AI / Solutions
Customer Service AI.
The bar for customer service AI in Indonesia is already high. Kata.ai is resolving 50 million conversations a month at 81% first-contact. Telkomsel has AI at 800+ service points. If your contact center is still routing every message to a human, you are both over-staffed and under-serving your customers. We build customer service AI that resolves, on WhatsApp, in Bahasa and regional languages, wired to your policy, payment, and account systems.
Your customers are on WhatsApp. Your service is built for email.
Most Indonesian contact centers are still running the motion they built for phone calls, with WhatsApp and webchat bolted on top. The result: every customer interaction becomes a human interaction, even the ones that didn't need to. We rebuild customer service as a resolution engine, AI on the first touch for intent detection, context lookup, and action; humans on the interactions that actually need judgment. We measure on resolution rate and customer sentiment, not containment.
How we ship customer service AI that resolves
Four phases from your worst support queue to a resolution system your CSAT graph respects.
Discover
We map the conversations. Ticket logs, call recordings, WhatsApp threads. We cluster by intent, effort-to-resolve, language, and outcome. We identify which intents AI can close, which need humans in the loop, and which you'd lose customers over if you automated. For financial services, OJK April 2025 guidance applies.
Pilot
A six-week pilot on a bounded intent space, one product line, one support category, or your top three contact drivers. Bahasa-native, tool-wired, with fallback to your human team. Pass/fail on resolution rate, sentiment, and handoff quality.
Validate
Evaluation harness: resolution accuracy, tone calibration, bias checks across languages, refusal quality, escalation handoff metrics. Red-teaming in Bahasa and regional languages. Documentation for OJK or UU PDP where applicable. Sentiment sampling on production traffic.
Scale
Handover to your ops and IT. Your team gets the runbook, the monitoring dashboards, the intent-expansion process, and the handoff-quality metrics. New intents and new languages added as modules.
What we build
Four disciplines that together convert a contact center into a resolution engine.
Intent Detection & Context Retrieval
Multi-label intent classification tuned to Bahasa and regional-language input. Customer context pulled via RAG from policies, tickets, and account data, permission-scoped per your org's access rules.
Tool Calling to Backend Systems
The difference between a chatbot and a resolution system. Live integration with your policy engine, payment system, ticketing, account system, appointment booking, order tracking, whatever the resolution actually requires.
Warm Handoff & Agent Context Panel
When AI hands off, it hands off prepared. Agent context panel pre-filled: customer profile, conversation summary, AI's proposed resolution, sentiment cues, suggested next action. Your human agents arrive briefed.
Resolution Measurement & Compliance Logs
We measure what customers experience, first-contact resolution, sentiment, handoff quality, re-contact rate, not containment. Every conversation logged for UU PDP data-subject requests; for financial services, logged to OJK audit standards.
Customer service AI in action
The bar is set, the scale is proven, the regulator has drawn the line.
50 million Indonesian conversations resolved monthly at 81%
Kata.ai's platform handles more than 50 million Indonesian conversations monthly, resolving 81% at first contact across major brand deployments. The benchmark is set, the question isn't whether Bahasa-native customer service AI can resolve at scale; it's whether yours does.
AI rolled out across a national telco's physical frontline
Telkomsel deployed AI Digital Smart Care across more than 800 GraPARI service points, winning IDC's 2024 Best Future Customer Experience award. When a national telco puts AI at the physical frontline at this scale, the question for competitors shifts from whether to deploy, to how well.
Financial-services customer service AI is now governed
OJK's April 2025 AI Governance Guidance covers AI systems in financial-services customer interactions. Bias testing, audit trails, and human oversight on high-risk decisions now apply. For banks and insurers, customer service AI is governed, not optional.
What's trending in customer service AI
View all insights →
Orkestrasi Strategis Melalui Ekosistem Kecerdasan Artifisial untuk Ketahanan Bisnis Global
Analisis strategis mengenai ekosistem kecerdasan AI dalam mengintegrasikan sistem otonom untuk memperkuat fundamental dan efisiensi operasional bisnis.
How to Move from Customer Deflection to Full Resolution on WhatsApp
Learn how to transition your enterprise contact center from customer deflection to full resolution on WhatsApp by integrating conversational AI with core transactional systems.
Building a Resilient Enterprise Cognitive Automation Infrastructure for the Indonesian Market
A comprehensive analysis of how an Enterprise Cognitive Automation Infrastructure integrates claims, accounts payable, healthcare, customer service, and fraud systems.
Which customer interaction is costing you the most agent hours?
Tell us the top three contact drivers, the repeated question, the status check, the booking change, the claim query, the complaint intake. We'll scope a six-week pilot on real conversations with real metrics: resolution rate, sentiment, handoff quality.
Start a project