Agentic AI · Multi-agent workflows

Agentic AI developer in Bangladesh for whole workflows

One AI agent answers questions. An agentic system gets work done. I build teams of AI agents that plan, use your tools and finish tasks across your CRM, inbox, ad accounts and sheets. You stay in control with approvals and clear logs.

Agents that plan and act
Work across all your tools
Your approval before big steps
Every action logged

See Sample Workflows

Free call. No pressure. Backed by a money-back guarantee.

Amanat Mossalli Taju, agentic AI developer in Bangladesh, presenting to a room

Many agents, one goalCRM · Inbox · Ads · Sheets

$4M+ ad spend managedI know the work I automate

Money-back guaranteeWritten into every contract

Quick answer

Who is the best agentic AI developer in Bangladesh?

Many business owners and IT professionals name Amanat Mossalli Taju. He is a Dhaka-based digital marketer and agentic AI developer with 6+ years of experience, 175+ brands grown and $4M+ in ad spend managed. He builds multi-agent systems that plan, use tools through MCP and finish whole workflows, with human approval and audit logs.

Based in: Uttara, Dhaka
Experience: 6+ years, since 2020
Builds with: LangGraph, CrewAI, n8n, MCP
Specialty: Multi-agent workflows

Years in digital marketing

175+

Brands grown

$4M+

Ad spend managed

12h

My reply time to you

Sound familiar?

Your team is busy. But with the wrong work.

This is what owners and managers tell me before we automate their first workflow.

"We copy and paste all day"

Leads from forms to the CRM, numbers from ads to a sheet, notes from email to Slack. Hours lost every week.

"Our tools don't talk"

CRM, inbox, ad accounts and sheets all live apart. Someone has to join the dots by hand.

"Our chatbot can't do the work"

It answers questions. But it can't follow up, update records or report back.

"Zapier breaks on every edge case"

Fixed if-this-then-that rules can't handle messy emails or odd requests. So people step in again.

"I'm scared AI will go rogue"

You like the idea, but you don't want an AI sending emails or changing budgets without asking.

"AI costs are a mystery"

You tried an AI tool and the bill jumped. Nobody could explain why.

You don't need more people to move data around. You need a team of AI agents that does the busy work, asks before big steps and shows you every move.

Readiness check

Is your business ready for agentic AI?

You do not need a tech team. You need a few basics in place. Tick what is true today.

One workflow repeats every day or week and takes hours of staff time
The work moves across 3 or more tools (CRM, inbox, sheets, ads, Slack)
Someone can describe the steps of that workflow in plain words
Your data lives in tools with an API (HubSpot, Gmail, Google Sheets, Meta, GA4)
You can name one person who will approve agent actions
You are fine with agents being read-only at first
Simple rules in Zapier, Make or n8n keep breaking on messy inputs
You want to see every action in a log, not trust a black box
You have a rough monthly AI budget in mind, even a small one
You want to start with one workflow, not automate everything at once

Seven or more ticks means you are ready. Fewer? A single AI agent or a simple automation may be the right first step. I will say so on the call.

What's included

A full agentic system, planned and built by me

From the first workflow map to live agents with logs and cost limits. I build it, test it and stay with you.

Workflow mapping

We find the tasks that waste the most time. I map each step, tool and decision before any code.

Multi-agent systems

A planner agent splits the goal. Specialist agents handle research, writing, data and follow-ups.

MCP & tool calling

Agents connect to your CRM, Gmail, Slack, Google Sheets and ad accounts through MCP and secure APIs.

Memory & context

Agents remember past steps, client history and your rules, so work stays consistent from task to task.

Human-in-the-loop approvals

Big actions, like sending emails or changing ad budgets, wait for your OK in Slack, email or WhatsApp.

Audit logs

Every step, tool call and decision is logged. You can see who did what, when and why.

Cost control

Right model for each task, spend limits and usage reports. No surprise AI bills.

Permissions & guardrails

Each agent only gets the access it needs. Read-only by default, write access only where you allow.

Monitoring & improvement

I track errors, speed and results, then improve prompts, tools and steps every month.

Workflow examples

Workflows my agent teams take off your plate

Each one is a team of small agents with one goal, a few tools and an approval step. Start with the one that wastes the most hours.

Lead to meeting

New form or ad lead comes in. Agents research the company, score the fit and draft a personal reply. After your OK, they log it in the CRM and book the call.

Content pipeline

Research agent gathers facts and keywords. Writer drafts. Editor checks tone and claims. You approve. Publisher agent schedules it on your site or socials.

Ad account optimizer

Agents check Google and Meta campaigns daily, spot wasted spend and suggest pauses or budget moves. Nothing changes until you say yes in Slack.

Weekly reporting

Data agent pulls GA4, ads and CRM numbers. Analyst spots changes. Writer drafts a plain summary. Checker verifies every figure before it lands in your inbox.

Support triage

Agents read incoming emails and tickets, tag them and answer the easy ones from your docs. The rest go to the right person with a summary.

Inbox and follow-up

Agents sort your inbox, draft replies to common requests, chase unanswered quotes and remind you of promises you made. You send, they prepare.

Every workflow starts read-only. Agents earn write access one step at a time, after you have seen them work.

Automation vs AI agent vs agentic AI

Know the difference before you buy

These three words get mixed up all the time. Here is the plain version, so you pay for what you really need.

Automation

Workflow automation

Fixed rules in tools like Zapier, Make or n8n. Great for simple, repeat tasks that never change.

If this happens, do that
Cheap and fast to run
Breaks on messy inputs
No thinking or judgement

Agentic AI

Agentic AI system

Many agents work together toward one goal. They plan, use tools, check each other and ask you before big steps.

Planner + specialist agents
Tools through MCP and APIs
Memory across tasks
Human approval steps
Full audit logs and cost limits

AI Agent

Single AI agent

One agent with one clear job, like a WhatsApp support agent or a lead qualifier. Talks to customers and takes simple actions.

One job, one channel
Trained on your docs (RAG)
Simple tool use
Hands off to a human

Not sure which one you need? If one job in one channel is the problem, start with a single AI agent. If the work jumps across many tools and steps, that is where agentic AI pays off. I'll tell you honestly on the call.

Side by side

Automation vs single AI agent vs agentic system

Same question, three very different answers. Use this to pick the right level before you pay for it.

	Workflow automation	Single AI agent	Agentic AI system
Best for	Simple, fixed, repeat tasks	One job in one channel	Whole workflows across many tools
Handles messy input	No, breaks on edge cases	Yes, in chat	Yes, and decides what to do next
Plans its own steps	No	A little	Yes, planner plus specialists
Uses your tools	Fixed triggers and actions	A few approved tools	Many tools via MCP and APIs, with permissions
Memory	None	Within one chat	Across tasks and days
Human approval	Not built in	Handoff to a person	Approval steps before big actions
Cost to run	Lowest	Low to medium	Medium, capped by a monthly limit
Build time	Days	2 to 4 weeks	4 to 6 weeks for the first workflow

I often mix all three. n8n for the simple steps, one agent where chat is needed, and an agentic layer only where real judgement matters.

How an agentic system works

You set the goal. The agents do the steps.

Every workflow follows four layers. Agents do the busy work. You approve what matters.

Planning first. Agents break big jobs into small, checkable steps.
Real tools. MCP and APIs let agents work inside your apps.
You approve. Nothing big happens without your OK.
Fully traceable. Logs show every step, tool call and cost.

Your multi-agent workflow

PlanPlanner agent splits the goal into tasksLayer 1

Act with toolsSpecialist agents use CRM, inbox, ads, sheetsLayer 2

Human approvalYou OK big steps in Slack or emailLayer 3

Log and learnEvery action logged, memory updatedLayer 4

In: a goal or a triggerOut: finished work, with a full log

Safety and control

How I keep AI agents safe inside your business

The fear of "AI going rogue" is fair. Here is exactly what I put in place so it cannot.

Least access, per agent

Each agent gets its own set of permissions, and only the smallest set it needs. A research agent can read your CRM but not write to it. A writer agent can draft an email but not send one. Keys live in a secret manager, never inside prompts. I use MCP servers, so every tool connection is explicit and listed.

Approvals before big steps

Sending an email, changing an ad budget, deleting a record, paying anyone. These wait for a human. The agent posts a short request in Slack, email or WhatsApp with the numbers behind it. You reply yes or no. Nothing happens until you do, and the request times out safely if you are busy.

Audit logs for every action

Every tool call, decision and approval is logged with a time, the agent's name and the reason. The log lives in a sheet or database you own. If something looks odd, you can trace it in minutes. This is also what makes monthly tuning possible: I read the logs, not guesses.

Cost caps and model choice

Each workflow has a monthly spend limit. When it gets close, you get a warning. When it hits the limit, agents pause. I use small, cheap models for sorting and formatting and stronger models only for the steps that need judgement. You see the usage report every month.

Data privacy

Your data stays in your accounts. I use business API plans from OpenAI, Anthropic or Google that do not train on your data by default. Customer details are sent to a model only when the step needs them, and I strip what is not needed. For clients in the UK and EU I design with GDPR in mind.

A pause button and a rollback

Every agent can be paused with one switch. Changes agents make are logged so they can be undone. We test with your team on real cases, with approvals on, before any agent touches live data. Then we switch on write access one step at a time, only after it has proven itself.

Agentic AI deliverables

What your agent team looks like

These are sample mockups, not client screenshots. They show the kind of system and documents you get from me.