The AI agent specialises in executing tasks, retrieving, and analyzing information from web-based sources, local models, and LLM APIs. It automates workflows, performs intelligent searches, summarizes content, and provides insights for research and decision-making.
Uses natural language processing (NLP) techniques to extract relevant information and generate structured outputs.
Tested using LLM APIs such as OpenAI GPT-4o and Gemini 2.0 Flash for extended capabilities.
Leverages local execution models like Deepseek-r1:14B and Mistral for on-device processing.
Use Cases
The AI agent has a broad range of applications, including:
Executing online tasks (e.g., adding grocery items to a cart and checking out, managing tasks in productivity apps).
Performing web searches (e.g., retrieving up-to-date news, extracting competitor insights, exploring research topics).
Writing blog posts and research reports by compiling information from multiple sources.
Providing AI consulting insights to businesses on leveraging AI for research and content generation.
Enhancing knowledge discovery by summarizing large datasets, articles, and technical documents.
Automating data entry and business workflows (e.g., transferring LinkedIn contacts to Salesforce, applying for jobs based on CV analysis).
Technical Stack
Mistral as an alternative model for local processing.
Deepseek-r1:14B for local AI model execution and knowledge retrieval.
Ollama for running LLMs on local machines.
GPT-4o and Gemini 2.0 Flash APIs for cloud-based model interaction.
Web scraping tools (if permitted) for public domain knowledge retrieval.
Process
The AI agent follows a structured process to execute tasks efficiently:
User Prompt or API Trigger: The AI agent is activated through a user command, API call, or scheduled task.
Task Identification & Planning: It interprets the prompt using NLP techniques and formulates a structured action plan.
Data Retrieval & Processing: The AI agent fetches relevant data from web sources, local files, or APIs like Deepseek and OpenAI.
Task Execution: Executes the defined steps, such as adding items to a cart, entering data into CRM systems, or applying for jobs.
Verification & Error Handling: Checks for accuracy, handles errors, and seeks clarification from the user if needed.
Results Compilation & Reporting: Summarizes completed actions and presents results via the Web UI or a downloadable file.
Performance & Results
Inference Speed: AI processes queries in under 2 seconds.
Task Execution Accuracy: Successfully completes structured tasks 90% of the time.
Efficiency Rate: Reduces manual research and workflow automation efforts by ~70%.
Impact
This AI agent enhances productivity by reducing manual effort in knowledge acquisition, task execution, and workflow automation. It is particularly useful for professionals, executives, and teams looking to integrate AI-driven automation tools into their workflows. As an AI consultant, I help organizations understand, implement, and optimize AI-powered task execution and knowledge systems through strategic adoption and practical application.
Demonstration
One notable demonstration involved prompting the AI agent to find information about me on Google. The AI agent executed the following steps:
Understanding the Query: The agent processed the user’s request and formulated a structured plan to perform a Google search efficiently.
Performing the Search: It navigated to Google, entered the search terms, and retrieved the top results.
Filtering & Extracting Relevant Data: The agent analyzed and summarized the most relevant links, filtering out advertisements and irrelevant sources.
Structuring the Output: The AI presented a summarized report containing key insights, such as professional profiles, recent activities, or relevant mentions.
Providing Actionable Insights: Based on the retrieved information, the AI suggested next steps, such as refining searches, saving profiles to a database, or automating future monitoring of online presence.
This capability can be extended to various business applications, such as tracking competitors, conducting background research, and monitoring brand presence online.
