Enhance, Transform, Perform
Natural Language Processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret, and generate human language.
NLP applications are vast, including chatbots, sentiment analysis, document summarization, search engine optimization, and machine translation.
scalenow AI primary goal is to facilitate meaningful interactions between humans and machines, enhancing communication and making technology more accessible and user-friendly.
Get StartedExample Use Case
A user types, "What is the budget remaining for the Apollo project?". scalenow AI identifies "budget remaining" as the intent and "Apollo project" as the entity, then retrieves and displays the relevant information.
Seamless interaction for Transformation
scalenow AI leverages Natural Language Processing (NLP) for seamless interaction with project-related data stored in a database.
Users can access and manage key project information such as budgets, issues, and tasks through natural language queries.
Additionally, a local large language model (LLM) enables users to generate narratives, user stories, and other project documentation. Each feature is broken down below for clarity and detail.
Access Metrics Using Natural Language
Users can query scalenow AI system using natural language to retrieve project-specific information.
Whether they need to check the budget, review pending issues, or list assigned tasks, the NLP engine interprets their intent and fetches the relevant data from the database.
- Saves of interaction
- Suggestive prompts
- Favorites Chats
- Store History
- Message to extract from database
- Information retrieved from database
- Information retrieved from LLM
- Choose file to Upload
- Upload file to LLM for analysis
- Switch between database and LLM
- Area to interact
- Send Button
Local LLM to generate Narratives, Documents
The integration of a local large language model allows users to craft detailed project narratives, user stories, and other textual assets directly within scalenow AI.
This ensures privacy and speed while enabling collaborative project documentation.
Example Use Case
A project manager requests, "Generate a user story for the Apollo project’s authentication module." The scalenow AI LLM produces a comprehensive user story, including roles, goals, and acceptance criteria.
Interface for Data , Content Generation
scalenow AI combines database querying and content generation into a single, intuitive interface.
Users can seamlessly switch between retrieving data and generating documentation without needing technical expertise.
Example Use Case
A user requests, "Summarize the completed tasks for Project Z and generate an end-of-sprint report." scalenow AI system retrieves the completed tasks and helps produce a polished report ready for review.
Access Metrics Using Natural Language
Users can query scalenow AI system using natural language to retrieve project-specific information.
Whether they need to check the budget, review pending issues, or list assigned tasks, the NLP engine interprets their intent and fetches the relevant data from the database.