Your data.
Your AI.
Zero compromises.
Deploy a private AI knowledge base on your own infrastructure in 6–8 weeks. Your Retrieval-Augmented Generation pipeline runs on your documents, your LLM, your compliance rules — without sending a byte to a third-party server.
No slides. Live walkthrough on your use case.
Organizations around the world trust us
Generic AI doesn't know your business
LLMs are powerful — but they're missing the one thing that makes your company unique: your data. Here's what happens when AI runs without it.
Hallucinations & inaccurate answers
Without your data, models fabricate answers, cite wrong policies, and erode employee and customer trust at scale.
Fine-tuning is cost-prohibitive
Training a custom model on your data costs hundreds of thousands of dollars and is obsolete the moment your data changes.
Direct connections create security risk
Connecting your data directly to third-party LLM platforms exposes proprietary information and creates compliance nightmares.
RAG: AI that retrieves before it generates
Instead of guessing, Sphere's solution retrieves the exact, current information from your data sources — then generates precise, grounded answers. Every time.
What is Enterprise RAG?
Enterprise Retrieval-Augmented Generation — or simply RAG — is an AI architecture that connects a large language model to a company's proprietary data, and runs entirely within the customer's security perimeter rather than exposing data to external providers.
Key distinctions include data isolation, permission enforcement, and source citations for verification — the same differences that separate private RAG from cloud RAG like ChatGPT Enterprise.
Full RAG Architecture
Connects to your existing data sources
Enterprise-grade, end to end
Four integrated layers — interfaces, platform, data integration, and your sources — all deployed within your private cloud or on-premise environment.
Fully deployed on your private cloud or on-premise — no data ever leaves your environment.
What you get with Sphere RAG
Eliminate hallucinations
Every answer is grounded in retrieved, verifiable content from your data — with source citations your teams can trust.
Real-time, always current
No retraining needed. As your data changes, answers update automatically — no stale AI, no maintenance windows.
Full data sovereignty
Everything runs within your private cloud or on-premise environment. Your data never touches third-party servers.
Any LLM, any model
Works with GPT-4, Claude, Llama, Mistral, and any future model — you're never locked into a single provider.
Role-aware responses
Permission-aware RBAC ensures each employee only sees what they're authorized to see — enforced at the retrieval layer.
Fraction of the cost
RAG costs a fraction of fine-tuning or custom model training, with faster time-to-value and no retraining overhead.
Built for every team, every industry
Sphere RAG adapts to your workflows — from customer support to engineering, sales to compliance.
Instant policy answers
Support agents get precise answers to complex policy questions drawn directly from your internal documentation — no tab-switching, no delays.
Customer-facing AI assistant
Deploy a public chatbot powered by your product knowledge base that gives accurate, on-brand answers 24/7 — without hallucinating.
Ticket resolution acceleration
Automatically surface relevant past tickets, runbooks, and escalation guides to reduce average handle time significantly.
Multilingual support
Combine your proprietary knowledge with LLM translation capabilities to serve global customers in their native language — accurately.
Enterprise security is not an add-on. It's the foundation.
Sphere has full security and governance infrastructure already in place — from role-based access control to audit logging and PII masking. We built this for enterprise from day one.
Certifications & Compliance
Deployment Options
Supported LLMs
From kickoff to production in weeks, not months
Sphere's proven deployment process removes the guesswork. We've refined every step across 5+ successful enterprise deployments.
Deployed. Proven. Delivering ROI.
Our enterprise customers share what changed when their proprietary data met AI.
Sphere's platform provided true role-based access control (RBAC), enterprise AI governance, and configurable AI guardrails that enabled us to securely scale Retrieval-Augmented Generation (RAG) use cases across the organization with confidence. Their ability to support private cloud deployment, secure AI architecture, and enterprise-grade governance capabilities was ultimately the deciding factor for us.
The business case for Sphere's enterprise RAG solution was clear from the start. We replaced a projected $400K AI model fine-tuning initiative with a secure Retrieval-Augmented Generation (RAG) solution deployed in just six weeks. Unlike traditional fine-tuned AI models that quickly become outdated, Sphere's RAG architecture continuously stays current as our enterprise data evolves — without the cost and operational overhead of retraining models. The combination of rapid deployment, lower AI implementation costs, secure enterprise integration, and real-time access to trusted organizational knowledge was the true differentiator for us.
Sphere's enterprise RAG solution transformed how our support team accesses and delivers critical knowledge. Our teams can now answer complex policy and compliance-related questions in seconds instead of minutes, dramatically improving operational efficiency and response times. The improvement in AI answer accuracy, consistency, and knowledge retrieval quality was immediate and measurable. Sphere's Retrieval-Augmented Generation (RAG) platform enabled us to provide faster, more reliable support experiences while ensuring responses remained grounded in trusted enterprise data.
Common questions
Turn your data into your AI advantage
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