AI-native consulting firm building ML models and data pipelines for enterprise clients
Sphere operates as a consulting practice spanning strategy, data, and custom software development. The tech stack reveals a sharp pivot toward AI: heavy adoption of LLMs (OpenAI, Claude, Llama, Gemini), retrieval frameworks (LlamaIndex, Langchain), and ML infrastructure (Databricks, TensorFlow, PyTorch). However, hiring has decelerated to 3 roles in the past 30 days—a mismatch with an ambitious AI product roadmap (ML dashboards, model optimization, advanced inference). The pain-point list is heavily sales-centric (lead gen, pipeline, upsell), suggesting internal friction between technical delivery capacity and revenue growth targets.
Sphere is a 201–500-person technology consulting firm headquartered in North Miami Beach, Florida. The company provides strategy, data analytics, custom software development, and staff augmentation across Python, .NET, Ruby on Rails, Java, and Golang. Recent project work centers on ML model dashboards, NETsuite implementations, marketing automation, and process mapping for mid-market clients. The tech stack—anchored by AWS, Azure, GCP, PostgreSQL, and increasingly LLM-based tools—indicates an internal focus on embedding AI into client deliverables and internal operations.
Sphere uses OpenAI, Claude, Gemini, Llama, LlamaIndex, Langchain, Hugging Face, TensorFlow, PyTorch, and Keras. Databricks is the primary data platform for model training and inference.
Python, TypeScript, React, Kotlin, PostgreSQL, MySQL, .NET, Ruby on Rails, Java, Golang, AWS, Azure, GCP, Salesforce, HubSpot, NetSuite, and WordPress. GitHub Copilot is active for development.
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