You will get AI READINESS AUDIT FOR SME OPERATIONS
Project details
Find out exactly where AI will save your business time and money — and what to implement first.
Most businesses know they should use AI. Few know where to start or what sequence will deliver ROI.
I assess your operations across seven dimensions — data readiness, workflow maturity, stack fit, team capability, security posture, measurement infrastructure, and strategic alignment — score each one, and deliver a prioritised roadmap telling you what to do first, second, and third.
This isn't a generic checklist. I've spent 19 years building enterprise software across healthcare, FMCG, research, and real estate, deploying AI orchestration systems in production. The assessment draws on real implementation patterns — what works, what fails, and why.
You receive: scored maturity assessment, use-case priority matrix with build/buy/partner recommendations, and a 90-day implementation roadmap. Standard and Advanced tiers include a recorded walkthrough and live Q&A.
Best for SMEs exploring AI, companies with failed pilots needing a reset, or leadership teams needing a defensible plan before committing budget.
Most businesses know they should use AI. Few know where to start or what sequence will deliver ROI.
I assess your operations across seven dimensions — data readiness, workflow maturity, stack fit, team capability, security posture, measurement infrastructure, and strategic alignment — score each one, and deliver a prioritised roadmap telling you what to do first, second, and third.
This isn't a generic checklist. I've spent 19 years building enterprise software across healthcare, FMCG, research, and real estate, deploying AI orchestration systems in production. The assessment draws on real implementation patterns — what works, what fails, and why.
You receive: scored maturity assessment, use-case priority matrix with build/buy/partner recommendations, and a 90-day implementation roadmap. Standard and Advanced tiers include a recorded walkthrough and live Q&A.
Best for SMEs exploring AI, companies with failed pilots needing a reset, or leadership teams needing a defensible plan before committing budget.
AI Development Type
Deep Learning, Knowledge RepresentationAI Tools
Google AutoML, MLflow, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$3,500
|
Advanced
$5,500
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | |
Model Documentation | |||
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - |
Optional add-ons
You can add these on the next page.
Extra Department Deep-Dive
(+ 3 Days)
+$800
Advisory Call (60 min)
(+ 1 Day)
+$250
Board Presentation Summary
(+ 2 Days)
+$500Frequently asked questions
About Tawhidur
AI Implementation Strategy | Agentic Systems Architect | Data Science
Dhaka, Bangladesh - 9:40 pm local time
This isn't theoretical. Over the past 19 years leading technology enterprises, I've personally designed, built, and deployed:
→ A 55-agent agentic AI orchestration system running autonomously in production — coordination logic, pipeline gates, human-in-the-loop governance, and multi-model integration (Claude, GPT, Gemini) serving the same knowledge layer through different interfaces
→ Computer vision systems for brand protection and supply chain integrity for a multinational FMCG corporation — processing product authentication across a national distribution network of 2,500+ field operatives
→ RAG-based conversational intelligence platforms that let non-technical executives query enterprise databases, policy documents, and operational data in plain language — deployed across financial services, research, and consumer goods
→ AI-powered business intelligence infrastructure for a global insurance company (Singapore and Japan) — predictive modelling of customer behaviour that directly drove policy subscription growth
→ A research operations platform for Oxford University's global neonatal sepsis programme — serving medical researchers, government health authorities, and international funding bodies across 19 countries with audit-grade compliance
→ Credit intelligence and fraud detection systems for the world's largest microfinance operator — advanced analytics, prediction modelling, and a proprietary credit-rating engine handling loan profiling and disbursement decisions
Most people talking about AI implementation in 2026 have never shipped anything into production. Most people who've shipped enterprise software haven't touched agentic AI. I sit at that intersection — and it's a small intersection.
What I bring to engagements:
▸ AI Readiness Audits — Where does AI actually create value in your operations? I assess your data maturity, process readiness, and technology landscape, then deliver a prioritised roadmap with realistic ROI projections. No jargon. No vendor pitches. Just a clear-eyed view of what's worth building.
▸ Automation Architecture Design — Complete system blueprints: workflows, integrations, data flows, AI components, governance frameworks. Implementation-ready specifications, not slide decks.
▸ AI Workshop Design & Delivery — Structured workshops that translate AI capabilities into business language for leadership teams. Industry-specific use case development, adoption frameworks, and practical implementation planning.
▸ Implementation Oversight — Strategic advisory during your team's build phase. Architecture decisions, quality assurance, and course-correction when things go sideways (they always do).
▸ Technology Due Diligence — Independent assessment for investors, boards, or executive teams evaluating AI vendors, platforms, or build-vs-buy decisions.
Industry depth: Healthcare & Life Sciences, FMCG & Consumer Goods, Financial Services & Insurance, Real Estate, Research & Academia, Government & Defense.
Geographic experience: Engagements spanning the US, Latin America, South Asia, Europe, Middle East, and Southeast Asia.
Background:
- 14 years leading a technology enterprise across six industry verticals and three continents.
- Former Business Executive at a Fortune-500 multinational.
- MIT MicroMasters in Data Science.
- MBA
- IBM certified in DataOps, Machine Learning, and Applied Data Science.
I take on 1–2 engagements at a time. If you're looking for someone who's been in the rooms where AI implementation decisions are made — and in the codebases where those decisions are turned into running systems — let's talk.
Steps for completing your project
After purchasing the project, send requirements so Tawhidur can start the project.
Delivery time starts when Tawhidur receives requirements from you.
Tawhidur works on your project following the steps below.
Revisions may occur after the delivery date.
Review
Review your intake answers and schedule a 30-minute kickoff call to clarify scope and priorities.
Interview
Conduct stakeholder interviews and systems review. Audit current tools, data sources, and workflows.