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Large Language Modeling (Generative AI)
Build and deploy solutions powered by large language models that are tailored to your data and domain. These models can power business applications like text generation, text classification, and question answering.
We have built specialized solutions that combine the power of Generative AI with other NLP models and techniques. Reach out to us to see what potential is hidden in your data that can be uncovered with Generative AI.
Question Answering
Make the best use of your knowledge base by creating Question Answering systems that can help you find what you are looking for from a vast collection of documents.
We can ensure that your company’s proprietary data is secure and not shared with public models like ChatGPT. You will be able to take full advantage of your data and be rest assured that your data is not shared with the outside world.
Text Classification
Automate business workflows or better organize information by classifying text and documents into multi-level taxonomy.
We have built AI-powered products that have complex text classification algorithms at their base. Our algorithms have successfully classified text into more than a thousand categories. With these algorithms, we have achieved up to 80% reduction in manual effort.
Named Entity Recognition
Quickly process large amounts of documents or paperwork by identifying named entities and automating workflows.
Reduce manual effort by up to 90% by automatically identifying important entities like Names, Company Names, Addresses, Phone numbers, Policy numbers, License numbers, Document IDs, and any other entity. Build systems with a feedback loop for continuous learning and improving the system.
Keyword Extraction and Topic Modeling
Understand highlights of content at a glance. Use the extracted keywords and topics to organize content without any training data or manual tagging.
When you have large quantities of unstructured and unorganized data, it is difficult to achieve the full potential benefit of that data. Keyword extraction and topic modeling techniques help you understand the important highlights of that data and organize the data easily. It also helps open up the AI black box to gain understandable insights into the data.
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Semantic Textual Similarity
Organize documents or information by grouping documents with similar text not just based on keywords but based on the meaning of the text.
We have built Semantic Textual Similarity based solutions for tasks where our client wanted to find the closest document from a database of documents based on another document. This algorithm has applications in HRTech or LegalTech by matching resumes to job descriptions or matching statutes to a particular case.
Information Retrieval
Find information in a way that the most relevant information shows up first.
Simple keyword search will get you hundreds or thousands of matching documents but you need algorithms that can order them in order of relevance. Our information retrieval based algorithms have helped clients to take utmost advantage of their knowledge base.
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Sentiment Analysis
Understand overall sentiment from large quantities of text. Identify positives and negatives about specific subtopics from the overall text.
We have helped our clients track changes in sentiment over a period of time and correlate them to specific events. We have also helped identify positive and negative sentiments about specific features from online reviews or products. When we parse reviews or feedback with this level of detail, it gives helpful and actionable insights into the business.
Fuzzy String Matching
Techniques to match strings with fuzzy logic are very important for data hygiene. Real-world data is messy, names of businesses, people, and addresses are written in slight variations by people. When you have to deal with this data and combine common entities fuzzy string matching algorithms are great. We have helped clients deduplicate up to 30% of data and maintain data hygiene.
Creating Real-world NLP Based Solutions
Real-world problems are seldom clean with well-defined boundaries where any one type of algorithm will suffice. Our expertise is to understand the business problem first, define it and break it into smaller components, and then apply one or more than one algorithm and techniques to solve the problem. We are all about solving real-world problems through algorithms and not just about writing code.
Technologies
Case Studies
AI-Driven Candidate Screening Revolution
JashDS revolutionized a company's hiring process by developing a GenAI-powered candidate screener that reduced time-to-hire by 50% and improved hiring outcomes. The solution leverages advanced language models to conduct dynamic, role-specific interviews, automatically generating and adapting questions based on job descriptions and candidate responses.
AI-Powered Resume-Job Matching Engine
JashDS developed an AI-powered resume-job matching engine for a leading Indian job portal, processing over 1M resumes and 50k job descriptions. The solution employed BERT embeddings and HNSW algorithms to create personalized job recommendations for candidates and streamline resume screening for recruiters, significantly enhancing the job search and recruitment processes.