All Practice Areas/Enterprise AI & Knowledge Engineering
Enterprise AI & Knowledge Engineering

Enterprise RAG, Vector Search & Private Knowledge Bases

Transform messy corporate PDFs, databases, and tickets into private, hallucination-free AI search.

We build enterprise Retrieval-Augmented Generation (RAG) and semantic vector search engines that allow your employees or customers to query thousands of private corporate documents with sub-second latency and zero data leakage.

Guaranteed Standards
Enterprise SLA & IP
Private VPC & Zero Data Leaks100%
Average Retrieval Latency< 450ms
Fact-Grounded Citation Score99.2%
Documents Indexed at ScaleMillions
100% IP & Git Repository Ownership
STRATEGIC OVERVIEW

Instant, cited answers grounded entirely in your verified corporate truth.

Generic LLMs hallucinate answers, lack domain-specific enterprise context, and cannot access the internal documentation, legal contracts, and ERP data where your company’s real value lives.

Cognopex engineers institutional Retrieval-Augmented Generation (RAG) systems. We build robust ETL ingestion pipelines, chunk documents semantically, generate dense vector embeddings, and implement hybrid search (sparse BM25 + dense vector embeddings + reranking models) to guarantee cited, fact-accurate answers.

Measurable Client Outcomes

Query millions of internal PDFs, customer tickets, standard operating procedures, and SQL records in real time.
Every answer includes direct clickable citations pointing to the exact page and paragraph of the source document.
Role-Based Document Access Control: employees only receive answers from documents their security clearance allows.
Complete privacy: deployed entirely on your private VPC using pgvector, Qdrant, or Pinecone with private LLM endpoints.
CORE CAPABILITIES

Production modules engineered to specification.

Every deliverable is backed by automated tests, comprehensive documentation, and production runbooks.

Hybrid Vector & Semantic Search Engines

Module 01

Advanced search combining keyword frequency (BM25) and dense embeddings with cross-encoder re-ranking for pinpoint contextual retrieval.

Included Deliverables:
Qdrant / pgvector / Pinecone Clusters
Hybrid Search (Keyword + Semantic)
Cross-Encoder Re-Ranking Pipeline
Sub-450ms Latency Tuning

Automated Document Ingestion Pipelines (ETL)

Module 02

High-throughput document processors that ingest messy PDFs, Word docs, spreadsheets, and scanned contracts, preserving tables and figures.

Included Deliverables:
Vision OCR & Table Extraction
Semantic Document Chunking
Automated Metadata Tagging
Scheduled Incremental Ingestion

Role-Based Access Control (RBAC) RAG

Module 03

Enterprise permission filters ensuring an employee or client only retrieves data from files they are authorized to view.

Included Deliverables:
Metadata-Filtered Vector Queries
Active Directory / Okta Auth Sync
Multi-Tenant Partition Isolation
Full Query Audit Logging

Domain-Specific LLM Fine-Tuning & Evaluation

Module 04

Custom fine-tuned open-source models trained on your domain taxonomy and evaluated with automated Ragas benchmark frameworks.

Included Deliverables:
LoRA / QLoRA Fine-Tuning Pipelines
Ragas Groundedness & Faithfulness Tests
Prompt Caching for Cost Reduction
Private Ollama / vLLM Hosting
DELIVERY METHODOLOGY

From architecture blueprint to production SLA.

No black boxes. You get live staging access, weekly sprint demos, and direct access to our core engineering team.

01

Data Ingestion & Extraction Architecture

We audit your corporate documents (PDFs, Notion, SQL databases) and build clean automated ETL parsers that preserve layout structure.

02

Vector Indexing & Hybrid Search Pipeline

We test embedding models on your specific vocabulary, build the vector index, and tune chunk sizes and cross-encoder rerankers.

03

Evaluation Benchmarking (Ragas Framework)

We run hundreds of test questions measuring Context Recall, Context Precision, and Faithfulness to mathematically eliminate hallucinations.

04

Production UI, RBAC Security & VPC Deploy

We deploy the search UI or API to your private cloud with full role-based security, citation links, and real-time query analytics.

TECHNOLOGY STACK

Production-hardened frameworks & infrastructure.

We build on modern, open technologies with strong developer ecosystems and zero vendor lock-in.

Vector Databases
pgvector (PostgreSQL)QdrantPineconeMilvus / Weaviate
Embedding & Reranking
text-embedding-3-largeBGE-M3Cohere RerankJina AI
RAG Frameworks
LlamaIndexLangChainHaystackRagas Evaluation
Deployment & Models
vLLMOllamaClaude 3.5 SonnetDeepSeek R1
Private Financial / Legal Data
Case Study: Enterprise Legal & Compliance Knowledge Base

Semantic Search Over 40,000+ Multi-Year Regulatory Filings and Contracts

The compliance team took 4 hours on average to manually locate precedent clauses across decades of contracts. Cognopex built a private, VPC-hosted hybrid RAG system with citation links that returns verified answers in under 2 seconds.

92%
Faster contract search time
100%
Source attribution citations
Zero
Data exposure to public clouds
COMMERCIAL MODELS

Flexible, transparent engagement structures.

Choose the model that best fits your project stage and delivery requirements.

Private RAG Proof of Concept (PoC)

Best for indexing a sample dataset (up to 2,000 documents) in 3 weeks.

Terms & Invoicing:
Fixed-price 3-week sprint
Features Included:
Ingestion & indexing of up to 2,000 corporate documents
Hybrid search pipeline (Vector + Keyword + Reranker)
Interactive web search interface with clickable citations
Ragas quantitative accuracy benchmark report
Architecture roadmap for enterprise-wide rollout
Select Private
Most Popular

Enterprise Knowledge Engine

Full production RAG system connected to your live corporate drives & databases.

Terms & Invoicing:
Milestone project + Ongoing ingestion support
Features Included:
Unlimited document ingestion with automated sync connectors
Role-Based Access Control (RBAC) linked to your SSO
Deployed 100% inside your private VPC or on-premise servers
REST API for embedding search into internal tools or Slack
Continuous evaluation dashboard monitoring user queries
Select Enterprise

Custom Model Fine-Tuning & RAG Pod

Domain-specific fine-tuning for proprietary jargon and strict compliance.

Terms & Invoicing:
Monthly retainer (AI & Data Engineers)
Features Included:
LoRA / QLoRA fine-tuning on your proprietary datasets
Custom open-source LLM hosting on private GPU clusters
Continuous prompt engineering and synthetic evaluation
Weekly vector index optimization and cache warming
Dedicated machine learning architect
Select Custom
FREQUENTLY ASKED QUESTIONS

Pre-empting enterprise procurement questions.

Our systems use strict source-grounding. The LLM is instructed only to answer based on the retrieved context chunks. If the retrieved documents do not contain the answer, the system states so explicitly rather than guessing. Furthermore, every statement includes a clickable citation link back to the exact source page.
FAST-TRACK SCOPING

Request a Scoping Call for Enterprise RAG, Vector Search & Private Knowledge Bases

Speak directly with an engineering leader. We sign an NDA, assess your technical requirements, and deliver a detailed architecture roadmap within 48 hours.

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