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AI-knowledge base

An AI-based knowledge base

RAG is a platform for automating corporate processes

  • Processing of standard and complex queries without operator involvement
  • Reducing the time spent searching for information in documents and correspondence
  • Access to corporate knowledge for fast onboarding of new employees
  • Reducing errors when transmitting information and working with documents
  • Automation of recurring requests and internal consultations
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on 15-20%
increase in the average
sales receipt
24/7
no days off, vacations, or
human factors
on 20-30%
improving
customer satisfaction

Advantages of an AI knowledge base for business

For managers and product owners
For managers and product owners
  • Instant access to key indicators and strategic information
  • A single information space without disparate sources
  • Employee and customer query analytics
  • Identification of bottlenecks and risks in business processes
  • Evaluating the effectiveness of projects and internal operations


Find out the cost and timing of implementing an AI-based knowledge base

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For project and operational managers
For project and operational managers
  • Real-time tracking of project and task statuses
  • Quick search through documentation, regulations, and internal instructions
  • Automation of standard requests and internal consultations
  • Support for quality standards and corporate norms
  • Reducing dependence on specific employees


Learn how the AI database automates internal processes

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For financial and analytical professionals
For financial and analytical professionals
  • Quick access to up-to-date financial and operational information
  • Data-driven decision support
  • Acceleration of reporting due to automatic compilation of information
  • Identification of deviations and monitoring of indicators
  • Analyzing large amounts of structured and unstructured data


Order an AI system for business

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The LighTech Team

Project managers
Product managers
DevOps engineers
Architects
Frontend Developers
Backend Developers
Mobile Developers
Flutter-
iOS Developers-Developers
Android Developers
QA Engineers
UX/UI specialists
Scrum Masters
Analysts
Designers
Marketers
Copywriters
Learn more about the team

Tell us about your project

As an IT agency with strong expertise in mobile and web development, AI-based automation, we will select the optimal solution, prepare an implementation roadmap, and calculate the timing and cost of implementation
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LighTech

Our advantages

Scrum.org certification
Scrum.org certification

Our team is certified according to international standards Scrum.org . We apply the best practices of agile development to your business.

The Open-Source approach
The Open-Source approach

Active participation in open-source projects allows you to create reliable solutions using proven technologies and keep up with the times. 

The component approach
The component approach

Our solutions are created from ready-made tested components. This speeds up development and scaling, as well as making further support easier.

Worked commands
Worked commands

Our experts with extensive experience in collaboration guarantee efficiency, coherence and quality of the final product.

Experience in BPMS, CRM, and Highload development
Experience in BPMS, CRM, and Highload development

We are not new to complex projects. We have extensive experience in creating BPMS, CRM and high-load systems.

Accredited IT company
Accredited IT company

Proven professional qualifications, reliability and compliance with advanced industry standards.

Technology stack

We will help you create a solution that will meet the needs of your business. Our team uses proven and up-to-date tools, develops digital products for stable and efficient work for many years to come. 

Go
A compiled programming language with a simple syntax, focused on high performance and parallel computing.
Python
A powerful and flexible programming language that provides fast development and high performance. It is ideal for creating complex business logic and processing large amounts of data.
RDBMS
A relational database management system that allows you to store and process data in the form of linked tables
AWS
Amazon cloud platform, which provides a wide range of services for computing, data storage, and application development
Celery
Asynchronous task queue for Python, which allows you to perform deferred operations and distribute the load
Docker
A platform for packaging, distributing, and running applications in isolated containers
Django
High-level Python framework for fast development of secure and scalable web applications
DRF
Django REST Framework, a Django extension for creating APIs with REST architecture support
FastAPI
Modern Python framework for building high-performance APIs with automatic documentation
React
A library for developing interactive user interfaces. Allows you to create fast and scalable web applications with excellent performance.
Angular
A progressive framework for creating dynamic and responsive user interfaces. Guarantees smooth operation of your portal on any devices
Vue
A progressive JavaScript framework for creating user interfaces with a reactive data update system
Next.js
React is a framework with support for server-side rendering for creating optimized web applications.
Nuxt
A framework for Vue.js, which simplifies the development of universal and statically generated applications
Dart
An object-oriented programming language from Google used for developing mobile, web, and desktop applications.
Flutter
A powerful framework for fast and efficient development, ideal for creating cross-platform applications. It provides high performance and flexibility, enables efficient implementation of complex business logic, and provides high-quality user interfaces.
Clean Architecture
An architectural approach to software development that focuses on separation of responsibility and independence from external frameworks
Swift
A modern programming language from Apple for developing applications for iOS, macOS and other platforms of the company
Kotlin
A statically typed programming language from JetBrains, compatible with Java, used for developing Android applications and server systems

They trust us.

Bayer
Bronevik
Stabilafonder
X5Group
W
Lean Apps

Stages of implementation of the AI knowledge base

1

Audit and task setting

We define the implementation goals: speeding up responses, reducing workload, and automating internal requests. We analyze the existing infrastructure (CRM, ERP, messengers, databases). 

2

Designing use cases

We analyze how employees are currently searching for information and identify key points of application of the AI knowledge base. We are configuring the RAG architecture and the logic of working with corporate data.

3

Integration and configuration

We connect data sources and external services and configure work with chats, mail, API, and internal portals. We implement automatic search and response generation. Setting up the launch of business processes according to the specified rules.

4

Testing the application

We check the correctness of the AI system: the correctness of responses, the fulfillment of tasks, stability under peak loads, work with typical and atypical requests.

5

Implementation and support

We are embedding the AI knowledge base into the corporate ecosystem, setting up access and security controls. We are updating data sources and optimizing scenarios. We provide technical support and system development

Why does a business need an AI knowledge base?

The AI knowledge base automates work with corporate information. It finds data in documents, databases, correspondence, and company systems and provides accurate answers based on real sources.

This is not just a chatbot, but an intelligent system for accessing the company's knowledge, which:

  • it works 24/7;
  • It relies on corporate data;
  • reduces the burden on employees;
  • accelerates decision-making.
     

How does it work?

RAG (Retrieval-Augmented Generation) combines search and response generation. The system first finds relevant data in internal sources, and then generates an accurate response based on the found context.

RAG systems are used in tasks where it is important to work with a large amount of verified information and get accurate answers based on sources. They are used in customer support to search knowledge bases and CRM, in legal and financial departments to work with regulatory and regulatory documents, in medicine to analyze clinical recommendations and medical data, as well as in education and corporate training to automate responses and access to educational materials.

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Frequent questions

Who is suitable for an AI knowledge base?
Where else are RAG systems used?
What should I do if there is no ready-made knowledge base?
What advantages does the RAG system have for businesses compared to regular reporting?

What will you get after completing the project

Get artifacts from the project
Open
Ready-to-use AI knowledge base
Ready-to-use AI knowledge base
Structured corporate data
Structured corporate data
Closing documents
Closing documents
Support
Support

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