Case Studies

Context-Aware Voice AI, Proven at Enterprise Scale.

Real Deployments. Real Numbers. Measurable Outcomes in Week One.

Real client deployments — not demos. Multilingual EdTech outreach at scale, post-dispatch and NDR recovery for D2C farmers, and a context-layer blueprint for one of the world's largest banks. Each story shows how context-aware voice changes the outcome a stateless dialer would have produced.

38.7%
Connection Rate
Education Technology (EdTech)

Contextual Voice AI for EdTech at Scale

JK Shah Classes - one of India's leading CA / CS / CMA coaching institutes ran 30 outbound voice campaigns through Alchemyst AI's Voice OS, covering career guidance, parent-teacher outreach, course enrollment, feedback collection, and multilingual regional re-engagement. Across tens of thousands of calls in six Indian languages, the AI voice agents achieved connection rates roughly 2x the best-in-class AI-outbound benchmark and meaningful-conversation rates that outpaced typical EdTech organic conversion by an order of magnitude.

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41.7%
Connection Rate
AgroTech & D2C Logistics

Post-Dispatch & NDR Recovery Voice AI

Katyayani Organics - an Indian AgroTech D2C operating across rural and tier-2/3 markets deployed Alchemyst AI's Kathan Voice OS to run automated post-dispatch confirmation and NDR (non-delivery report) recovery campaigns across thousands of farmers in Hindi, Telugu, and Tamil. Across 31 campaigns over six weeks, the system held meaningful conversations with farmers at rates that outperformed AI-outbound benchmarks by ~2x and traditional outbound by more than 3x, turning a stubborn category of post-purchase loss into a recoverable revenue line.

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5
BFSI Use Cases Scoped
Banking, Financial Services & Insurance (BFSI)

Context-Aware Voice for Russia's Largest Bank

Sber is Russia's largest bank, serving roughly 100 million retail clients and millions of corporate clients across 80+ regions, with Customer Care fielding tens of millions of voice and text requests every month. Existing automation handles most simple, single-turn queries, but interactions that require persistent memory across calls still route to humans. Alchemyst AI scoped a blueprint of five Voice AI and Context Layer use cases (Russian-first, English-secondary) that add stateful memory underneath Sber's existing voice and text agents.

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4
Hospital Use Cases Scoped
Healthcare & Hospitals

AI-Augmented Patient Care Across a Multi-Campus Hospital

Dr. Mehta's Hospitals handles thousands of patient interactions daily across its Chetpet and Velappanchavadi campuses in Chennai. Alchemyst AI scoped four targeted Voice AI use cases on Kathan Voice OS, appointment reminders, post-visit recovery check-ins, test report notifications, and NPS-style patient feedback, each designed to augment existing hospital workflows rather than replace them. Every capability has been cross-checked against production deployments at JK Shah Classes (31,000+ calls, six languages) and Unacademy (14,258 NPS calls, 35.2% connection rate).

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7
Patient Care Use Cases Scoped
Healthcare & Mission Hospitals

AI-Augmented Patient Care Across Hospital, Hospice, and Rural Outreach

Bangalore Baptist Hospital serves over 440,000 outpatients and 29,000+ inpatients annually across its Hebbal main campus and two Express Healthcare satellite clinics, and runs a flagship palliative and hospice programme with five home-care teams active across four rural taluks. Alchemyst AI scoped seven targeted Voice AI use cases on Kathan Voice OS, spanning OPD appointments, post-discharge well-being, palliative caregiver support, chronic disease and dialysis adherence, lab report notifications, Community Health Division outreach across 50 villages, and NPS-style patient feedback. Each is designed to augment, not replace, existing BBH workflows.

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