Patent and scientific literature analytics using AI and big data
SciTech Patent Art extracts insights from patents and scientific literature for Fortune 500 clients using Python, TensorFlow, PyTorch, and generative AI (ChatGPT, DALL-E, Langflow). The stack reveal—heavy ML infrastructure paired with design tools (Figma, Sketch, Photoshop) and presentation layers (PowerPoint, After Effects)—suggests a research-to-deliverable workflow optimized for visual legal and competitive analysis. Steady hiring across engineering, design, and legal roles reflects scaling of both technical delivery and client-facing output.
SciTech Patent Art is a research analytics firm based in Hyderabad that specializes in patent search, analysis, and landscape development for large corporations across the US, Japan, and Europe. The firm serves Fortune 500 clients across Oil & Gas, Consumer Products, Electronics, Telecommunications, Automotive, and other sectors, with a practice spanning freedom-to-operate assessments, licensing opportunity analysis, and competitive IP intelligence. Work centers on three core streams: legal presentations for court proceedings, patent landscape mapping, and competitive intelligence tracking. The company has operated since 2002 and operates primarily in India with client-driven hiring.
Python, TensorFlow, PyTorch, Hugging Face Transformers, and Langflow for analytics; ChatGPT and DALL-E for AI-driven insights; AWS, Azure, and GCP for infrastructure; Figma, Sketch, Photoshop, and After Effects for design and presentation output.
Patent search, analytics, and landscape development; freedom-to-operate and infringement analysis; technology due diligence; licensing opportunity analysis; and competitive intelligence. Primary clients are Fortune 500 firms across multiple industries including automotive, consumer electronics, and energy.
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