Your Enterprise AI – Private, Governed, Running on AWS
Sphere builds production-grade GenAI applications on AWS Bedrock and SageMaker – RAG pipelines, fine-tuned foundation models, AI agents, and LLMOps infrastructure – with enterprise security, compliance, and governance built in from day one. Move from AI pilot to AI production.
Trusted by Leading Enterprises
Why This Matters Now
Enterprise AI projects have an alarming failure rate: 87% of AI pilots never reach production. The causes are consistent – models that hallucinate on enterprise data, security and compliance gaps that block deployment, lack of LLMOps infrastructure for monitoring and retraining, and AI teams that are exceptional at model research but don’t have production engineering experience.
1. Hallucination Destroys Enterprise Trust in AI
General-purpose LLMs like GPT hallucinate on domain-specific enterprise data at rates of 15–40%. In legal, healthcare, and financial applications, a single wrong answer can cost millions.
2. Security Blocks Production Deployment
Enterprise data cannot be sent to OpenAI APIs without carefully designed privacy architecture. Most AI prototypes are built without production-grade security – and never get cleared by InfoSec.
3. No LLMOps = Model Decay
Without monitoring, retraining pipelines, and model versioning, GenAI applications degrade silently as data distributions shift – with no mechanism to detect or address the decay.
What Sphere Delivers
Sphere’s GenAI practice builds on AWS Bedrock’s private, VPC-isolated model hosting and SageMaker’s ML lifecycle management – ensuring enterprise data never leaves your AWS environment, models are continuously monitored and improved, and every deployment meets your security and compliance requirements.
Built On Industry-Leading Technology
Built on AWS’s core GenAI and machine learning stack, Sphere delivers production-ready systems for retrieval, orchestration, model operations, and monitoring. This technology foundation supports secure enterprise use cases end to end — from knowledge-based assistants and AI agents to fine-tuned models, API integrations, vector search, and ongoing performance control in production.
Who This Is For
INDUSTRY
VERTICAL APPLICATION
Get Your Free GenAI Readiness Assessment
Take Sphere’s 15-minute GenAI Readiness Assessment. Our senior AI architects will evaluate your data infrastructure, use case viability, and security posture – and deliver a custom GenAI roadmap within 48 hours. No cost, no obligation.
How It Works
Readiness Assessment
2-week assessment of data infrastructure, security posture, use case viability, and team capabilities.
Architecture Design
Design RAG pipeline, model selection, security architecture, and LLMOps framework.
MVP Development and Hardening
Build and validate core GenAI application – typically 6–8 weeks to working prototype on your data. Then, performance optimization, guardrail configuration, and compliance validation.
LLMOps & Handoff
Deploy monitoring, retraining pipeline, and handoff to internal team with full documentation and training.
ROI & Bussines Impact
Enterprise GenAI applications built by Sphere achieve average ROI of 8–15x within 12 months. Knowledge management applications reduce employee time spent searching for information by 60–70% (saving $500K–$2M/year for large organizations).
Customer service AI reduces support costs by 35–55% while improving CSAT. Code generation tools improve developer productivity by 20–35%.
Let’s Connect
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Flexible, fast, and focused — Sphere solves your tech and business challenges as you scale.
Luke Suneja
Client Partner
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