NeuralSearch: Intelligent search that prepares data for AI

NeuralSearch is more than search. It’s a brain for your data.

Turn disparate documents into precise answers. NeuralSearch finds the right information for you or prepares the perfect context for artificial intelligence, eliminating “noise” and reducing costs.

Call To Action

Two modes — one goal: find what you need

Work in a way that suits you

Mode 1: Indexed Search	Mode 2: AI Integration
For whom: Teams who need fast and accurate access to source documents without the expense of AI. Ideal for closed loop work.	For whom: Companies that want to receive not just documents, but ready answers, analytics and sammaries based on their data.
How it works: You enter a query – NeuralSearch instantly finds relevant documents, files and text fragments in your database.	How it works: NeuralSearch finds the most relevant documents for your query and passes this cleaned dataset to AI to generate an accurate answer.
Result: List of documents sorted by relevance.	Result: A finished, meaningful answer generated from the facts in your documents.

NeuralSearch: not just a search, but an intelligent data preparation system

Modular multi-agent architecture for any task

Traditional search engines operate on an all-or-nothing basis: either you get a list of files, or you send the entire database to AI and hope for the best. This leads to wasted time, overconsumption of tokens, and inaccurate answers

NeuralSearch is built on a modular agent architecture, where a team of 6 specialized agents can work as a standalone search engine or as an intelligent filter for AI. You choose the mode depending on the task

Team of AI agents under the hood

Behind the single chat interface is a whole team of digital specialists, each an expert in their field:

Mode Routing Agent – Intelligent Dispatcher

Analyzes the request and determines the optimal processing path: whether you need a list of documents or a ready-made AI response. Controls data flow between agents depending on the selected mode. Provides system flexibility without compromising speed

Indexing Agent – Digital Preparator

Processes all document formats: PDF, DOCX, XLSX, TXT, images. Uses Mistral OCR to recognize text with 99% accuracy and speeds up to 2000 pages per minute. Creates optimized search indexes for instant access to information

Hybrid Search Agent – Semantic Expert

Combines two approaches: sense vector search (weight 0.7) and keyword search (weight 0.3). Uses optional reranking to maximize the accuracy of results. Finds relevant documents even with vague query wording

Context Filtering Agent – Optimizer for AI

Key component of AI integration mode: selects 10-20 most relevant documents out of thousands. Reduces token consumption by 95%, saving tens of thousands of rubles every month. Forms an ideal context for LLMs – without “noise” and unnecessary information

The answer generation agent is an AI analyst

Works only in AI-integration mode: generates ready-made answers, analytics, sammaries. Uses only validated data from filtered context – no hallucinations. Supports different language models: GPT, Llama, specialized ones

Why agency architecture is critical to enterprise search

Multi-agent systems are the standard for enterprise AI in 2025. NeuralSearch gives you a choice: use powerful semantic search without AI or enable intelligent filtering to maximize the accuracy of answers while minimizing token costs.

Modularity and flexibility

The system works in two modes without reconfiguration. You pay for AI only when you really need it

Savings on AI tokens

The filtering agent reduces the amount of data transferred to LLM by 95%. For active AI users, this saves tens of thousands of rubles every month

Scalability

The architecture handles millions of documents. Adding new data does not compromise search speed and accuracy

Transparency and control

You see which agents are involved and control the flow of data at every stage. Full transparency from request to result

Readiness for integration

API-architecture allows to embed NeuralSearch into any corporate system: CRM, ERP, internal portals

Transparent and modular architecture for your business

Description of 6 key components of the system

Data Gateway:

Cloud drives (Google Drive, Dropbox).
Your local servers and network folders.
Secure cloud storage on our servers.

Document Storage:

Centralized database where processed information is stored (after OCR or direct conversion from TXT, DOCX).

Vector database:

The “brain” of semantic search. This is where numerical representations of your documents’ meanings are stored for fast and accurate AI work.

Core requested NeuralSearch:

A high-performance engine responsible for indexing and search based on keywords and semantic proximity.

AI query processor:

Our proprietary development that manages the interaction between the search engine and AI models, generating the right queries.

Artificial intelligence models:

The “aisks” themselves (LLMs) that generate the answers. We support both popular models (GPT, Llama) and specialized ones.

Full control over data and infrastructure

Placement of the search engine

In your On-Premise circuit.

Maximum security. All components are deployed on your servers. Data never leaves your infrastructure.

On our servers (SaaS/Private Cloud):

Quick start and savings on support. We take care of all infrastructural work.

Placement of artificial intelligence models

In your closed circuit:

Models are deployed on your power (GPUs are required). You have full control over the AI.

On dedicated GPU servers:

We help you deploy models on your leased capacity from cloud providers (Yandex.Cloud, Contabo, etc.).

Through our secure API:

The easiest way. You connect to models we have already deployed and optimized, saving on GPUs.

Call to Action

A powerful tool that is easy to incorporate

Utilization Scenarios:

As the core for NeuraDoc:

NeuralSearch is the “engine” that powers intelligent search in our flagship product NeuraDoc.

As a stand-alone product:

Set up NeuralSearch as a corporate search engine for your employees.

API Integration:

Embed NeuralSearch into your existing systems (CRM, ERP, internal portals) to create your own intelligent solutions.

QUESTIONS AND ANSWERS

Traditional search looks for exact matches of keywords in documents. NeuralSearch uses semantic analysis and understands the meaning of the query, not just the words. For example, if you search for “return policy”, the system will find documents that mention “claims policy”, “exchange policy” or “warranty”, even if the exact phrase is not present. In addition, NeuralSearch can work in two modes: as a standalone search for quick access to documents or as an intelligent filter for AI models that selects only relevant documents before passing them to AI to generate a response.

Yes, absolutely. NeuralSearch can work as a fully autonomous search engine without AI integration. In this mode, you get powerful semantic search across your document base with instant results. This is ideal for companies that operate in a closed loop, have restrictions on using external AI services, or simply want to minimize costs. Employees will be able to quickly find the documents, files and snippets of information they need without having to pay for AI model tokens.

The speed of implementation depends on the chosen deployment option. Cloud version (SaaS) is connected in 15-30 minutes – you just upload documents and the system starts working. A private cloud on your leased facilities is deployed in 1-2 days. Corporate implementation (On-Premise) in your closed loop takes from 3 to 7 working days, depending on the complexity of the IT infrastructure and the volume of documents. We provide full support at all stages, including customization of integrations with your existing systems (CRM, ERP, internal portals).

NeuralSearch works with all popular formats: PDF (including scans), DOCX, XLSX, TXT, as well as images (JPG, PNG). The system uses Mistral OCR technology to recognize text from scans, photos and handwritten documents with up to 99% accuracy. Processing speed is up to 2000 pages per minute. The system scales from hundreds of documents to millions of pages. The only technical limitation when using OCR via API is a maximum file size of 50MB and up to 1000 pages, but these limits are removed when deployed locally.

NeuralSearch acts as a “smart filter” in front of the AI model. Instead of passing your entire database of 10,000 documents to AI (which results in huge token consumption and model “hallucinations”), NeuralSearch first finds the 10-20 most relevant documents for the query. Only this filtered set is passed to AI to generate a response. This reduces token consumption by up to 95%, speeds up response generation by 5-10x, and significantly improves accuracy as AI only works with validated relevant information. For companies actively using AI, the savings can amount to tens of thousands of dollars each month.