Gupshup
Conversational AI platform for messaging — formerly Active.Ai, rebranded to Gupshup
Active.Ai (now Gupshup) is a Singapore-built conversational AI platform best for SEA retail banks, wealth managers, and digital banks that need banking-specific intent recognition trained on financial services dialogues across English, Bahasa, Thai, Vietnamese, Tagalog, and Mandarin. Its core banking integrations with Temenos, FIS, and Finastra plus MAS, OJK, BNM, BSP compliance logging make it credible for regulated environments. The trade-off is enterprise pricing of USD 6,000-80,000 per month, which rules out SME banks with under 10,000 monthly inquiries.
- ✓Banking-specific intent training beats horizontal conversational AI on banking domain accuracy
- ✓Multi-language coverage across EN, ID, TH, VI, ZH, MS, TL fits SEA retail bank footprints
- ✓Core banking integrations with Temenos, FIS, and Finastra cover dominant bank stacks
- ✓Compliance-aware conversation logging for MAS, OJK, BNM, BSP audit trails
- ✓Voice and chat channels including WhatsApp, web, mobile, IVR in one platform
- ×USD 6,000-80,000 per month enterprise pricing rules out SME banks and smaller fintechs
- ×Banking domain focus limits use for general retail or non-financial conversational AI
- ×Yellow.ai and Haptik are competitive on horizontal use cases at lower cost
- ×Implementation requires real integration work into core banking and customer service stacks
About Gupshup
Active.Ai is a Singapore-headquartered conversational AI SaaS used by SEA retail banks, wealth managers, and financial institutions for customer service automation, transaction inquiry handling, account opening assistance, and product cross-sell across web chat, mobile app, WhatsApp, and voice channels. Used by Axis Bank, HDFC Bank, OCBC, RHB Bank, and major SEA financial institutions for natural-language banking conversations across English, Bahasa, Thai, Vietnamese, and Mandarin.
Key Features
Best For
Southeast Asia Fit
Active.Ai is the Singapore-built conversational AI for SEA retail banks and financial institutions. Pricing is enterprise SaaS and typically lands at USD 6,000 to USD 80,000 per month depending on conversation volume, language coverage, and channels. For SEA retail banks handling more than 100,000 monthly customer service inquiries, Active.Ai's banking-specific intent training and multi-language coverage typically beat horizontal conversational AI (Yellow.ai, Haptik) on banking domain accuracy and on regulator-compliant conversation logging. Yellow.ai and Haptik are competitive alternatives; Active.Ai wins on banking domain depth and SEA financial institution deployment count, Yellow.ai wins on horizontal enterprise conversational use cases. For SEA SME banks under 10,000 monthly inquiries, simpler chatbot tooling is usually fine.
- Global
- SEA
- Singapore
- Indonesia
- Thailand
- Malaysia
- Philippines
- Vietnam
- Hong Kong
Integrations
- E-commerce
- Shopify
- Messaging
- LINE
- Facebook Messenger
- Telegram
- Other
- Zapier
- Zoho CRM
- CleverTap
- Salesforce Marketing Cloud
- MoEngage
- HubSpot CRM
- Salesforce CRM
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Related Analysis & Guides
The questions operators actually ask.
Is Active.Ai still a separate product?
Active.Ai has rebranded to Gupshup. The website now redirects to gupshup.ai, though the SEA banking conversational AI product positioning continues under the new brand.
Does Active.Ai handle MAS compliance?
Yes. Compliance-aware conversation logging for MAS, OJK, BNM, BSP audit trails is a listed feature, which matters for SEA regulated retail banks and digital banks under regional regulator scrutiny.
Is Active.Ai affordable for a small fintech?
No. Enterprise pricing lands at USD 6,000 to USD 80,000 per month depending on conversation volume, language coverage, and channels. SEA SME banks under 10,000 monthly inquiries are better served by simpler chatbot tooling.
Can Active.Ai replace my contact center?
Partially. The platform reduces call center volume on routine inquiries like transactions, account opening, and product information, but complex escalations and relationship-driven advisory still require human agents. Most banks run hybrid deployments.