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Sarana AI

Human + AI agents for Indonesia's next decade of work.
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California, United States
11-50 employees

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Company Description

Sarana AI is an Indonesia-native software company focused on workforce augmentation, building practical AI agents that take ownership of repetitive, rules-based work so people can focus on higher-value judgment and relationships. As part of the FDS-PAC Group, the company serves public and private sector organizations across 12+ industries, with domain-tuned agents spanning HR and Talent, Compliance and Risk, Operations and Supply Chain, and Customer and Commercial functions. Its product family includes Recruitment AI for screening CVs at scale and running structured video assessments; QUARC for continuously monitoring OJK, BI, and other regulatory changes and mapping their impact to SOPs; Kala for ML-powered demand forecasting and automated reorder suggestions; Netra for extracting and reconciling data across invoices, POs, and delivery notes; Omni for omnichannel customer service on WhatsApp, email, and web chat; and Semesta, the orchestration backbone that connects documents, systems, and agents into end-to-end workflows. Sarana AIs engagement model is designed to de-risk adoption and prove value fast: a discovery and alignment phase to pinpoint the highest-impact workflow, a pilot agent build with clear KPIs and guardrails, a shadow run with tight iteration, and then scale and productization across adjacent processes. Typical outcomes include a 30-day proof of concept with measurable results before full commitment, 1540% cost reductions in targeted workflows, 25x revenue per employee uplift in sales, service, or processing roles, and a minimum $100K+ annualized P&L impact per engagement. With sector-specific playbooks for banking and financial services, insurance, healthcare and hospitals, retail and ecommerce, manufacturing and mining, logistics and supply chain, education, and the public sectorand compliance tuned to Indonesian regulators like OJK, BI, and BPOMSarana AI delivers agents that are context-aware, auditable, and built to scale from the first use case.

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