Kodlo is an AI native workspace designed for sales teams and individual representatives who manage high-ticket B2B deals. Its primary function is to consolidate the entire sales cycle into a single platform, replacing the need for multiple separate tools. The system integrates lead discovery, prospect research, outreach, pipeline management, and content creation into one unified workflow. Underlying this integration is a shared data and memory architecture, which ensures that information does not need to be manually synced between different stages of the sales process. The platform offers a range of capabilities that cover the full sales cycle. These include an ICP (Ideal Customer Profile) interview tool, lead sourcing and list enrichment, deep research and cited brief generation, personalized outreach drafting, pipeline updates, and campaign content management. A key feature is its agent driven research function, which creates detailed briefs by executing a research plan, reading actual web pages, and cross checking facts across multiple sources. The system also includes a CRM for contact management, a ticket system, and a knowledge hub with OCR (Optical Character Recognition) for querying internal documents. Memory is organized in three layers to keep company data, prospect information, and campaign history connected. Typical use cases involve a sales representative defining their target market, sourcing leads, and then using the agent to conduct deep research on specific accounts. This research covers the company, its executives, competitive landscape, and industry context, resulting in a brief that cites multiple sources. The agent can then draft personalized outreach messages and update the pipeline based on the interaction. The workspace is designed to provide a single source of truth, allowing users to ask the agent questions about a contact or deal, with answers grounded in LinkedIn data, company news, and CRM history. The platform operates on a subscription model with no per contact charges, and it adheres to GDPR, CCPA, and global privacy standards, using only public sources for research while keeping user data within the workspace.