Enterprise AI for document processing and intelligent automation in regulated industries
Scry AI builds conversational AI and intelligent document processing platforms for finance, insurance, healthcare, and logistics. The tech stack reveals a hybrid approach: RAG + LangChain + OpenAI for NLP and conversational layers, paired with PyTorch + TensorFlow + OpenCV for computer vision—indicating active work across document extraction, data querying, and edge-based vision pipelines. Hiring is accelerating across ops and product (8 roles combined), signaling scaling of go-to-market and platform capabilities alongside infrastructure demands.
Scry AI is a San Jose-based enterprise AI company founded in 2014, operating at 201–500 employees and serving highly regulated verticals. The product line centers on three platforms: Auriga (conversational AI for multilingual querying across structured and unstructured data with source traceability), Collatio (intelligent document processing for template-free extraction and reconciliation), and domain-specific automation for insurance, lending, and compliance workflows. All products carry SOC 2 and ISO 27001 certifications. Active projects span document validation systems, real-time vision pipelines, and edge deployment of CV models, paired with insurance and loan-processing automation. The organization is addressing compliance gaps and complex process documentation—core friction points in their target segments.
Python, PostgreSQL, MongoDB on AWS. For AI/ML: OpenAI, RAG, LangChain, PyTorch, TensorFlow, OpenCV. Visualization: Tableau, Power BI, Looker. Frontend: React, TypeScript. Infrastructure: Docker. Vision hardware: NVIDIA Jetson, Raspberry Pi.
Currently hiring in India alongside the US headquarters in San Jose, California.
Scry AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.