Business leaders across various industry domains discuss a common set of challenges or “pain points” when working with legacy tools and manual processes. These challenges also present an opportunity for solution providers like Onix to address using Agentic AI technology.
3 pain points across enterprises – and how AI agents can overcome them
As a rapidly increasing and impactful technology, Agentic AI platforms can truly deliver a breakthrough when they can address real-world pain points across enterprises. By doing this, enterprises can achieve a clear, measurable business outcome in terms of cost reduction or revenue increase.
Based on our customer interactions, the Onix team identified 3 categories of chronic business challenges faced by modern companies, and how Agentic AI can address each of them.
- High customer churn and expensive service
In any industry domain, customer-centric companies struggle with high volumes of repeat customer calls, along with unresolved customer issues. Most CRM systems operate using “siloed data,” which prevents them from having a comprehensive 360-degree view of any customer. This often leads to slower issue resolution and even customer churn. Customer service agents also lack contextual information when interacting with any customer.
How Agentic AI addresses this pain point:
Enterprises working with AI agents can identify and resolve issues on their first customer contact. With post-call analysis, AI agents can “self-heal” unresolved customer issues, thus eliminating any repeat calls. Agentic AI systems are also designed to integrate real-time data from third-party legacy applications, including CRM. This provides customer service agents with a complete 360-degree view of any customer, thus enabling contextual analysis, which can lead to faster issue resolution and lower customer frustration. - Manual processes and inefficient workflows
Despite the emergence of AI technology, enterprises continue to invest high capital in manual, repetitive processes, along with high administrative overload (like scrum management) and complex workflows (like underwriting). Besides human errors, manual processes and workflows create operational bottlenecks, thus causing cost escalation and delays. Employees are unable to improve their productivity, getting “stuck” in manual tasks instead of elevating to high-value, strategic tasks.
How Agentic AI addresses this pain point:
By deploying a variety of AI agents, enterprises can avoid the costs of manual human work, administrative overheads, and back-office operations. AI agents can automate document-centered workflows such as insurance underwriting, thus saving the costs of hiring and training the workforce. Agents can also perform administrative tasks such as scrum management and cloud migration. - Extended asset downtime
Industries like manufacturing, logistics, and distribution depend on the availability of physical assets. That said, there’s an enormous gap between real-time data (error codes, IoT alerts) and actionable business processes. This can lead to preventable asset downtime, high maintenance costs, and inefficient resource usage (for instance, high fuel consumption).
How Agentic AI addresses this pain point:
Agentic AI can improve the user’s interaction with physical assets and products across B2B industries. By constantly monitoring real-time asset data (for example, vehicle error codes), it can automatically convert real-time alerts into actionable work orders, thus minimizing downtime. AI agents can also detect waste in the form of extended vehicle (or machine) idling and take appropriate action to reduce wastage costs.
The need for centralized intelligence in enterprises
It’s no surprise that organizations are struggling with legacy systems and their bottlenecks in current times. Despite having the domain experts and data, enterprises lack a centralized intelligence framework to empower AI agents to work deterministically on the available data and knowledge.
AI agents can only be as effective as the data provided to them. Companies cannot acquire measurable, quantifiable business value by investing in a single AI agent or system. Instead, what they need is to address the gap between data and context, which restricts the effectiveness of deployed agents.
The Onix solution: architecting the network of deterministic agents
While other solution providers are developing AI agents for a specific use case or application, Onix is focused on building a foundational data baseline that helps in creating smart, deterministic, and scalable agents.
With Onix, enterprises can look forward to a network of specialized agents for underwriting, customer service, and asset monitoring to operate with high speed and accuracy.
Onix is providing the essential foundation for:
- Centralized context and knowledge
This involves the integration of critical components, including data governance, data lineage, security, and context as a unified layer. This baseline addresses the accuracy problem of siloed AI solutions, thus ensuring that their output is derived from accurate enterprise data. - Deterministic results
Onix focuses on delivering AI agents that can provide correct, predictable, and repeatable actions. This elevates agents from a highly creative tool to a reliable, mission-critical asset that can handle high-value tasks. - Faster agent development and deployment
Lastly, Onix’s Wingspan agentic AI platform accelerates the agent development and deployment process. By automating data engineering and governance, business teams can leverage this platform to build, test, and deploy custom agents to unlock business value and overcome legacy challenges.
Conclusion
For modern enterprises, adopting Agentic AI technology is similar to building a complex railway line across rugged terrain. The initial infrastructure – such as data governance and knowledge graphs – requires enormous investment and engineering skills. However, once the tracks are laid, enterprises can run their autonomous trains (or custom agents) to achieve business value and insights.
Why is Wingspan regarded among the best AI agent platforms? Contact our team to learn more.
