ALURA launches Alura Pexus, an AI-based lead enrichment system designed to help B2B organizations focus sales efforts on the most relevant and timely prospects.
ALURA, a Norwegian artificial intelligence consultancy, announced the launch of Alura Pexus, its AI-based lead enrichment system, a service designed to help B2B organizations improve how they identify, prioritize and engage potential customers. The system addresses a common challenge across B2B markets: large volumes of data and leads, but limited clarity on where commercial focus should be placed.
As sales and marketing teams operate across more channels and datasets than ever before, many organizations struggle to distinguish between companies that are structurally attractive and those showing concrete signals that engagement is timely. According to ALURA, this often leads to inefficient use of sales capacity, inconsistent follow-up and reduced predictability in pipeline development.
Alura Pexus is intended to provide a more structured approach to prioritization. Rather than increasing lead volume, the system supports decision-making by helping organizations identify which prospects align most closely with their strategic objectives and which show observable signals that suggest a higher likelihood of productive dialogue.
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“In many organizations, the challenge is no longer finding leads, but deciding which ones deserve attention,” said Jonas Bakke, CEO and co-founder of ALURA. “This system is built to support clearer prioritization by grounding decisions in defined criteria instead of assumptions or intuition.”
The lead enrichment system was initially developed to support ALURA’s own commercial operations, where consistent prioritization was required across outbound and inbound activities. After extended internal use and refinement, the system is now being offered externally as both a standalone service and as part of broader AI-driven lead acquisition and outreach programs. These programs are currently being applied in B2B environments in Norway and internationally.
At a practical level, the system assembles and structures publicly available and appropriately licensed company data into comprehensive lead profiles. Instead of presenting raw data in isolation, the system organizes information in a way that enables commercial teams to compare opportunities, align internally and focus outreach efforts more effectively.
Each lead is evaluated against a customer-defined Ideal Customer Profile and assessed across a limited set of clearly articulated dimensions. These include structural alignment with the target profile, observable market activity that may indicate change or growth, reachability of relevant decision-makers, and external reputation signals. The outcome is a transparent, letter-based prioritization from A to F, allowing teams to quickly identify which prospects represent the strongest overall match within agreed parameters.
“For sales and marketing teams, consistency in prioritization is often just as important as ranking,” said Ferdinand Stene, co-founder and CTO of ALURA. “By making the logic behind prioritization explicit and adjustable, the system supports better internal alignment and higher execution quality.”
ALURA notes that the system is particularly relevant in B2B contexts where proactive outreach, account-based engagement or targeted prospecting are central to growth strategies. Typical applications include narrowing focus to a manageable set of high-priority accounts, designing differentiated outreach strategies for different lead categories, and establishing a shared factual basis for commercial planning across teams.
In selected internal use cases, ALURA reports that AI-driven commercial initiatives built on similar prioritization principles have supported several hundred booked meetings, contributed to the development of multiple automated lead acquisition channels and materially improved response times to inbound and outbound inquiries. While outcomes vary by organization and market, these observations have influenced how the system has been designed and applied.
“Our experience indicates that better prioritization tends to improve both efficiency and the quality of commercial dialogue,” said Marius Reidar, co-founder & Chief Operating Officer of ALURA. “By basing decisions on observable signals, organizations are better positioned to engage prospects with relevance and confidence.”
ALURA emphasizes that transparency and governance are central to the system’s design. Customers retain control over how their Ideal Customer Profile is defined, how prioritization criteria are weighted and how the model evolves as strategies or market conditions change. The company is also exploring future enhancements, including trigger-based alerts for significant lead-level changes and extended trend analysis to support longer-term planning.
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