Mae Cornes
Photo Courtesy of: Primetime
Artificial intelligence is no longer confined to automating repetitive tasks or responding to customer inquiries. Primetime, a newly launched AI company, believes AI should function as an active team member rather than a passive tool.
Co-founded by Boris Lapouga and Zach Lupei, the company has secured $460,000 in early funding from investors including Flex Capital and HMC INQ. Its AI agent, Prime, helps teams with decision-making, document drafting, and data analysis, while also maintaining long-term memory and context awareness.
“We are moving beyond task-based automation,” said Lapouga, the company’s Chief Technology Officer. “Prime isn’t just answering questions—it’s remembering conversations, understanding project goals, and participating in actual work.”
AI With Persistent Memory and Adaptive Learning
Many AI systems operate in isolation, losing context between interactions. Lapouga’s patent-pending memory and context management system allows Prime to function more like a human coworker by remembering previous discussions, tracking project details, and adapting to user preferences over time by using semantic and episodic memory allocation.
While most of Silicon Valley is building vertical chatbots, they are building the next phase AI interaction which is much more human-like. Prime is much more like a co-worker than an application.
Lapouga’s pioneering adaptive learning framework, which utilizes a proprietary multi-modal knowledge graph architecture, has been recognized by institutional VCs that fund AI startups as a breakthrough in contextual reasoning systems. This innovation enables AI agents to iteratively refine their understanding of workplace dynamics – a capability previously unattainable in most commercial AI systems.
This capability addresses a common frustration with workplace AI: the need to repeatedly input the same information at the leaf and not being able to iterate on created knowledge with their colleagues. A 2023 survey by Gartner found that 62% of employees feel AI tools fail to provide continuity between conversations, making them less useful for complex workflows. Primetime aims to solve this with an AI that connects discussions across different tools and platforms.
Prime integrates with Slack, Microsoft Teams, Google Meet, and Primetime’s own Canvas system, allowing employees to interact with it across multiple communication channels without losing context. This solution demonstrates how Lapouga’s work enables AI systems to overcome the ‘tool silo’ problem that McKinsey estimates costs enterprises $12M annually per 1,000 employees.
The yielded value of using Primetime is centralizing any company knowledge and enabling multiple AI Agents, internal or external to not only tap into company’s data, but also execute tasks assigned to them by the users.
This approach boosts productivity across the entire industry that adopts Primetime as their coworker, allowing people to quickly query past information, make informed decisions, delegate tasks to AI, and generate reports, summaries, or various analyses.
In the age of rapid technological progress and the need to move faster, any company using Primetime will be able to stay productive, competitive and elevate their businesses and value proposition to their own customers.
Independent analysts note that Lapouga’s architectures are redefining industry standards for AI collaboration, with potential applications to a wide array of industries that require to remain context-aware across multiple tools. Flex Capital’s investment memo specifically cited ‘The Primetime team is working on building a platform that allows companies to import and collaborate with Artificial Intelligence (“AI”) agents. AI is the frontier of technology today, and agents are at the cutting edge of artificial intelligence.’
AI Could Reduce Information Overload in the Workplace
Information overload is a growing problem in modern workplaces. Employees often spend hours searching for documents, messages, or project updates scattered across multiple platforms. A 2022 study by McKinsey & Company found that knowledge workers spend nearly 20% of their workweek searching for information.
Lapouga’s Primetime AI is designed to reduce this inefficiency by using a knowledge graph that connects data across different sources. This solution is drastically different from available market solutions that work with Vector based solutions only which are limited and often as good as the user’s query, often producing incorrect answers. Additionally Vector storages are lacking context awareness across multiple data storages. Instead of requiring employees to manually sift through emails, chat threads, and shared drives, Prime retrieves relevant information based on the context of the conversation.
“Most companies today use multiple AI tools that don’t communicate with each other,” said Lapouga. “We are building an AI that understands the workplace as a whole, not just individual tasks.”
AI as an Active Participant in Decision-Making
AI has long been used for automation, but its role in decision-making has been more limited. Many businesses remain hesitant to trust AI with strategic or analytical tasks, citing concerns about accuracy and transparency.
Lapouga’s AI system, implemented at Primetime, aims to go beyond automation by assisting teams with complex decision-making processes. Instead of simply retrieving information, Prime is capable of analyzing trends, identifying patterns, and generating data-driven recommendations.
For example, a manager preparing a quarterly performance review could ask Prime to compile productivity metrics, summarize key insights, and suggest areas for improvement. Unlike standard automation tools, Prime is built to adapt its analysis based on previous team discussions and company priorities.
A 2023 Deloitte survey found that 78% of executives believe AI will play a larger role in business decision-making within the next five years. However, adoption remains uneven, with only 24% of companies currently using AI for advanced analytics and strategic planning.
Challenges of Workplace AI Adoption
Despite advances in AI, workplace adoption is still met with skepticism. Employees often question the reliability of AI-generated insights, and organizations worry about data security and compliance risks.
Primetime acknowledges these concerns and has focused on developing strict access controls and encryption protocols. Lapouga emphasizes that AI should function as a support system rather than a replacement for human judgment.
Regulatory frameworks are another challenge. The European Union’s AI Act, set to take effect in 2025, will introduce stricter compliance requirements for AI systems that impact hiring, performance evaluations, and financial decision-making. Companies developing AI-driven workplace tools will need to adapt to these evolving regulations.
AI in the Workplace: What’s Next?
Investment in AI-driven workplace technology is increasing. A 2023 PwC report projected that AI automation could contribute $15.7 trillion to the global economy by 2030, with business productivity and efficiency gains as primary drivers.
Primetime plans to use its initial funding to expand product development and onboard early customers. The company believes that AI systems like Prime will eventually become as integral to business operations as traditional software tools.
“We’re not trying to replace people,” Lapouga said. “The goal is to build an AI that actually works alongside teams, making collaboration smoother and more effective.”
As AI technology advances, organizations must carefully consider its role in their workflows. Lapouga’s vision suggests a future where AI transitions from being a mere tool to becoming an integral team member.