Artificial Intelligence Services
Clustrex provides comprehensive AI and ML services covering Large language models, Image and Video analytics with leading technologies including OpenAI, AWS Bedrock, Google Vertex, Langchain, LlamaIndex and more
Build your chatbot for your website to engage with your clients in a conversational way to explain your services. Enable your business to collect information by natural language conversations in text or voice and fill out the forms from your users. Examples could be pre-visit patient information collection, account opening information collection and more.. Query your database using natural language to build interactive dashboards and reports.
AI based Image processing:
AI based Image processing has multiple use cases such as automatic face recognition to offer personalized services, image classification and more.
Document processing with AI
With the advent of GenAI, document processing, conversational interface and summarization and generation of documents as Blogs have gone through a transformation. Following are some use cases we have worked in this area.
1. Bank Statements Extractor
Technologies Used :AWS Textract, S3, Lambda, DynamoDB, API Gateway, Google Login.
Value delivered :We have also integrated automatic verification system, which reduces user's time to manually verify all the files. This ensures the accuracy and integrity of the extracted data.
Challenges :Converting variety of formats used by each bank to a single standard format.
2. Blog Generator for Bankruptcy documents
Technologies Used :AWS Bedrock, Langchain, AWS Textract, S3, Lambda, DynamoDB, API Gateway, Google Login, Prompt Engineering. LLM modals: GPT-4 from OpenAI, Claude from Anthropic.
Value delivered :Application not only acts as blog generator, but also acts as a chat-bot and answer user's queries based on the documents provided by the user. By adopting a serverless architecture, we have optimized costs while maintaining high efficiency and scalability.
Challenges :The complexity of transforming document data into informative blogs and integrating advanced AI models.
3. Invoice Extraction from a variety of vendors
Technologies used :AWS Bedrock, OpenAI's GPT-4, Prompt Engineering, Llama-Index, AWS Textract, S3, Lambda, Comprehend, Sagemaker Groundtruth, EC2, Step Functions, SQS, MySQL. LLM modals: GPT-4 from OpenAI, Claude from Anthropic.
Value Delivered :High Quality Data, ability to easily review only the required files, reduced manual intervention for files.
Challenges :To achieve a standard format for various vendors and to ensure consistency and reliability in handling diverse invoice templates.
4. Dynamic Project Query Bot
User-Friendly Queries :The bot allows users to interact intuitively with project data through natural language queries.
Dynamic Information Retrieval :Users can obtain specific details, including open and completed project lists or in-depth information about individual projects.
Sorting Capabilities :The bot supports sorting projects by completion dates, providing a quick overview of project timelines
Status-based Filtering :Users can easily filter projects by status, streamlining access to ongoing, completed, or open projects.
Value Inquiry :The bot accommodates queries about project values, aiding in financial planning and decision-making.
Deadline Proximity Alerts :Users can inquire about projects ending soon, facilitating prioritization and efficient project management.
Top-Value Sorting :Users can request a sorted list of completed projects based on values, supporting analysis of high-value projects.
Intelligent Responses :The bot is programmed to comprehend diverse queries, ensuring accurate and relevant responses.
Enhanced Experience :By incorporating these features, the bot aims to elevate the overall user experience, promoting effective project management and decision-making.