TRUSTORYX.
LlamaIndex Development Agency

Advanced Data-Connected RAG Apps with LlamaIndex

We build intelligent search engines and document query agents using LlamaIndex — configuring custom ingestion pipelines, node parsers, and hybrid vector retrievals.

LlamaIndex
Data Centric AI
Low
Hallucination
12+
RAG Apps Deployed
LlamaParse
Precise Tables
Growth Obstacles

Problems This Solves

!

Your standard RAG chatbot hallucinates or misses critical figures inside complex PDFs, slide decks, and spreadsheets.

!

You want to query massive internal databases and local document folders using natural language without leaking secrets.

!

Your LLM token consumption is extremely high because of unoptimized chunking models and broad prompts context.

!

You struggle to structure unstructured inputs (contracts, invoice files) into organized database schemas.

Methodology

Our Proven Process

1

Document Ingest Design

We load unstructured files using LlamaParse, extracting tables and structured layouts.

2

Node Parsing & Indexing

We segment text into nodes, extract custom metadata layers, and construct VectorStoreIndexes.

3

Hybrid Retrieval Setup

We combine dense vector search with sparse keyword search (BM25) to boost retrieval accuracy.

4

Reranker Post-Processing

We implement Cohere Rerank models to sort and filter retrieved nodes before prompting LLMs.

5

Secure Deployment & APIs

We link the pipeline to vector databases (Qdrant/Pinecone), package it in Docker, and deploy.

Scope of Work

What's Included

Comprehensive data ingestion blueprints and vector index schema maps
Clean, modular Python/TypeScript codebase utilizing LlamaIndex framework
Optimized text chunking structures and metadata extraction rules configurations
Qdrant, Pinecone, or PGVector store connection script libraries
Cohere Rerank or BGE post-processor model integrations
Production Dockerfiles and cloud-native serverless deployment files
30-day post-launch optimization support and chatbot hallucinations audit reports
Growth Targets

Expected Results

High document retrieval precision with significantly reduced chatbot hallucinations

Fast query response times leveraging indexing and hybrid search lookups

Minimized API token costs using targeted, metadata-guided content retrieves

100% accurate table data extractions from multi-page layout PDFs

Fully secure local-first deployments protecting company private datasets

Tech Stack

Technologies We Master

LlamaIndex
Python
TypeScript
Qdrant
Pinecone
LlamaParse
Cohere Rerank
FastAPI
Exhaustive Solutions

Comprehensive Capabilities

We don't just scratch the surface. Here is a detailed breakdown of everything we can engineer, optimize, and execute for your business.

LlamaParse Ingestion

Writing custom code pipelines to parse tables, grids, and visual elements from multi-page PDFs.

Metadata Tag Injections

Injecting tags such as date, department, and category into index nodes to refine retrieval paths.

Hybrid Vector Retrievals

Linking dense semantic searches with BM25 keyword matching to index content accurately.

Cohere Reranker Setups

Implementing post-processors to prune search contexts and minimize prompt input sizes.

Qdrant Integration

Wiring scalable vector store adapters and metadata filters to query indices instantly.

Query Routing Agents

Engineering routing agents that select the best target data store based on user query intent.

Specialized Focus

Specialized Services

Explore our specialized engineering teams and tailored solutions for this domain.

Transparent Pricing

Investment Plans

Transparent pricing with no hidden fees. Every plan includes dedicated support and monthly reporting.

Document Query Engine

$4,500USD · USD fallback/starting

Single data directory query system, basic vector store index, query REST API, and markdown text parses.

LlamaIndex text parser setups
Local file directory ingestion
VectorStoreIndex creation
Fast query REST API endpoint
Standard OpenAI API connection
Local SQLite memory caching
14-day post-launch support
Basic chunking optimizations
Build Query Engine
Most Popular

Custom RAG Pipeline

$10,000USD · USD fallback/starting

Multi-source document sync, hybrid vector search, Cohere Rerank, custom web chat dashboard, and Qdrant integration.

Includes all Document Engine features
LlamaParse complex table extracts
Multi-source ingestion (Slack, Drive)
Qdrant or Pinecone vector database
Cohere Rerank model integration
Custom React chat dashboard UI
30-day active design support
Evaluation benchmark testing logs
Deploy Custom RAG

Enterprise Data Agent

$20,000USD · USD fallback+/project

Autonomous data routers, sub-question query engines, multi-document agent loops, and private local LLM support.

Autonomous data routing agents
Sub-question query splits logic
Private local LLM (Ollama/Llama3)
Secure enterprise SQL database sync
Dedicated weekly strategy calls
Priority SLA support contracts
60-day post-launch support
24/7 Slack communication channel
Build Data Agent

All plans are month-to-month with no long-term contracts. Custom enterprise plans available.Contact us for a tailored proposal.

Why Trustoryx

Why Choose Us

No Long-Term Contracts

Month-to-month engagements. We earn your business every single month.

Dedicated Team

A named strategist, not a rotating cast of juniors. Consistent point of contact.

Revenue-Focused

We report on revenue impact, not vanity metrics. Every dollar is attributed.

Rapid Execution

Strategy in week 1. Execution by week 2. Results tracked from day one.

Support

Frequently Asked Questions

LangChain is a general-purpose agent framework, while LlamaIndex is a data-centric toolkit designed specifically for advanced RAG systems, ingestion, and querying private data.
It is a state-of-the-art document parsing engine by LlamaIndex that extracts complex tables and formatting from PDFs, avoiding traditional text parser output corruption.
We deploy PGVector or Qdrant databases locally within your servers and wire them to open-source LLMs so no datasets are shared externally.
Reranking uses models like Cohere Rerank to re-sort vector search results by true semantic relevance, ensuring the most accurate context reaches the LLM.

Ready to Get Started?

Start with a free audit. We'll analyze your current performance and show you exactly where the growth opportunities are.

Or email our dedicated desk: ai@trustoryx.digital