How do AI chatbot solutions boost customer satisfaction and engagement?

AI chatbots provide instant responses to customer queries, 24/7 across multiple channels (websites, mobile apps, WhatsApp, Facebook Messenger), reducing wait times and ensuring accurate information every time. By handling routine tasks (e.g., FAQs, order status) they free human agents to focus on complex issues, improving overall customer experience, satisfaction, and loyalty. Plus, chatbots gather customer data and valuable insights that help businesses continuously optimize their support and marketing strategies.

Can chatbots deliver personalized customer interactions and tailored product recommendations?

Yes. Modern AI chatbots leverage machine learning and historical customer preferences to power personalized support, from greeting users by name to suggesting products based on past purchases. Bots can push tailored product recommendations or promotions through conversational ads and conversational commerce, driving higher sales and deeper customer engagement without manual intervention.

How do chatbots integrate with existing systems to streamline business operations?

Chatbot platforms integrate CRMs, ERPs, payment gateways, and logistics providers. For example, Bahasa.ai supports logistic integrations (JNE, JNT) and banking integrations (Bank Sinarmas, GoPay), enabling bots to automate order bookings, payment processing, shipment tracking, and invoicing, all within a single chat flow. This unified approach optimizes operational efficiency, reduces errors, and ensures a smooth customer interaction from end to end.

How do AI chatbots turn customer data into valuable insights to streamline business operations?

AI chatbots capture customer data, from past queries and preferences to interaction timestamps, across multiple channels (web, mobile apps, WhatsApp, Messenger). By applying machine learning and analytics, they extract valuable insights on common pain points, peak contact times, and product interests. These insights integrate seamlessly with CRMs and BI platforms, helping you: -Personalize customer interactions with targeted offers and tailored product recommendations -Optimize operational efficiency by automating high-volume, routine tasks (e.g., FAQs, order updates) -Align business operations and marketing strategies around real-time customer behavior -Continuously refine your AI chatbot solutions to meet evolving customer needs and boost overall customer satisfaction

AI GenAI Applications Chatbots

Top 4 Indonesia Chatbot Vendors & 7 Case Studies

Cem Dilmegani

updated on Jul 24, 2025

See our ethical norms

Indonesia had 212 million internet users by January 2025, ranking high in the Asia-Pacific for mobile adoption, with 75% of users accessing the internet via smartphones.¹

We outlined the Top 4 chatbot companies in the Indonesian market, their use cases, and their benefits.

Top 4 chatbot vendors in Indonesia

Vendor	# of employees	LLM Integration	Agentic AI & Workflow Automation
Botika	51-200	GPT-powered NLG	“Omnibotika” platform is capable of coordinating multi-step API calls, including order handling, ticketing, and tracking
Kata.ai	51-200	GenAI chatbot platform with multimodal & multilingual LLMs	Conversational “agents” that integrate voice, chat, and third-party systems
Bahasa.ai	11-50	Generative-AI modules	Action-item extraction, RAG-powered knowledge retrieval for enterprise Q&A
Chatbiz	11-50	primarily rule-based/NLP	Low-code flow builder for multi-turn processes

We gathered the top 5 chatbot companies that provide chatbot services for businesses in Indonesia. The vendors are listed according to the number of employees. We cannot compare the pros and cons of those chatbots as there are no reliable user reviews on the review platforms such as G2, Capterra, etc.

1- Botika

Some distinctive features of Botika include:

It offers chatbots that can interact in text and voice through popular messaging platforms.
Integrates GPT technology with WhatsApp.

Botika LLM and GPT-powered NLG create context-aware and human-like replies.
The Omnibotika suite allows bots to call external APIs for end-to-end transaction completion, such as handling orders, issuing tickets, and checking inventory, all without human handoffs.

Most prominent clients: Danone and UNAIDS

2- Bahasa.ai

Bahasa.ai possesses several unique attributes, which are as follows:

Supports the buying journey using GoPay, Grab, Bank Transfer, Bank VA, JNE, JNT, etc.
Easy shipping with logistic integrations
Retrieval-augmented generation (RAG) links the chatbot to enterprise knowledge bases, extracting real-time policy, product, or HR data to address employee or customer inquiries.

Most prominent clients: Bank Sinermas and Tupperware

3- Kata.ai

Kata is a conversational AI platform that offers AI technology solutions to businesses.

They develop chatbots and virtual assistants for industries such as consumer goods, financial services, healthtech, retail, and telco.
They offer text and voice channels, with LLMs fine-tuned for Bahasa and English across verticals, including retail, finance, telco, and healthtech.
The system integrates with speech-to-text and text-to-speech systems, as well as business systems (CRMs, ERPs), to automate tasks like appointment scheduling and account lookup.

Most prominent clients: Bank BRI, KFC, and Danone

4- Chatbiz

Chatbiz is a B2B chatbot startup for companies in Indonesia.

While not yet LLM-centric, Chatbiz’s low-code editor constructs branched, multi-turn flows that manage bookings, FAQ triage, and complaint tickets.
It connects seamlessly with web widgets, LINE, Telegram, and internal CRM/ERP backends for end-to-end process automation..

Most prominent clients: Bank Indonesia, ISUZU, and Kino

Figure 1. Chatbiz chatbot interacts in Indonesian

Real-life examples of chatbots in Indonesia

1- Customer services

Telkomsel’s virtual assistant, “Veronika,” utilizes Microsoft Azure OpenAI Service to manage 95% of routine inquiries from balance checks to top-ups across MyTelkomsel, WhatsApp, Facebook Messenger, LINE, and Telegram. This enables human agents to concentrate on more complex issues and reduces call-center workload by almost 50%.²

Most customer service software integrates chatbots for omnichannel support. Our vendor selection guide on customer service software explains this.

2- Banking and finance

Midtrans, a fintech company regulated by Bank Indonesia, provides payment solutions for various online businesses. Their challenge was onboarding new merchants due to poor communication and missing information on the process and simple questions. To address this, Midtrans adopted a WhatsApp chatbot, which accelerated onboarding, guided the process in Bahasa, and enabled automated ID OCR, reducing manual input.
Bank Rakyat Indonesia’s chatbot “Sabrina,” developed by Kata.ai, addresses account-balance inquiries, generates mini-statements, and can initiate card locks or loan pre-approvals through chat. This significantly reduces the turnaround time for simple banking requests and promotes self-service usage.³

To learn more about finance chatbots: Finance chatbots & tools.

3- Insurance

PasarPolis’s “Poli” assistant, which operates on Google Dialogflow Enterprise, guides users in searching for micro-insurance policies, generating quotes, and submitting claims instantly. This enables the insurtech to manage 70 million policies monthly with very little human assistance.⁴

To learn more about chatbot applications in the insurance industry: Insurance Chatbots Applications & Use Cases

4- Logistics

SiCepat Ekspres’s WhatsApp-Business (“WABA”) chatbot enables merchants to create shipment orders, produce labels, and monitor drop-point deliveries instantly, transforming a previously multi-step portal process into a streamlined series of chat interactions.⁵

5- Retail and e-commerce

Kanmo Group is an enterprise in retail distribution in Indonesia and the Indian sub-continent. They are working with the distribution of brands such as Adidas, Nespresso, etc. Therefore, their challenge involved managing customer service for various brands, addressing product-related concerns via email, and swiftly resolving customer inquiries. The company adopted a customer support automation solution that included a chatbot. As a result, the Kanmo Bot helped the company achieve a 40% increase in first response time and a 42% improvement in agent productivity.
Alfamart’s “Salma” bot, created by Kata.ai, operates on WhatsApp and Messenger. Using natural language chat, it assists customers with product promotions, store locators, and digital coupon redemptions, transforming casual browsers into paying customers without exiting the conversation.

You can learn more about retail chatbots and conversational commerce from our articles.

6- Marketing and advertising

Meeting.ai helps the Jayapura Municipal Government and APL Care managers by transcribing, summarizing, and extracting action items from online and in-person meetings. This automation of note-taking and follow-up processes allows staff to concentrate on the conversation rather than on the minutes.

You can check our marketing chatbots and sales chatbots articles for more information.

7- Travel, restaurant & hospitality

PT Kereta Api Indonesia’s avatar, “Nilam,” utilized on vertical displays at Gambir, Bandung, Yogyakarta, and Gubeng stations, leverages Azure OpenAI to respond to inquiries about ticket availability, schedule changes, cancellation procedures, and local facilities effectively assisting over 200 station visitors daily at the same time without queues.⁶

You can check our travel chatbots and hospitality chatbots articles for more information.

Business chatbots and use cases

If you want to deploy a chatbot for your business. You can check the linked articles below to learn about:

FAQ

Reference Links

Digital 2025: Indonesia — DataReportal – Global Digital Insights

Layanan Pelanggan Asisten Virtual “Veronika” di MyTelkomsel Kini Terintegrasi Teknologi Microsoft Azure OpenAI Service | Telkomsel

Media | Kata.ai

PasarPolis Case Study | Google Cloud

Sicepat expands Sicepat drop point in Logitek Digital Nusantara retail network | IDNFinancials

KAI Luncurkan Asisten Virtual Berbasis AI di Sejumlah Stasiun - Makro Katadata.co.id

Principal Analyst

Cem Dilmegani

Principal Analyst

Follow On

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 55% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE and NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and resources that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

View Full Profile