TelecommunicationsConversational AICustomer Experience

A Leading Indonesian Telco Transforms Customer Experience with Neo, OBZ's Enterprise AI Coworker Platform

How OneByZero deployed Neo, its enterprise AI Coworker platform built on Amazon Bedrock with Anthropic's Claude Sonnet, to power 50+ automated customer journeys for one of Indonesia's largest telcos, serving 95 million subscribers.

9×

improvement in chatbot NPS, from -10 to +4 range to 36

92%

First Contact Resolution, up from approximately 55%

34%

reduction in agent ticket handling costs through automation

Overview

About the Customer

The customer is one of the largest integrated telecommunications providers in Indonesia, serving approximately 95 million subscribers across mobile, home broadband, and enterprise services. Operating in a highly competitive, multilingual market, the company manages large-scale digital and contact centre operations under multiple consumer and business brands. As part of its digital transformation strategy, the operator set out to modernise customer service and introduce AI-driven automation to improve experience, efficiency, and scalability.

The Challenge

Business Challenges

Inconsistent rule-based chatbot – The existing bot delivered inconsistent resolution quality, driving low satisfaction and heavy dependence on human agents.
Chatbot NPS of -10 to +4 – Against 4+ for other contact channels, the chatbot was actively eroding customer trust.
First Contact Resolution at ~55% – Unresolved queries drove repeated interactions, high agent handovers, and rising operational costs.
Fragmented, weakly governed journeys – Journeys were split across chat, voice, and digital, with limited Bahasa Indonesia / English support and no enterprise-grade governance.

The Solution

Solution Approach

OBZ designed and deployed Neo, an enterprise AI agent platform built natively on AWS, covering 50+ customer journeys—from sharing information and resolving product queries to recording complaints and raising service tickets. The solution leverages Amazon Bedrock as its AI platform, with Anthropic's Claude Sonnet serving as the core generative AI model, selected for the quality, consistency, and multilingual strength of its responses. Neo is structured across three layers, each with a distinct responsibility.

Layer 01 — Foundry

A data foundation, owned by platform teams. Shared, reusable knowledge made available to every agent.

• Integration with enterprise knowledge bases, APIs, and customer systems • Centralised data pipelines for conversation history, feedback, and usage signals • Retrieval-Augmented Generation (RAG) pipeline for grounded, accurate responses • Anthropic's Claude Sonnet on Amazon Bedrock, via model access and orchestration

Layer 02 — Studio

A design and journey builder where agents are built, tested, and published to production.

• Visual journey builder for chat and voice workflows • 50+ journeys: information sharing, query resolution, complaints, service tickets • Low-code configuration of intents, entity extraction, and business rules • Reusable templates via the Journey Bank, with built-in testing and preview

Layer 03 — Command Centre

Operations, quality, and optimisation, with real-time visibility across all live agents.

• Real-time performance monitoring and SLA tracking • Agent handover management and escalation controls • Integrated feedback, sentiment, and quality scoring • Usage analytics, compliance auditing, and guardrail enforcement

AWS Services Used

Built on AWS

Amazon Bedrock – Hosts Anthropic's Claude Sonnet model for conversational intelligence and streaming responses, with Bedrock Guardrails for governance
Amazon Lex – Multilingual natural language understanding for Bahasa Indonesia and English
Amazon EKS – Containerised orchestration, scheduling, execution, and observability with autoscaling
Amazon OpenSearch – Vector-based semantic retrieval for Retrieval-Augmented Generation (RAG)
Amazon RDS – Highly available transactional storage for session state and orchestration workflows
Amazon S3 – System of record for knowledge assets, campaign data, and analytics outputs
Amazon ElastiCache – Low-latency session and context caching
AWS VPC Endpoints – Private connectivity to AWS services without public internet exposure
IAM, KMS & Secrets Manager – Access control, encryption, and credential governance
CloudWatch + CloudTrail – Operational monitoring and auditability
AWS CodeBuild – CI/CD automation for controlled deployments

Outcome

Business Outcomes

9× chatbot NPS improvement, rising from the -10 to +4 range to 36
92% First Contact Resolution, up from approximately 55%
34% reduction in agent ticket handling costs
Agent handover rates declined from 32% to 20%, reducing human workload
9,500 AI-driven sessions per day now supported across the platform
Average customer engagement increased to 35 messages per session
Bot traffic increased by 29%, indicating strong customer adoption
New journeys deployed up to 50% faster using the reusable Journey Bank

About OneByZero

OneByZero is a frontier Systems Integrator specialising in AI Coworker design, build, and deployment for regulated enterprises across financial services, telecommunications, and retail. We operate across ASEAN, India, ANZ, and Japan, with a presence in the United States, combining domain expertise in regulated industries with deep AI engineering capability.