From One AI Use Case to an Enterprise-Wide Vision.
How Bectorfood Started Its Enterprise AI Journey with Wisebric
From Meeting Intelligence to a broader enterprise AI adoption strategy, built around enterprise control, practical business value, and long-term scalability.
Food Manufacturing
Enterprise AI Needed to Work on Enterprise Terms.
For Bectorfood, the opportunity to adopt artificial intelligence was clear. The challenge was finding the right way to introduce it into everyday business operations.
Like many enterprises, Bectorfood wanted to move beyond AI experimentation and explore applications that could address practical business requirements.
Meetings presented a natural starting point. Every business meeting generates valuable information: discussions, decisions, commitments, action items, and contextual knowledge.
But much of this information can remain distributed across recordings, transcripts, emails, and individual employees. Bectorfood wanted to make meeting knowledge more accessible and useful.
However, selecting the right solution required addressing three important considerations.
- 01 /Enterprise Control
Bectorfood wanted meeting conversations and organizational knowledge to remain within an environment it could govern. The AI solution needed to align with its enterprise deployment requirements.
- 02 /Data Retention
The organization wanted to define its own requirements for retaining meeting information and organizational knowledge.
- 03 /Commercial Scalability
With more than 1,000 potential users, Bectorfood needed to consider the long-term economics of enterprise-wide adoption. Conventional per-user subscription models were an important consideration when evaluating the commercial scalability of the solution.
The challenge was not simply to find another meeting assistant. It was to identify a practical starting point for enterprise AI that aligned with Bectorfood's operational, governance, and commercial requirements.
Turning Meeting Conversations into Organizational Knowledge.
Bectorfood selected Wisebric Meeting Intelligence as the first step in its enterprise AI journey.
The solution was implemented within Bectorfood's private-cloud environment and is now live for its teams.
The objective went beyond meeting transcription and summarization. Wisebric Meeting Intelligence helps turn conversations into information employees can organize, retrieve, and use in their daily work.
- 01
Capture Important Conversations
Capture meeting discussions so important information remains available for review.
- 02
Generate Transcripts and Summaries
Transform meeting conversations into transcripts and structured summaries, making important discussions easier to revisit.
- 03
Identify Decisions and Action Items
Extract action items to help employees follow up on meeting decisions and commitments.
- 04
Organize Meeting Knowledge
Allow users to manually add meeting conversations to relevant client or project knowledge folders.
- 05
Retrieve Context Across Meetings
As meeting information accumulates, employees can ask questions and retrieve relevant context across conversations.
Instead of manually searching through multiple recordings, transcripts, and emails, employees can access relevant meeting knowledge through Wisebric.
The goal was not just to remember what happened in a meeting. It was to make that information useful after the meeting ended.
Start with a Business Problem. Build the Foundation. Expand with Confidence.
Rather than attempting to transform every business process at once, the engagement began with a clearly defined use case.
- 01
Identify the Opportunity
Meeting Intelligence was identified as an initial enterprise AI application that addressed a recognizable business need.
- 02
Align with Enterprise Requirements
The solution approach considered Bectorfood's private-cloud environment, governance expectations, retention requirements, and commercial scalability.
- 03
Deploy the Solution
Wisebric Meeting Intelligence was implemented within Bectorfood's private-cloud environment.
- 04
Introduce Everyday Usage
The solution went live, enabling teams to capture meeting conversations, generate summaries, identify action items, and organize meeting knowledge.
- 05
Expand the Enterprise AI Engagement
Following the initial implementation, Bectorfood signed an agreement to expand Wisebric across the enterprise. The expanded scope includes enterprise AI chat, business knowledge and data connections, and personalized leadership AI assistants.
What began as a focused Meeting Intelligence implementation became the starting point for a broader enterprise AI journey.
Beyond a Successful Deployment.
The initial implementation established a working enterprise AI use case within Bectorfood's environment. More importantly, it created a foundation for continued AI adoption.
- A Live Enterprise AI Application
Wisebric Meeting Intelligence is deployed in Bectorfood's private cloud and is being used by its teams.
- More Accessible Meeting Knowledge
Meeting summaries, action items, knowledge folders, and contextual retrieval help employees organize and access information generated through business conversations.
- Alignment with Enterprise Requirements
The private-cloud implementation supports Bectorfood's requirement for greater control over its AI deployment environment.
- A Broader Enterprise Engagement
The engagement has expanded beyond the initial application, with an agreement covering additional enterprise AI capabilities.
- A Foundation for Long-Term Adoption
The initial use case provides a practical starting point for connecting more organizational knowledge and introducing additional AI experiences.
Business Benefits
- Information Accessibility
- Employees have a structured way to revisit meeting discussions and retrieve relevant context.
- Knowledge Continuity
- Meeting information can be organized into reusable knowledge folders rather than remaining isolated in individual recordings or documents.
- Operational Support
- Structured summaries and action items help teams review discussions and follow-up requirements.
- Enterprise Scalability
- The engagement considers enterprise deployment requirements and the commercial implications of adoption across a large potential user base.
- Expansion Opportunities
- The initial implementation provides a foundation for extending AI into business knowledge access and leadership support.
From Meeting Intelligence to Connected Enterprise AI.
Meeting Intelligence was the starting point, not the final destination.
Bectorfood and Wisebric are expanding the engagement toward broader access to organizational knowledge and business information. The next phase brings together enterprise AI chat, business knowledge connections, personalized leadership assistants, and user enablement.
Enterprise AI Chat and Knowledge Integration
The expanded solution will connect relevant organizational knowledge and business data to enterprise AI chat.
The objective is to help employees find useful information through a conversational experience rather than manually navigating multiple documents, reports, and systems.
This approach can create a more accessible way to work with enterprise knowledge while respecting the organization's deployment and governance requirements.
Personalized Leadership AI Assistants
Another important part of the expanded engagement is the delivery of personalized AI assistants for Bectorfood's leadership team.
These assistants are intended to help business leaders access information relevant to their responsibilities, business priorities, and KPIs.
Leadership briefing example
Give me my business update for today.
Instead of manually reviewing multiple dashboards, reports, and updates, a leader could receive a consolidated business briefing. Depending on the leader's responsibilities and available connected information, the experience could bring together:
- Sales performance
- Market-share information
- Financial indicators
- Relevant business KPIs
- Areas requiring management attention
The objective is to move beyond simply displaying numbers toward presenting relevant business context in a conversational experience. This capability forms part of the enterprise AI expansion scope.
Enterprise AI Training and Enablement
Technology alone does not create enterprise-wide adoption. Employees and leaders need to understand where AI can support their responsibilities and how to incorporate it into everyday work.
The next phase includes structured training and enablement to help Bectorfood teams become comfortable using enterprise AI.
As adoption expands, additional opportunities for specialized AI assistants and agents can be identified based on business processes, recurring challenges, and departmental requirements.
The People Behind the Transformation.
Enterprise AI adoption is a collaborative journey involving business teams, technology stakeholders, and implementation partners.
Enterprise AI Adoption Doesn't Have to Start with Everything.
It has to start somewhere.
The Bectorfood journey illustrates a practical approach to enterprise AI adoption.
- Start with a recognizable business challenge.
- Deploy a solution that aligns with enterprise requirements.
- Introduce AI into everyday work.
- Build confidence through actual usage.
- Expand into broader AI capabilities as the organization progresses.
For Bectorfood, that journey began with Meeting Intelligence. The broader engagement now extends toward connected enterprise knowledge, AI chat, and personalized leadership assistants.
One practical use case can become the foundation for a much larger enterprise AI opportunity.
Your Enterprise AI JourneyWhat Could Your First AI Use Case Unlock?
Every organization has different challenges, systems, and priorities. Wisebric helps enterprises identify practical AI opportunities, deploy solutions aligned with their requirements, and expand adoption over time.