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© 2026 Vafaei Intelligent Consulting · AI Transformation · Integration · Automation