Immocore is relevant to the AI agent ecosystem as an example of a vertical-specific 'assistant' platform. They use AI for structured data extraction (KI-Import), turning unstructured documents into the clean data necessary for agentic workflows. By building a unified data layer for commercial real estate—traditionally a messy, document-heavy field—they create the infrastructure where autonomous agents could eventually negotiate or match deals.
Currently, their software acts as a human-in-the-loop assistant that automates the 'matching' of purchase profiles to listings. This sits at the intersection of CRM and automated reasoning, showing how vertical SaaS is evolving from a system of record into a system of action. Their use of OpenAI for data extraction and their focus on 'intelligent matchmaking' places them in the stack of companies building specialized, agent-enabled tools for high-value industries.
Most real estate software starts with the residential market—houses and apartments—and tries to squeeze commercial workflows into a frame that doesn't fit. Immocore reversed this. Based in Berlin, the company builds a CRM and transaction management platform designed specifically for the complexities of commercial real estate (CRE). They cater to a niche where floor plans are divided by usage types, rental contracts span decades with indexation, and matchmaking requires cross-referencing specific purchase profiles against a shifting inventory of office, industrial, and retail spaces.
The platform is built around three core modules: Marketing, Leasing, and Transactions. The marketing module focuses on reducing the manual labor of generating exposés and listings. It uses automated data analysis to pull property details into templates for portals like ImmoScout24 or custom WordPress-based property sites. One of the more technically interesting features is the AI-driven import system. Instead of manually entering hundreds of fields for a new office complex or a client's search request, users can upload documents or unstructured data, and the system extracts the relevant structured parameters. This is a clear application of Large Language Models used to solve a data entry problem that has historically plagued the CRE industry.
Founded in 2023 by Maximilian Hessel and Konrad Eitner, Immocore enters a market where digital adoption is often fragmented. Brokers often use one tool for lead management, another for marketing PDFs, and a third to track their deal pipeline. Immocore attempts to collapse these into a single environment. They position themselves against broader tools by highlighting that commercial real estate is their sole focus. For asset managers and owners, the value is in the Deal Room, a central space where all parties—brokers, owners, and potential tenants—can view the status of a transaction. This level of visibility is rare in a sector that traditionally operates via siloed email threads.
The company is based in Berlin and operates primarily in the DACH region. Their pricing model focuses on a flat rate rather than per-user seats, which encourages entire teams to collaborate on the platform without cost friction. By integrating with existing tools like Microsoft Outlook and various real estate portals, they ensure that they don't have to replace a firm's entire tech stack on day one. Instead, they act as the connective tissue for data that previously lived in inaccessible silos. Their roadmap moves toward becoming a digital assistant for the broker, where the software doesn't just store data but proactively suggests matches between buyers and sellers based on stored purchase profiles.
CRM and transaction management software for commercial real estate.
Immocore is hiring.