Vamana offers an AI‑native video infrastructure that combines edge capture, hardware‑accelerated inference, and cloud distribution into a single platform. Its API‑first service lets developers ingest video streams, run real‑time computer‑vision models, and deliver adaptive bitrate streams without managing separate encoding, inference, or CDN components, reducing latency and bandwidth costs.
Funding
Funding not disclosed
Founders
Product
Problem
Current video processing pipelines rely on fragmented, on‑premise hardware and generic cloud services that are not optimized for AI workloads, leading to high latency, excessive bandwidth costs, and limited scalability for real‑time computer‑vision applications.
Solution
Vamana provides an AI‑native video infrastructure that integrates edge capture, AI inference, and cloud distribution into a unified platform. Video streams are ingested at the source, processed with hardware‑accelerated neural networks for tasks such as object detection, segmentation, and analytics, and then delivered via adaptive streaming to downstream applications. The platform abstracts the underlying compute and networking layers, allowing developers to deploy AI video pipelines without managing separate encoding, inference, or CDN services. Vamana’s API‑first design enables seamless integration with existing media workflows while delivering lower latency and reduced data transfer through on‑the‑fly processing.
Target Audience
Primary customers are developers and product teams building real‑time video analytics, surveillance, autonomous‑vehicle perception, and interactive media applications that require integrated AI processing at scale.
Features
- Real‑time AI inference engine with GPU/TPU acceleration built into the video ingest path
- Edge‑to‑cloud orchestration that routes streams to the optimal processing node based on latency and bandwidth constraints
- Adaptive bitrate streaming combined with AI‑driven content-aware encoding to minimize bandwidth while preserving analytical fidelity
- Unified REST and gRPC APIs for ingest, model deployment, and output delivery, supporting popular video formats and protocols
- Built‑in model management allowing versioned deployment of custom computer‑vision models without service interruption
- Scalable, pay‑as‑you‑go cloud backend that auto‑provisions compute resources to match stream volume