Plug Tensorplay Into Your Existing AI Stack
We don't replace your stack — we make it production-ready. Whether you're running on AWS or GCP, using OpenAI or open-source models, Pinecone or pgvector, we meet you where you are and build the infrastructure that makes it all reliable at scale.
Anthropic
Build reliable, safe, and high-quality AI applications powered by the Claude model family — with the engineering infrastructure to make them production-grade.
Aws
Deploy production AI systems on AWS — from SageMaker model hosting and Bedrock foundation models to EKS GPU clusters and Lambda-powered serverless inference.
Huggingface
Access thousands of open-source models — LLMs, embedding models, vision models, and more — and deploy them in production-grade inference pipelines on your own infrastructure.
Langchain
Build sophisticated AI orchestration workflows — RAG pipelines, multi-agent systems, and complex chains — on a solid production engineering foundation.
Openai
Build production-grade applications powered by GPT-4o, GPT-4 Turbo, o1, and the full OpenAI model suite — with enterprise-class reliability, streaming, and cost controls baked in.
Pinecone
Build production RAG systems and semantic search applications on top of Pinecone's fully managed vector database — with proper data architecture, indexing strategy, and cost management.
Ready to scale your AI from 'Demo' to 'Deployed'?
Contact UsStop settling for prototypes that break under pressure. Join forces with Tensorplay to harden your infrastructure, optimize your models, and deliver enterprise-grade AI experiences that actually perform.