How it works
Our Technology,
Explained Through A Task Request
Write A Task Prompt For Ninja To Complete
Chat with Ninja as you would a colleague at work simply by conversing. Our autonomous AI agents can handle tasks, such as scheduling, advising, researching, image generation, and more, concurrently.
A few sample skills include:
Schedule Meetings: Our AI agents will find the right time across time zones for internal and external meetings; for users outside your company, agents can initiate email discussions to find a time.
Calendar Analysis: Our AI agents can provide suggestions for managing your time better and to make you more productive, and then make these calendar changes for you.
Conduct Research: Get insights to your most pressing questions from search engines and multiple generative AI models.
Chat and Get Advice: Ask our AI agents for advice, a great joke or to write a poem. Choose from different agent personalities that match your preferences and role type.
Multi-Agent AI System
Ninja is a multi-agent AI system specialized in a variety of tasks. These autonomous agents work together to solve complex problems through a multi-step work plan.
Specialized Functions: Each AI agent focuses on a specific task, such as scheduling, research, writing, code generation, and much more.
Collaborative Workflow: Our AI agents collaborate to ensure efficient task completion through a common work plan that is built uniquely to solve each problem or prompt.
Unified User Interface: All tasks are done within one cohesive interface. Whether an AI agent is booking a meeting or conducting research (or in the near future, making reservations, conducting outreach or booking travel), it stays in our UI through the lifecycle of a task.
Scalability and Flexibility: Our AI agents adapt and scale to handle a range of complex ‘chained’ tasks.
Tree Of Thoughts
Ninja utilizes a "Tree of Thoughts" model in its multi-agent AI system to efficiently process and respond to user queries, with specialized agents collaborating on various aspects of the task.
Input Analysis: The selected AI agents breaks down queries using natural language processing.
Tree of Thoughts Formation: The AI agent constructs a logic tree with each branch representing a potential combination of solutions. Over time, these trees become more efficient through reinforcement learning.
Agent Collaboration: Our AI agents work on branches simultaneously, pooling expertise to simulate and test in a safe environment.
Comprehensive Output: Our AI agents combine insights from all skills to provide a well-rounded response.
Simulation Environment
When Ninja's chosen AI agent successfully completes a task, it replicates the solution and stores it in a simulation environment for future problems.
Recording Success: Our AI agents identify the strategies and decisions that led to success and store them in a bank of inference.
Learning from Experience: The stored strategies and decisions are analyzed by machine learning algorithms using anonymized data to find commonalities with other successful strategies.
Improving Future Performance: Through this analysis, our AI agents optimize their approach, leading to quicker and more accurate task scenarios. This means faster and more accurate handling of tasks over time and a faster learning curve for new skills.
Adapting to User Preferences: As the agents learn from each task, they become more personalized, adapting to the users’ specific needs. Put simply, they become better at getting tasks done more efficiently.
Complete Task
Ninja's AI agents efficiently schedule the requested meetings and notify users, then use the success to improve future task handling.
Task Completion: Successfully schedules meetings and informs the users.
Data Storage: Records the successful process in its training environment.
Learning and Optimization: Analyzes the success to refine algorithms.
Enhanced Future Performance: Applies improvements for quicker, more advanced personal AI tasks.
