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Portfolio Case Study · AI & Automation

An AI Customer-Engagement Chatbot Powered by OpenAI & Gemini

Always-on automated support and engagement — multi-model, cost-metered, and built to run for many customers at once.

OpenAI + Gemini
Multi-model
24/7
Automated support
Token
Usage metering
Multi-tenant
Per-account
Analytics
Usage insight
Django
Platform

Summary: AbedinTech built an AI customer support chatbot for automated engagement, using both OpenAI and Gemini so responses aren’t tied to a single model. Delivered on a Django platform, it comes with the production essentials: multi-tenant accounts, token-usage metering with plan limits, per-user analytics, and admin controls — automated conversations that stay helpful and cost-controlled at scale.

Project at a Glance

Project typeConversational AI · customer engagement & support
PlatformDjango web application
AI modelsOpenAI and Google Gemini
FocusAutomated support, cost control, multi-tenant delivery
OutcomeAn always-on chatbot with metering, analytics, and admin control

The Challenge

A chatbot demo is easy; a dependable support assistant you can put in front of real customers is not:

Answers must be helpful and on-brand.

Automated support only works if the responses are actually useful and consistent with the business’s voice.

AI usage has to be metered.

A chatbot that talks all day burns tokens. Usage has to be tracked and capped per account to protect margins.

One model is a single point of failure.

Relying on a single provider risks outages, price changes, and quality drift. Multi-model support is insurance.

The Solution

Multi-model conversational AI

The chatbot answers using either OpenAI or Gemini, so the business isn’t locked to one provider and can route for quality or cost.

Token metering & plan limits

Every conversation’s token use is tracked per account and enforced against plan limits, keeping support costs predictable.

Multi-tenant delivery

Built so one platform can serve many customers, each with isolated accounts, usage, and settings.

Analytics & admin control

Per-user analytics show usage and engagement, while an admin panel manages plans, API keys, and access.

Architecture & Engineering

The chatbot runs on a Django platform with role-based access and a token-accounting layer that spans both OpenAI and Gemini, feeding analytics and plan enforcement. A dual API-key model lets administrators provision keys centrally or let customers bring their own — the same engineering foundation that powers AbedinTech’s broader AI automation platform, focused here on conversational support.

Results & Impact

Always-on engagement — automated support that responds instantly, around the clock.
Costs under control — token metering and plan limits keep AI spend predictable.
Resilient & flexible — multi-model support avoids single-vendor lock-in.

Technology Stack

Python Django OpenAI API Google Gemini API

Want an AI chatbot for your business?

AbedinTech builds AI chatbots and support assistants with metering, analytics, and multi-model flexibility. Get a proposal.

Frequently Asked Questions

What can an AI customer support chatbot do?

It can answer customer questions instantly around the clock, handle routine support conversations, and engage visitors — reducing load on human agents. This one uses both OpenAI and Gemini and runs on a multi-tenant platform with usage metering and analytics.

Why use both OpenAI and Gemini?

Supporting multiple models avoids single-vendor lock-in — it provides resilience against outages, flexibility on cost and quality, and the ability to route requests to whichever model fits best.

Can AbedinTech build a custom AI chatbot for my business?

Yes. AbedinTech builds AI chatbots and support assistants with multi-model AI, token metering, per-account analytics, and admin controls — tailored to your product and brand voice.

Related service: Explore AbedinTech’s AI Chatbot Development services.