Ibexa launches agentic marketing platform to coordinate AI models
enterprise software vendor Ibexa launched an agentic marketing platform designed to coordinate multiple artificial intelligence models and workflows across disparate software tools, moving beyond isolated chatbots and copilots.
The platform targets a widening operational friction point within corporate marketing departments, according to an interview published by lemondeinformatique.fr. Bertrand Maugain, CEO of Ibexa, stated that the widespread adoption of generative AI initially worsened tool fragmentation rather than curing it.
Origins in the QNTM Project
Ibexa traces its corporate lineage back to QNTM, a European MarTech consolidation project launched in 2021. Over subsequent operating cycles, the organization absorbed several specialized digital experience brands, including CMS provider Cohesivo, PIM vendor Quable, customer data platform Raptor, data collection tool Qualifio, and marketing automation suite Actito.
For roughly 18 months, an R&D laboratory based in Poland focused on agentic workflows. That research culminated in the new orchestration layer. Maugain noted that while specialized tools excel at localized tasks like email dispatch or CRM record management, enterprises run into severe friction when attempting to execute multi-step campaigns from end to end.
Orchestrating Complex International Campaigns
Under traditional configurations, a multi-country product rollout across Germany, Switzerland, and Austria requires weeks or months of manual coordination. Marketing teams must extract specifications from the product information management system, build assets inside the content management system, handle multi-language translations, and pull targeted audiences from customer data platforms.
Ibexa’s agentic platform allows a marketer to issue a unified operational instruction. Agents then execute the required steps across separate software applications. Maugain described the resulting shift as moving human workers from manual operators to high-level orchestrators focused on strategic judgment and brand messaging.
Ibexa Integrates External Models with Token Budget Controls
The platform does not require organizations to replace existing software stacks. Built to accommodate external large language models, the system incorporates Model Context Protocols to connect with third-party software outside the Ibexa portfolio.
To address the financial risk of runaway token consumption, the management interface lets administrators assign strict credit budgets to specific agent tasks and limit execution steps.
Enterprise Adoption Requires Verified Data Governance
Security and institutional governance remain central to deploying autonomous agents at scale.
Maugain emphasized that while developers can easily build isolated experimental agents, enterprise adoption requires stable production environments equipped with verified data governance and strict cost controls.