EMB Global
RAG Solutions

AI that knows what
your company knows.

We build enterprise-grade retrieval systems on top of your documents, databases, and tools, so every AI app in your business answers with citations, not guesses.

Book a knowledge audit →See RAG architecture
100M+ documents indexed5+ billion retrievals servedMulti-tenant ready
RAG diagram
Trusted across
BFSIHealthcareRetailManufacturingTelecomEdTechReal EstatePharmaLogisticsGovernmentBFSIHealthcareRetailManufacturingTelecomEdTechReal EstatePharmaLogisticsGovernment
The Problem

AI without your data
is just a guess.

Foundation models know the internet, not your business. They don't know your contracts, your policies, your products, your customers. So they make things up, and users learn not to trust them. Without retrieval, AI is a parlour trick.

01
Hallucination is a data problem
Models hallucinate when they don't know the answer. Give them the answer, and they stop.
02
Search is broken
Keyword search misses intent; vector search alone misses precision. You need hybrid retrieval and reranking.
03
Permissions are ignored
Most RAG systems leak data across users because they bolt on access control as an afterthought.
04
Knowledge goes stale
RAG isn't a one-time index; it's an ongoing pipeline. Most teams underestimate this.
RAG knowledge retrieval diagram
What We Build

Five RAG capabilities,
all production-grade.

All designed to be the knowledge backbone for your AI stack.

01

Enterprise Knowledge Assistants

Employee-facing search and Q&A across SharePoint, Confluence, drives, wikis, ticketing systems. Always cited, permissions-aware.

02

Customer Support Copilots

Agents and bots that answer with citations from product docs, policies, and past-ticket history. Cuts handle time and improves first-call resolution.

03

Sales & Marketing Intelligence

Reps query their entire knowledge base: battle cards, case studies, pricing, competitor info, all in natural language.

04

Compliance & Audit Copilots

Trace any regulation, policy, or audit finding back to source docs in seconds. Critical in BFSI, Energy, and Mining.

05

Multimodal RAG

Retrieve across text, tables, images, charts, PDFs, audio transcripts. Especially valuable when your knowledge isn't text-first.

How We Deliver

Build a knowledge layer
that scales.

RAG is deceptively simple to demo and brutally hard to operate. Our 4-phase approach gets you a production knowledge layer in 60 days.

01
1-2 weeks

Knowledge Audit

We map your sources, assess quality, identify gaps, and define the access-control model upfront.

02
3 weeks

Ingest & Index

Connectors for every source, chunking strategy tuned to your content type, hybrid index (vector + keyword), metadata enrichment.

03
2 weeks

Retrieve & Generate

Reranker, query rewriting, citation logic, fallback flows, evaluation harness with retrieval and generation metrics.

04
Ongoing

Govern & Operate

Drift monitoring, freshness pipelines, permission audits, retrieval analytics, content quality alerts.

Industries & Use Cases

Built for your industry.

Every industry has different documents, different compliance requirements, and different latency tolerances. Our RAG systems are architected for your context, not a generic one.

IndustryUse CasesOutcome
ManufacturingSOPs, equipment manuals, troubleshooting, safety procedures40% MTTR reduction
BFSIPolicy Q&A, advisor copilots, compliance lookups, regulatory tracking70% faster policy lookups
Energy & UtilitiesGrid-operation procedures, equipment manuals, regulatory standards (NERC/CEA), incident history55% faster operator lookups
Real Estate & PropTechLease and title documents, zoning regulations, due-diligence research, property-history search60% faster due diligence
Metal & MiningMine-plan documents, environmental clearances, safety procedures, equipment logs, royalty filings45% faster operations-knowledge lookups
Enterprise ITRunbooks, incident history, internal docs, vendor SLAs50% L1 ticket auto-resolution
Talk to a solutions architect →
Impact & Outcomes

What a real RAG system delivers.

Drawn from our deployments and validated against enterprise benchmarks.

0%+
Answer accuracy with citations
0%
Faster knowledge lookup vs. manual search
0%
Citation coverage on every response
50-0ms
Retrieval latency at scale
0M+
Documents indexed in a single deployment
0
Hallucinations on grounded queries (in our top deployments)
Tech Stack & Trust

Open architecture.
No lock-in.

Built on the best of open-source and enterprise tooling. No vendor lock-in.

SOC 2 Type IIISO 27001EU AI Act–readyGDPR compliant
EmbeddingsOpenAI, Cohere, BGE, E5, custom domain embeddings
Vector DBsPinecone, Weaviate, Qdrant, pgvector, OpenSearch
Graph layersNeo4j, NebulaGraph for knowledge graphs
RerankersCohere Rerank, BGE reranker, custom cross-encoders
ConnectorsSharePoint, Confluence, Notion, Drive, S3, SAP, Salesforce, ServiceNow, custom APIs
EvaluationRagas, custom retrieval/generation metrics, golden-set automation
Case Study
CASE
Spotlight: Global Bank

How a global bank reduced compliance research time by 65%.

We built a RAG layer over 200,000 regulatory documents, internal policies, and prior audit findings. Compliance officers query in natural language and get cited answers in seconds, across jurisdictions, with full traceability.

200K docs indexed65% faster research100% citationsMulti-jurisdiction

Common questions.

Chatbots talk; search returns links. RAG retrieves the right chunks AND generates a synthesized answer with citations. It's both faster and more accurate — when built right.

We embed permissions at the index level. Users only retrieve content they're authorized to see. We audit this; we don't bolt it on.

Depends on your needs. We can index in real time, hourly, or nightly. Most of our deployments use incremental indexing with change detection.

That's the norm, not the exception. We have ingestion pipelines for scanned PDFs, tables, handwriting, audio transcripts, and even legacy file formats.

Your AI is only as smart
as your retrieval.

Send us a sample of your docs. In 5 days, we'll show you a working RAG demo over them.

Request a knowledge audit →