40+

Successful AI Projects

With a team of over 30 AI experts who have successfully delivered more than 40 AI projects, we will implement advanced document search capabilities to your solution, ensuring structured data and automating all data-related activities.

How Does AI-Powered Document Search Work?

AI-powered document search operates by utilizing the so-called RAG (Retrieval Augmented Generation) technique to analyze and comprehend the information within your documents.

The document search process relies on LLMs (Large Language Models) managing conversations and understanding user questions. After understanding the query, the system identifies relevant parts of the documents to provide context for LLMs to generate answers grounded in the user’s data.

The technology offers the following important benefits:

Cost-effectiveness

RAG offers a more affordable approach to integrating new data into generative AI systems, making this technology more accessible and usable for organizations.

Enhanced user trust

RAG enables generative models to provide accurate information with proper source attribution, increasing user trust and confidence in the AI solution.

Up-to-date information

With RAG, developers can ensure that generative models have access to the latest research, statistics, or news by connecting them directly to live social media feeds, news sites, and other frequently updated sources.

Increased developer control

Developers can efficiently test and improve chat applications with RAG, adjusting information sources to meet changing requirements and ensuring appropriate responses. They can also troubleshoot and fix issues related to incorrect information sources.

Possible Use Cases of the RAG Technology

External applications

RAG can be implemented in products and corporate portals to provide embedded help and support directly within applications or through preferred communication channels like chatbots. For instance, users can access a product website and ask questions, receiving precise answers based on product documentation.

Internal employee support

RAG is valuable for integrating corporate policies and procedures into corporate messenger apps, benefiting all employees. This allows for the creation of comprehensive how-to guides to facilitate onboarding and address general employee inquiries.

Specific information retrieval

RAG enables smart search functionality within corporate portals and messenger apps, facilitating efficient retrieval of specific information from private documents. Unlike general employee support, this feature is tailored for targeted searches, aiding in decision-making and problem-solving within organizations.

Discover how Emerline can create a search system that perfectly fits your business needs. Get in touch with us right now!

Document Search Case Study: Emerline’s RAG Solution

At Emerline, we’ve developed a practical RAG tool aimed at enhancing data interaction for businesses. Our platform enables users to upload customer datasets and swiftly receive human-like questions, improving efficiency in result processing.

Key features include:
  • Accurate human-like answers drawn from customer document sets.
  • Time-saving result processing.
  • User experience comparable to GPT.
  • Seamless integration with corporate messenger applications, third-party portals, and custom apps through chatbot service, etc.
We utilize this tool to showcase the potential of RAG technology to our customers. It serves as a practical demonstration of its capabilities and benefits. Contact us today to explore how our RAG tool can optimize your business operations. Rest assured, we prioritize the privacy and security of your data.

Why Choose Us for Document Search Development?

Investments in R&D
We’ve allocated more than 10,000 hours to research and development, cultivating unmatched expertise across domains within our team.
Expertise of adapting AI for mobiles
Emerline’s tech team is proficient in tailoring AI for mobile applications, providing you with a strategic edge and competitive advantages.
Cooperation with universities
We partner with universities to tap into their deep expertise in specialized knowledge areas. Our on-campus labs are instrumental in efficiently delivering niche projects with precision and effectiveness.
AI ethics and compliance
We specialize in creating and implementing responsible AI solutions, guaranteeing their trustworthiness, transparency, and ethical standards.

Industries We Serve

The technology is cross-industry, meaning regardless of your sector, if you possess documentation sets or a knowledge base and aim to optimize your interaction with it, RAG can be leveraged effectively. At Emerline, we have extensive experience delivering document search solutions across various industries, including but not limited to:

Manufacturing

Marketing & Advertising

Finance & Insurance

Information Technology

Real estate

Retail & E‑Commerce

How do we work?

To achieve outstanding outcomes, we adhere to the CRISP-DM methodology, a proven framework that has played a pivotal role in the success of more than 40 AI projects.

STEP 1

Business and data understanding

  • Examining business processes and challenges.
  • Detailing, investigating, and confirming data quality.
  • Evaluating the business situation, understanding existing data, and identifying additional data requirements.
STEP 2

Data preparation

  • Structuring data for modeling. This step involves data selection, cleaning, construction, integration, and formatting.
STEP 3

Modeling

  • Identifying appropriate modeling techniques.
  • Choosing techniques, creating test designs, and constructing models.
STEP 4

Evaluation

  • Technically assessing results, reviewing the process, and strategically determining subsequent steps.
STEP 5

Deployment

  • Orchestrating a smooth deployment of the AI solution.
  • Monitoring and maintaining the solution.
  • Compiling a comprehensive final report and conducting a project review for success and sustainability.

Let Emerline propel your endeavors with innovative and tailored AI solutions, ensuring efficiency and reliability.

Tech Stack We Use for RAG Development

Python
LangChain
LlamaIndex
Azure
AWS
GCP
AWS Sagemaker
Bedrock
GCP Vertex AI
Databricks
Amazon
Cohere
Google
OpenAI
Meta
Mistral

Awards & recognitions

Our recognized achievements through various awards across diverse domains, including generative AI, E-commerce, and custom software development, stand as a testament to our dedication and excellence in delivering innovative solutions.
view all awards

Case Studies

more case studies
What Our Clients Say

We are proud to have earned a reputation of a reliable software development provider, which is supported by feedback received from our clients.

4.9

25 Reviews on Clutch

25 Reviews on Clutch

FAQ

Our Clients

Throughout our history, we have developed a number of partnerships with technology leaders, who attested our technical competencies and the ability to understand our customers’ needs and translate them into quality services