Introduction to AI Grid Agents
What are AI Agents?
AI agents can be described as a system with reasoning capabilities, memory, and the necessary tools to execute end-to-end task completion. Consider AI agents as your new AI team members that can work alone, or as part of a team of other agents and real people.
Agents have clearly defined roles and responsibilities, and they can choose how best to get their work done using the knowledge they access, and the tools you equip them with.
What are AI Grid Agents?
At Lampi AI, we've been focusing on developing state-of-the-art AI agents, able to automate end-to-end complex tasks and workflows. Our agents are designed to gather knowledge from internal knowledge or public data, and synthesize and condensate all the information gathered from multi-step workflows into structured reports – from few pages to more than 50-100 pages of fact-based and grounded information, saving countless hours of market and equity research and drafting memorandums or reports.
However, while AI agents execute end-to-end processes and provide complete documents with citations to sources, it turns out that for most tasks (e.g., portfolio analysis, agreement review, etc), users need to:
- Understand the agent's thought-process
- Verify – not only with citations and sources – and compare every single data retrieved step-by-step by the agents
- Receive an exhaustive analysis of all documents through parallelized data analysis (i.e., each file needs to be analyzed completely independently in the same workflow)
We built AI Grid Agent to answer these requirements - an agentic system that tackles the most complex tasks, powered by the best and latest models – DeepSeek R-1, Qwen2.5, Claude Sonnet 3.5, OpenAI's o1, etc. and available through private deployment (on-cloud or on-premise).
Lampi's AI Grid Agents are designed to automate data and insights retrieval and analysis at scale that would take analysts days of work.
We made the decision to provide a familiar grid view that allows users to visualize, manage, and follow each step of data retrieval and analysis in a structured table format. With the flexibility to customize each column, organizing, interpreting and analyzing complex data has never been simpler.
In a single grid, AI agents can gather and interpret thousands of complex documents, including with graphics, charts and tables with state-of-the-art accuracy and an infinite context window, which overcomes one of the main limitations of Retrieval-Augmented Generation (RAG) systems (i.e. to answer nuanced questions whose answers are not explicitly mentioned in the documents, but rather require reasoning and analysis of the document).
For each task, Lampi's AI automatically completes all the cells of the grid by extracting and analyzing insights from all the documents - powered by an advanced and proprietary citation mechanism that allows to easily fact-check every answer.
Watch as your table transforms into a dynamic and intelligent tool with in-depth research and analysis!
Grid View
The Grid view is the central feature of AI Grid Agents. It represents all the steps the agent will execute and allows you to visualize, manage, and analyze both internal and external data in a structured table format.
With the flexibility to customize each column, organizing, interpreting, and analyzing complex data has never been simpler.
Lampi's AI Grid Agents are designed to automate end-to-end workflows. Lampi's AI automatically complete cells by extracting and analyzing insights from your files or external data.
Column Understanding
Columns are the building blocks of your AI Grid. They define all the steps of the workflow and determine what information is retrieved and analyzed for each row through prompting.
In each column, you can prompt your agent to execute a specific function.
Each one can be customized to capture specific types of data, ensuring your data is accurate and efficiently structured (text, date, number, boolean, etc.).
AI Settings and Tools
Lampi's AI capabilities bring your columns to life, enabling them to automatically gather and enrich data based on your specific needs.
For each column, you have a list of tools that can be used to answer the task.
How AI Grid Agents Work?
When you run your table, your AI agent automatically executes all the steps of the workflow and completes all the cells based on the selected tool and the data sources. For example:
- If you choose Web Search, the AI will analyze each row by searching the web.
- If you choose File Analysis, it will extract and analyze data from the uploaded files.
To understand how to create an AI Grid Agent, you can refer to 🛠️ Create an AI Grid Agent.
Example Use Cases
There are a great many cases of use for AI Grid Agents. Here are some real-world examples of how they can be used:
| Use Case | Description |
|---|---|
| Competitive Analysis | Track key competitors, product offerings, KPIs or other market data |
| Agreement Analysis | Extract key points from multiple agreements with ease |
| Company Research | Structure searches for company data and gain comprehensive insights |
| Interview Analysis | Extract valuable insights from meetings or interviews |
| Portfolio Monitoring | Monitor and manage your portfolio efficiently |
| Due Diligence | Conduct thorough due diligence processes by automating the collection, analysis, and synthesis of data from diverse sources |
| Investment Research | Accelerate investment research by gathering, and analyzing vast amounts of data |
Sharing is Caring
You can easily create templates of tables that can be shared across your organization!
Identify team members that possess a thorough understanding of their team's workflows, and have, or are eager to acquire, AI skills, and ask them to create templates for your teams.
Advantages of AI Grid Agents
Consider AI agents as your new AI workforce
1. Performs Endless Tasks
You can scale agents to meet all your needs. Run the necessary agents to perform the tasks you need to be done, without recruiting new employees or increasing the workload of existing ones.
2. Increases Productivity
You can use agents to automate repetitive time-consuming tasks, so that your human employees can be freed up to do more engaging work.
3. Can Work Autonomously
Agents can complete work end-to-end without you needing to be involved at all.
When you run AI agent, the task is performed in the back without needing human input at all.
FAQs
When should you use an agent?
AI Agents are especially well-suited for repetitive tasks, no matter how complex the task is. For example, many financial analysts spend a huge amount of time searching for insights on new markets, including recurring type of data, when they could instead focus on more interesting work further down the funnel, like analyzing the insights and take decision.
Who should build agents?
Domain experts or team members who are currently doing the work you want to delegate to your agent should be the one creating the AI agent. Consider adding AI enthusiasm in the process to improve the instructions and prompts to give to the agent.
Next: Create an AI Grid Agent manually →