For years, software was a tool—a dashboard you logged into, software you wielded to execute a specific task. No matter how advanced the tool, “Software-as-a-Service” (SaaS) demands that you educate yourself to master the tool and achieve the promised outcomes.
But in 2024, innovation intelligence took a leap forward. While the market buzzed with talk of Generative AI and LLMs, another quiet revolution was reshaping how enterprises extract actionable insights: the rise of Service-as-a-Software, powered by autonomous AI agents.
This shift wasn’t just about cooler tech. It was driven by real business needs: a growing recognition that corporate innovation teams and investors needed more than data dumps—they needed personalized insights. Fast. Tailored. Done For You.
At entrapeer, this journey wasn’t theoretical. In 2024, we pivoted from a DIY SaaS platform to a multi-agent AI ecosystem that automates everything from startup scouting to portfolio tracking. What started as a use case search engine evolved into a white glove, AI-powered innovation intelligence solution, capable of cutting research times from weeks to days and transforming overburdened teams into strategic powerhouses.
Welcome to the era of Service-as-a-Software, where intelligent agents drive actionable insights in real time. This isn’t just a new way to work; it’s the future of work.
The Road to SaaS+: Why Traditional Software is No Longer Enough
For years, SaaS platforms were the gold standard in enterprise software. Platforms like Salesforce, HubSpot, and Tableau offered self-service tools that users could configure and manage. But SaaS had a major flaw: it required users to do the heavy lifting.
Imagine trying to stay on top of emerging technologies, market trends, and new competitors using a SaaS platform. Sure, the tool might provide access to data, but the burden of finding, synthesizing, and acting on insights fell on human teams.
As Gartner noted in their 2024 Top Strategic Technology Trends, enterprises are now demanding solutions that go beyond dashboards and reports. They want innovation intelligence systems that deliver personalized insights—not just data.
This shift reflects a broader trend across industries:
AI is moving from decision-support to decision-making.
Autonomous agents are replacing manual processes across workflows.
Organizations are adopting innovative intelligence solutions to reduce costs, increase speed, and improve accuracy.
The traditional SaaS model isn’t built to deliver these outcomes. It’s reactive, not proactive. That’s why companies like entrapeer are building AI agents to automate complex workflows and deliver actionable insights in real-time.
The DIY Era: Lessons Learned
Before we get ahead of ourselves, let’s rewind to the pre-AI agent era of entrapeer.
We’re a little biased but the platform was, by all customer accounts, impressive. Users could access the world’s largest database of realized use cases, emerging startups, market research reports, and competitive intelligence.
But there was one catch: users had to navigate it themselves.
At first glance, this DIY innovation intelligence platform seemed ideal for innovation teams who wanted flexibility and control. A telecom giant could search for 5G-related use cases, while a bank might dig into fintech trends. But soon, the cracks began to show.
Three core challenges emerged:
- Time-Intensive Data Analysis: Users spent hours sifting through reports, articles, and data points, trying to find the most relevant insights.
- Overwhelming Decision-Making: The sheer volume of data created cognitive overload, making it hard to identify actionable insights.
- Lack of Tailored Support: Nuanced organizational goals often required custom research that users couldn’t execute on their own. Users could request custom research, but delivery times—though well within industry standards—were long because humans cannot work around the clock.
These pain points aren’t unique to Entrapeer users. They’re endemic across industries. In a world where markets change daily, “time to knowledge” is a critical metric. Enterprises can no longer afford to spend weeks on manual research.
The solution? Automation.
But not just any automation. What these companies needed was a system that could curate, synthesize, and deliver insights tailored to their objectives—without the heavy lifting. This was the driving force behind our pivot to an AI agent ecosystem (i.e. the “Service-as-a-Software” model), which embodies the next step in innovation in artificial intelligence.
The Pivot: From Software-as-a-Service to Service-as-a-Software
Our shift to Service-as-a-Software (SaaS+) was inspired by larger trends in artificial intelligence and innovation sweeping through the tech world: the realization that automation can replace complex manual tasks with intelligent digital agents.
In traditional SaaS models, users are given tools to perform tasks themselves. But in a multi-agent Service-as-a-Software model, users rely on autonomous agents to handle complex workflows. Think of it this way:
- Traditional SaaS platforms offer tools and dashboards that users must navigate themselves.
- Service-as-a-Software platforms, like entrapeer, provide a team of digital agents that perform tasks on the user’s behalf.
At first glance, this shift may seem like a simple upgrade in automation. But the reality is that the SaaS+ model isn’t just more efficient—it fundamentally changes how organizations access, synthesize, and act on data. The growing need for speed, accuracy, and scalability is reshaping what enterprises expect from software, driving the adoption of AI-powered agents.
This realization, paired with several converging trends, made our pivot to autonomous agents both timely and necessary.
The AI Agent Revolution: What’s Driving the Shift?
Our shift to SaaS+ (powered by AI agents) was driven by several converging trends shaping the future of work:
- AI-Augmented Applications: AI is driving unprecedented autonomy across organizations, with 69% of executives believing it brings new urgency to reinvent how technology systems and processes are designed, built, and operated.
- The Proliferation of Data: Organizations are drowning in data. Autonomous agents can process vast amounts of information in seconds, delivering curated insights faster than any human team.
- The Generative AI Boom: Generative AI has made artificial intelligence and innovation more accessible. Tools like ChatGPT have shifted expectations, making businesses demand more intelligent, conversational interfaces.
- Demand for Speed and Accuracy: Enterprises in fast-moving industries—like finance, automotive, and telecom—are pushing for faster insights. Traditional methods simply can’t keep up.
By identifying these trends early, entrapeer set out to build a system that not only delivers faster insights but also mimics the workflows of top innovation analysts. Here’s how it works.
How Entrapeer’s AI Agents Work
Entrapeer’s multi-agent ecosystem is designed to reduce redundancies, streamline workflows, and provide actionable insights in record time. How?
Well, we began by identifying the most complex, time-consuming workflows that enterprises, VCs, and startups grapple with, things like:
- Market research
- Due diligence
- Benchmarking
- Startup scouting
- Company tracking
- And so on.
Then, we pooled our team’s knowledge and decades of corporate innovation experience to outline the ideal workflows for each use case. From there, we built a specialized agent to execute each workflow, tapping other specialized agents much like a team of human specialists would collaborate. Leveraging the realized use cases and real-time market data that form the foundation of the entrapeer platform, these agents could perform tasks in hours that once took weeks.
Take Reese, our Research Manager Agent. A global enterprise in the automotive sector requested a custom report on the European commercial vehicle market. Specifically, they wanted to understand the impact of electrification efforts, Chinese imports, and the European Green Deal.
Within minutes, Reese generated a comprehensive research outline tailored to the client’s preferences and market position. Once the client provided feedback and approved the outline, Reese completed the report within 48 hours—a feat that would typically take multiple human analysts weeks or months to achieve.
Meet the Agents
Our conversational AI agents act as your digital coworkers, collaborating with you and each other to deliver customized innovation insights. Here’s a breakdown of the core agents, their roles, and their value to enterprises.
| Agent Name | Role | Use Cases | Best For | Avg. Time Savings | Avg. Cost Savings |
|---|---|---|---|---|---|
| Peer | Concierge Agent | Manages workflows and connects users to agents | Innovation Teams, VCs | 97% | NA |
| Reese | Market Research Manager | Conducts trend reports, competitor analysis | Strategy Teams, Corporate Development, Startups | 84% | $50K per report |
| Scout | Scouting Manager | Identifies startups and new technologies | Corporate Innovation, Investment Teams | 90% | $25K per scouting |
| Nova | News Manager | Aggregates industry news and competitor updates | Marketing, Competitive Intelligence, Startups | 52% | $15K per quarter |
| Tracy | Tracking Manager | Monitors real-time market data | Portfolio Managers, Analysts | 96% | $50K per year |
| Nash | Competitor Analysis Manager | Reports on competitor news, pivots & milestones | Strategy Teams, Corporate Development, Startups | 85% | $30K per report |
Users interact with Peer, our AI Agent Concierge, via chat to receive answers to straightforward questions or define their objectives. Peer then assigns the task to the appropriate Manager Agents, who coordinate with team member agents to execute the work.
Each Manager Agent operates autonomously, but they also collaborate across workflows, ensuring seamless task execution. For example, when drafting a company tracking report, Tracy will tap Nova for news about the companies being tracked, Scout for those companies’ usecases, and Nash for a list of the companies’ competitors. This kind of inter-agent collaboration creates a holistic innovation intelligence experience.
This seamless collaboration across agents creates a holistic innovation intelligence experience, helping enterprises stay ahead of emerging trends and competitive threats.
How AI Agents Add Value & Accelerate Time to Knowledge
The primary value of AI agents is their ability to automate repetitive tasks, freeing up human teams to focus on creative, strategic work.
Consider these real-world case studies from our happy customers:
1. Automotive: Electric Vehicle Innovations
A leading automotive company accelerated innovation during a competition by leveraging entrapeer’s research capabilities. Six detailed reports were delivered in just two days, providing real-world examples that participants praised for their clarity and value.
2. Finance: Fintech Partner Identification
A prominent bank utilized entrapeer to onboard a new team member without prior banking experience. The platform’s curated insights and training materials quickly equipped her with the knowledge to confidently engage with business units.
3. Airlines: Sustainable Aviation
A major airline worked with entrapeer to establish an international innovation hub. Using AI-driven benchmarking and strategic analysis, they identified the best location and strategy, launching a successful innovation program that supports cutting-edge industry solutions.
4. Telecommunications: 5G Competitor Tracking
A telecom leader relied on entrapeer’s AI agents to scout emerging startups and track competitors. The comprehensive report highlighted high-potential companies and provided trend insights, which helped align future-focused strategies.
These case studies highlight how AI agents deliver immediate value across industries, empowering innovation teams to reduce time to knowledge and make faster, more informed decisions. But this is just the beginning.
A Vision for 2025: Bridging the Gaps in AI Adoption
By the end of this year, entrapeer plans to introduce a new wave of specialized AI agents to expand our Service-as-a-Software (SaaS+) model, reinforcing our commitment to innovation intelligence.
- Benji (Benchmarking Manager): Identifies where a company stands against its competitors, cutting through bias by providing data-backed insights.
- Dewey (Due Diligence Manager): Automates legal, financial, and operational risk assessments, ensuring organizations make decisions with confidence.
- Lia (Startup Liaison Manager): Builds bridges between enterprises and startups, helping innovation teams discover the right partners faster.
Unlocking the true potential of these agents requires more than just deploying the technology. It means addressing the real-world challenges preventing the widespread adoption of autonomous AI.
Despite the growing excitement around AI agents, many organizations remain hesitant to embrace automation at scale. According to the World Economic Forum, 40% of companies plan to reduce their workforce due to AI automation. Yet, that same report predicts a net increase of 78 million jobs globally by 2030, suggesting that innovation in artificial intelligence won’t eliminate jobs—but it will transform them.
The challenge for businesses is finding the balance between automation and augmentation—and that’s where entrapeer stands apart.
Why the Future is Human-Centered—Even in an AI-Driven World
We don’t believe in replacing human workers with AI agents. Instead, we see these tools as powerful augmentations to human potential, freeing people from repetitive, time-consuming tasks so they can focus on strategic, creative work. After all, it’s the people within an organization who build its culture, foster resilience, and drive innovation—not the technology.
But businesses still face three key challenges in adopting AI agents:
- Cultural Resistance: Shifting from manual processes to AI-driven workflows requires a change in mindset. Many organizations fear losing control to machines or worry about job displacement. Entrapeer addresses this by positioning agents as digital coworkers—not replacements—working alongside human teams to empower them.
- Data Silos: For AI agents to deliver accurate insights, they need access to clean, structured data. Yet, data fragmentation remains a significant barrier across enterprises. Our agents are designed to navigate and integrate disparate data sources, ensuring businesses can fully leverage their existing assets without reinventing the wheel.
- Ethical Concerns: As AI agents take on more decision-making tasks, companies must grapple with questions of trust, fairness, and transparency. According to eWEEK, 77% of executives agree that unlocking the true benefits of AI requires building it on a foundation of trust. Entrapeer’s agents are built with transparency at their core, ensuring users understand how insights are generated and can verify their accuracy.
Join the AI Agent Revolution
As companies integrate more AI agents into their workflows, they must remember one essential truth: technology will never replace the human element. While autonomous agents can execute tasks with speed, accuracy, and scale, it’s the people within an organization who bring creativity, empathy, and cultural resilience—the traits that machines can’t replicate.
Entrapeer’s vision for the future isn’t a workforce reduced by AI. It’s a workforce enhanced by AI, with people freed from repetitive tasks so they can focus on the uniquely human challenges of leadership, strategy, and innovation.
By 2025, businesses that embrace this vision will outpace their competitors, reduce time to knowledge, and position themselves as leaders in their industries. Those who resist risk falling behind in an increasingly fast-paced, AI-driven world.
The question for businesses isn’t whether to adopt AI agents, but how to do it responsibly—with trust, transparency, and humanity at the core.
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