We design, build and deploy custom AI agents that take real work off your team — chatbots that answer customers, analyzer agents that read your data, report agents that write the weekly summary, and n8n automations that tie it all together. Built on Claude, GPT, Gemini or open-source models, and grounded in your own data.
What we build
Every agent is scoped to a job your team does today — and measured against how well, how fast and how cheaply it does that job.
An agent built to own one job end to end: it reads the input, decides the steps, calls your tools and hands back a finished result — with a human approval step wherever you want one.
Custom AI chatbots for your website, WhatsApp, Messenger or Slack that answer from your own content, capture leads and hand the conversation to a person when it matters.
Agents that sit inside your helpdesk, resolve the repeat questions, draft replies for the rest and tag every ticket — so your team only handles the conversations that need them.
Point an analyzer agent at spreadsheets, databases, documents or reviews and it finds the trends, outliers and answers — then explains them in plain language.
Report generation agents that pull from your sources on a schedule, write the summary and deliver it — the weekly KPI report nobody has to assemble by hand again.
Invoices, receipts, forms and IDs go in as scans or PDFs; clean, validated data comes out — straight into your accounting system, ERP or database.
Agents that enrich new leads, score them against your ideal customer, draft the first outreach and keep the CRM up to date without anyone copying fields across.
Research agents that search the web and your internal sources, compare what they find and return a short, cited brief instead of forty open tabs.
Agents that write in your brand voice — product descriptions, SEO drafts, social posts and order-aware customer emails — ready for a quick human review.
Agents that parse CVs in bulk, rank applicants against the role, answer candidate questions and schedule interviews — the approach behind our own Aplicaro platform.
Retrieval-augmented (RAG) assistants that let your team ask questions of policies, SOPs, manuals and past projects — with answers cited back to the source document.
For bigger jobs, several specialised agents work together — a researcher, an analyst and a writer — coordinated through LangGraph or MCP with clear checkpoints.
Workflow automation
Not every problem needs a bespoke agent. Often the fastest win is an n8n workflow with an AI step in the middle — reading an email, classifying a ticket or writing a summary — connected to the tools you already use. We build, self-host and maintain n8n for you, or wire the same logic into Make, Zapier or your own code when that fits better.
Automate a workflowCustom requirement
Have a process that doesn't fit any template? Tell us the job. We'll check whether AI can do it reliably, build a proof of concept on your own data, and show you the numbers before you commit to a full build.
The stack
Any model API, any automation tool, any system with an API — chosen for your task rather than out of habit.
Use cases
The same building blocks, applied to the work that eats the most hours in each industry.
Shopping assistants, order-status chatbots, product content and review analysis.
In-product AI features, support deflection and usage reports written for every customer.
Invoice extraction, reconciliation checks and month-end reports assembled automatically.
CV screening, candidate ranking, onboarding assistants and policy Q&A.
Multilingual support agents and plan recommendations for travel and eSIM businesses.
Document processing, exception alerts and daily operations summaries.
Our process
Value proven on your own data first, then scaled — never the other way round.
We find the task with the clearest return — the hours it costs today, the data it needs, and what 'done well' looks like.
A working proof of concept on your real documents and systems, so you judge results, not a slide deck.
The agent is connected to your tools with guardrails, permissions and human-in-the-loop steps where they belong.
We test against a set of real cases for accuracy, safety and cost per task before anything reaches your customers.
Production deployment with monitoring and logs, then ongoing tuning as your data, models and needs change.
Why us
An AI agent is only useful if it keeps working after the demo. That's the part we're built for.
We choose Claude, GPT, Gemini or an open-source model on accuracy, cost and privacy — and design so you can switch later without a rebuild.
Private deployments, API tiers that don't train on your data, and self-hosted n8n or open models when your data can't leave your servers.
Every agent ships with an evaluation set and a cost-per-task estimate, so you know it works — and what it costs to run — before launch.
We ship SaaS and mobile products, so our agents come with logging, retries, authentication and monitoring — not a fragile prompt in a spreadsheet.
A senior team in Bangladesh with working-hour overlap across Europe, the Middle East and Asia — and support that continues after launch.
Proof
Document automation, AI recruitment and AI-written store email — built, running and demonstrable.
Document automation · 2025
A document automation tool that reads invoices and returns structured data — the retyping step between a supplier's PDF and the accounting system, removed.
Extraction engine
Document type
Built and maintained
Data entry
AI recruitment SaaS · 2025
A multi-tenant AI recruitment platform: branded career pages, automated job posts, bulk CV intake and AI candidate ranking, on a subscription billing model.
Subscription tiers
Free trial
Plans start from
Support included
WooCommerce plugin · 2025
A WooCommerce and Shopify plugin that generates order-context emails from inside the store dashboard — custom templates, brand-aligned copy and no switching to a separate marketing tool.
Platforms: Woo and Shopify
Email generation
Install type
Built and maintained
FAQs
What clients ask most before starting an AI agent, chatbot or automation project.
An AI agent is software that uses a large language model to complete a task on its own — it reads the input, decides which steps to take, uses tools such as your CRM, database or email, and returns a finished result. Unlike a simple chatbot, an agent acts, not just answers.
A chatbot holds a conversation and answers questions. An AI agent can also take actions: look up an order, update a record, generate a report or trigger a workflow. Many projects combine both — a chatbot front end with agents doing the work behind it.
Task-specific agents, AI chatbots, customer support agents, analyzer agents, report generation agents, document processing and OCR agents, sales and lead agents, research agents, content and email agents, recruitment agents, internal knowledge assistants and multi-agent systems. If your requirement is different, we scope a custom agent around it.
All of them. We integrate Claude (Anthropic), OpenAI GPT, Google Gemini, and open-source models such as Llama, Mistral and DeepSeek, including through Azure OpenAI and AWS Bedrock. We pick the model on accuracy, cost and privacy for your task, and keep the design model-agnostic.
Whichever fits. n8n (cloud or self-hosted), Make and Zapier are the fastest route for workflow automation with an AI step. For agents that need complex reasoning, custom interfaces or heavy scale, we build in Python or Node.js with frameworks like LangGraph — and the two often work together.
Yes. We connect agents to CRMs (HubSpot, Salesforce), helpdesks, ERPs, accounting software, Shopify and WooCommerce, Google Workspace, Slack, WhatsApp and any system with an API — and use the Model Context Protocol (MCP) where it makes tool access cleaner.
Your data is not used for training. We use API tiers and cloud deployments (Azure OpenAI, AWS Bedrock) that exclude customer data from training, apply access control and logging, and can run open-source models and n8n entirely on your own servers when required.
By grounding answers in your own data with retrieval (RAG), constraining what each agent is allowed to do, testing against real cases before launch, and adding human approval for high-stakes actions. We monitor production and tune the agent as issues appear.
A focused single-task agent or n8n automation is usually live in a few weeks; a chatbot on your knowledge base or a multi-agent system integrated across several tools takes longer. We confirm the timeline after a free scoping call, once we have seen your data and systems.
It depends on the scope: the number of tasks, the systems involved and the accuracy required. After a free scoping call we give you a fixed scope and price, plus an estimate of the running cost per task for model usage, so there are no surprises.
Yes. Mirailit is based in Dhaka, Bangladesh, and most of our clients are outside Bangladesh. Projects run remotely across time zones, with published overlap hours and regular check-ins.
Tell us the job and the tools involved — we'll come back with a plan, a model recommendation and a proof of concept.