AI Knowledge Assistant & RAG Services

Your AI doesn't know your business. Ours does.

Sphere builds custom RAG development and AI knowledge assistants connected to your real documents — every answer comes with a citation, not a guess.

4.9

“These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.”

Lee Ebreo, VP of Engineering, CreditNinja

Launch Your Intelligent RAG Solution

Your project details are 100% protected by NDA · a Sphere engineer responds within 1 business day.

Regulated industry? Compliance is built in, not bolted on.

GDPR data governance, legal document AI, healthcare knowledge management, and document compliance AI — designed into every regulated-industry RAG deployment, including RAG for financial services and RAG for compliance.

Talk to Us About Compliance-Ready RAG →

Build an Intelligent RAG System That Actually Knows Your Enterprise Knowledge

AI Knowledge Assistant & RAG Chatbot

A technician asks "What AHU serves Cleanroom Suite 204?" — the AI knowledge assistant answers in seconds, with a citation, not a guess.

Technical knowledge assistants
Internal help-desk automation
Policy & procedure guidance

Custom RAG Development & LLM RAG Services

Hybrid vector + keyword retrieval and a tamper-evident audit trail, from architecture to production.

Data prep & document ingestion
Retrieval pipeline engineering
Vector database integration

Enterprise Search AI & Knowledge Management

Turn scattered drives and legacy systems into one enterprise search platform with document intelligence AI.

Document intelligence AI
Citation-backed answers
Role-based access control

RAG Analytics & Insights Platforms

Retrieval-backed dashboards and reporting that cite their sources instead of guessing.

Self-service reporting
Governance & security controls
Compliance-grade audit trails

Trusted By

Empowering enterprise leaders and regulated industries to put AI on their real data — not a demo.

Client Organizations Served

Countries

Net Promoter Score (2026)

$0B+

Client Revenue Impacted

Your Innovation Partners From Strategy to Production and Beyond

Real clients, real engagements — not stock testimonials.

Ben Crawford

Senior Product Manager, Enova Financial

Sheldon Gilbert

CEO, Proclivity Media

John Krauze

VP of Product, Nextcapital

Featured Awards

96% client retention. 21+ years of enterprise engineering.

TOP AI CODE GENERATION COMPANY UNITED STATES 2025

TOP AI TEXT GENERATION COMPANY FLORIDA 2025

TOP APP DEVELOPMENT COMPANY MANUFACTURING 2025

GLOBAL RECOGNITION AWARDS 2026

TOP ARTIFICIAL INTELLIGENCE COMPANY UNITED STATES 2025

TOP CHATBOT COMPANY UNITED STATES 2025

TOP RECOMMENDATION SYSTEMS COMPANY UNITED STATES 2025

Document research that took 6 hours now takes seconds.

A real, verified result from a live Sphere RAG deployment — AI document search enterprise-wide, replacing point enterprise search products with enterprise RAG compliance built in.

Speak to Our AI Experts

Technologies We Leverage

We Work With Your AI Stack

Built on the infrastructure you already run — no forced replatform. A generative AI development company delivering LLM integration development and retrieval augmented generation services into your existing enterprise search platform, enterprise search software, or enterprise search engine.

LLMs & Frameworks

OpenAI GPTClaudeMistralLlama 3GeminiMixtral

Vector Databases

PineconeWeaviateFAISSMilvusChromaElastic

Data & Storage

SnowflakeDatabricksPostgreSQLAzure Cognitive Search

Pipelines & Orchestration

LangChainLlamaIndexHaystackPrefectAirflow

Infrastructure

AWS BedrockAzure OpenAIGoogle Vertex AI

Case Studies

RAG Solutions Accelerating Real Business Outcomes

Financial Services / Tax AdvisoryEnterprise RAG

From Six Hours to Seconds: Enterprise RAG for a Leading International Tax Advisory Firm

Client identity withheld at their request — results independently verified by Sphere.

CHALLENGE

FATCA, FBAR, treaty law, and multi-jurisdictional guidance scattered across shared drives, a legacy document system, and email. Advisors spent an average of six hours per engagement on document research alone.

SOLUTION

A production enterprise RAG system with hybrid vector + keyword retrieval, jurisdiction-aware metadata filtering, role-based access control, and a tamper-evident audit trail — live in 5 weeks, built with Sphere's Precision-Driven Engineering™ methodology.

6h → sec

Document research per engagement

+66%

Retrieval accuracy vs. prior keyword search

5 wks

Kickoff to production

>99.9%

Research time reduction, measured live

“Sphere deployed a production-ready RAG pipeline in five weeks. Document retrieval accuracy improved by 66% compared to our previous keyword-based search. Most strikingly, the time our advisors spend on document research dropped from an average of six hours per engagement to seconds.”

— Managing Partner, international US tax advisory firm (name withheld at client's request; quote verified by Sphere)

Explore Full Case Study →

Life Sciences / GxP Facilities (anonymized)

“The question that used to take 45 minutes now takes 9 seconds — even inside a cleanroom.”

45 min → 9 sec

60–80% search time reduction · 3–5x documentation utilization

Hospitality & Entertainment Operator (anonymized)

“Engineering drawings and manuals turned into a conversational, fully traceable knowledge platform on Azure.”

60–80%

Search time reduction · 20–30% technician productivity increase

PetroLedger (named client)

“AI-powered Digital Twin Knowledge Platform solving institutional knowledge loss ahead of a retirement wave.”

120% faster

Onboarding: 8–12mo → 3–5mo · $1.2M/yr saved · 100% regulatory adherence

Industries Sphere Serves

RAG for Enterprise Across Regulated and High-Stakes Industries

A custom RAG solution provider and AI consulting firm for enterprise RAG solutions and AI knowledge bases across every regulated vertical.

Financial Services / Fintech

Energy / Oil & Gas

Healthcare / Life Sciences

Insurance / Open Banking

Construction / Manufacturing

Retail / eCommerce

SaaS / Entertainment Tech

Telecommunications

Entertainment / Hospitality

Private Equity / M&A

Related Insights

Explore Our Insights on RAG Development

Article · May 2026

The 12 Best Enterprise RAG Platforms and Tools in 2026 — A Compliance-First Comparison

Scored on retrieval quality, deployment flexibility, sovereignty, and EU AI Act readiness.

Article

How RAG Works in Enterprise AI — And Why Your Knowledge Base Architecture Determines Answer Quality

Why chunking strategy and retrieval architecture decide whether RAG actually works for your documents.

Article

Why Enterprise AI Gets Your Company-Specific Questions Wrong

Microsoft Research found ~80% accuracy on complex enterprise queries with RAG vs. ~50% without.

Frequently Asked Questions

Retrieval-Augmented Generation grounds AI answers in your actual documents and data, with citations — instead of relying on a model's general training, which can be outdated or simply wrong for your specific business context.

Our fastest verified production deployment took 5 weeks from kickoff, using our Precision-Driven Engineering™ methodology. Typical enterprise builds run 6–8 weeks depending on data complexity and integration scope.

In your own cloud environment — AWS, Azure, or GCP. Sphere does not require your data to leave your infrastructure.

Yes. Sphere builds RAG with role-based access control, audit-grade logging, and architectures aligned to GDPR, HIPAA, and SOX from the design stage — not added after launch. Our tax-advisory case study includes a tamper-evident audit trail built in from day one, the same pattern we apply for healthcare and financial services clients.

No — Sphere works across OpenAI GPT, Claude, Mistral, Llama 3, Gemini and Mixtral, and across Pinecone, Weaviate, FAISS, Milvus, Chroma and Elastic, so you can swap components as the AI landscape evolves.

Both are possible. Some clients want ground-up enterprise AI development and a new knowledge base AI for enterprise; others want their existing enterprise search tools and knowledge management AI kept in place, with RAG added as a layer on top. Sphere scopes an enterprise RAG implementation around what you already run, not a forced rebuild.

A generic LLM answers from general training data and can hallucinate specifics about your business. RAG grounds every answer in your real, current documents, with a citation trail your team can verify.

Get a Free RAG Assessment

Tell us about your data and use case — a Sphere engineer will map out feasibility, timeline, and architecture before you commit to anything.

A Sphere engineer responds within 1 business day · your data stays in your cloud.

4.9

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