Research areas
We study six areas of AI to help teams understand information, automate useful tasks, and make better decisions. Each area below explains the problem we work on.
Core AI
Teach computers to learn from examples, find patterns, and make better predictions.
3 focus clusters
Language & Reasoning
Help AI understand documents, answer questions using your information, and support everyday tasks.
4 focus clusters
Vision & Multimodal
Help AI understand images, video, and text together—for tasks such as reading documents or inspecting objects.
4 focus clusters
Data Intelligence
Turn scattered data into useful insights, forecasts, and early warnings your team can act on.
4 focus clusters
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AI Engineering
Turn AI prototypes into reliable applications, then monitor and improve them as people use them.
4 focus clusters
Trustworthy AI
Test AI for mistakes and unfair results, protect private data, and keep people in control of important decisions.
4 focus clusters
Publications
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Research team
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Research area
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Newest -> Oldest
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Aug 18, 2026
Evaluating Retrieval-Augmented Intelligence for Indonesian Enterprise Workflows
A practical evaluation framework for retrieval quality, answer grounding, latency, and human trust in internal knowledge systems.
Language & Reasoning
Jul 29, 2026
Early Warning Signals from Public Data Streams
How weak signals from news, social media, geospatial feeds, and market events can be structured into decision-grade alerts.
Data Intelligence
Jun 11, 2026
Responsible AI Deployment Patterns for Regulated Teams
Deployment patterns for audit trails, guardrails, model monitoring, bias checks, and human escalation in high-stakes workflows.
Trustworthy AI
Foundation Models
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→
DS
↗ Arutala v.1.0
Baseline Indonesian reasoning model for analytics, summarization, and workflow assistance.
DS
↗ Arutala v.1.5
Improved instruction-following and retrieval behavior for enterprise knowledge tasks.
DS
↗ Arutala v.2.0
Next-generation multimodal and long-context research foundation for decision intelligence.
DS
↗ Aruna v.1.0
Compact model family optimized for efficient deployment and domain-specific assistants.
Gen AI
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→
DS
↗ Gaksara v.1.0
Generative language system for structured content, research drafting, and multilingual business workflows.
Fundamental Algorithm
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→
DS
↗ IndoLLNet
Low-resource Indonesian language network for robust classification, extraction, and linguistic representation.
DS
↗ BioBNet
Biomedical and public-health representation algorithm for entity signals, literature, and clinical-adjacent data.
Let's move forward
YOGYAKARTA · CENTRAL JAVA · BALI