Building vs. Deploying Conversational AI Platform

Working with conversational AI is challenging. Deploying virtual assistants requires ongoing optimization, monitoring, and training. It is not as simple as pressing a switch and then never looking back. Hence, many businesses prefer buying pre-built conversational AI platforms, while tech-savvy companies or those needing tailored solutions consider building their platforms and systems from scratch.

This choice is not simple. Custom building offers control but demands expertise. Pre-built solutions provide faster implementation but limit customization. Before committing resources, carefully assess your capabilities, budget constraints, and specific business needs.

The following blog dives into both approaches. We will be comparing costs, timelines, customization options, scalability, and performance to help guide you toward the option that best fits your business situation. 

Building a Conversational AI Platform

Building an in-house conversational AI platform is a massive undertaking. You are developing a highly complicated AI-driven technology from the ground up to gain complete control, which, as it sounds, is not easy by any means. 

It remains a highly demanding project even if you are customizing an existing framework because you still need a large pool of resources and specialists, including data scientists to manage conversational data and underlying intents, conversation designers to map out user interaction flows, and integration specialists to ensure compatibility with contact center platforms and backend systems.

Also, the work does not end once the system is live. That is just the beginning. Just like a human agent, a conversational AI platform requires ongoing monitoring and updates to remain effective. It needs continuous training to stay aligned with evolving customer needs, company policies, and product changes. Building a platform from scratch can be a powerful option, but it is also resource-intensive and requires long-term commitment.

Pros

• Full Control: You own the conversational AI platform, making it easy to oversee the development process, implement security measures, handle maintenance, and apply updates as needed.
• Data Ownership and Management: You decide how data is collected, stored, and used, which is usually a huge ask.  
• Customization: This is the real reason why you are opting to build your own conversational AI platform. You want a tailored solution that meets your specific requirements and supports desired features. 
• Compatibility: You built it, so it is naturally completely compatible with your existing systems and infrastructure. 

Cons

• High Costs: Building a custom conversational AI platform is a highly expensive venture. Everything from development and research to hiring skilled personnel and testing demands a significant investment. 
• Time-Hungry: It is just not money. Building an in-house conversational AI platform takes a lot of time, so deployment and implementation can take years. 
• Ongoing Maintenance and Updates: It is more of a challenge than a pitfall, but be ready to dedicate a lot of effort to a continuous cycle of updates and troubleshooting. Since technology is moving so fast, it's often difficult to keep up with new trends, best practices, and improvements. So, staying competitive means continuously improving your platform, not just maintaining it.
• Team Dependency: AI-driven platforms are highly complicated to create and manage from scratch. If key members leave, you will have to find a suitable replacement in time or risk jeopardizing the longevity of your creation.

Deploying a Conversational AI Platform

If you are more concerned with time, cost, and scalability, buying an all-in-one platform is a practical option. While many pre-built conversational AI systems require businesses to forfeit some level of control, this isn’t always the case. Some vendors offer flexible, customizable solutions tailored to your specific needs and complex interactions, often ready to deploy within 3 months. Even so, a slight trade-off in control can be a small price to pay when weighed against the broader benefits.

Additionally, buying pre-built conversational AI platforms can often be the only option for businesses that need to deploy chatbots or virtual assistants quickly. While they offer less control than custom-built solutions, the trade-off brings faster implementation and proven functionality. Most businesses find the limitations acceptable when weighed against the practical benefits of rapid deployment and established reliability.

Pros

• Faster Deployment: Launch within days or weeks rather than months.
• Regular Updates: Vendors maintain and improve the technology over time, leaving you to focus purely on growth. 
• Analytics Tools: Buying a conversational AI platform means getting easy access to pre-built dashboards for tracking performance and other metrics for valuable insights.
• Scalable Infrastructure: You can scale up and down as needed without worrying about building custom systems. 
• Excellent Integrations: Connect with common business tools and APIs.
• Lower Technical Barrier: You can get by with minimal expertise. 
• Cost Predictability: Subscription models make expenses predictable without the right vendor.
• Built-in Compliance: Your AI platform comes packed with security and privacy standards. 

Cons

• Limited Customization: You must accept some levels of restriction when it comes to modifying features and functionalities.
• Vendor Dependencies: Your stability, continued support, and need for specific features solely rely on the vendor. 
• Branding Constraints: Without an enterprise vendor, your AI-driven platform may struggle to fully match your specific brand voice.
• Data Ownership: Depending on the vendor you are working with, you may or may not have rights to conversation data. 

Reasons to Choose a Conversational AI Platform Over a Simple Software

Building a custom conversational AI platform costs substantially more than deploying a pre-built solution, both initially and long-term. For most businesses, especially those without existing AI expertise, the deployment approach wins clearly on cost-effectiveness. 

Pre-built solutions minimize initial investments and ongoing expenses while offering scalable features suitable for various business requirements. Unless you have specialized use cases that justify custom development, it is generally better to find a good AI vendor.

You also get to enter the market a lot faster with pre-packed tools and features without having to worry about any maintenance or development requirements. Leave that to the vendor.

How to Choose the Best Conversational AI Solution for Your Needs

Consider these five key factors when choosing a conversational AI platform:

• Business Requirements: List specific tasks your conversational AI needs to perform such as customer service, status updates, answering questions, internal automation, etc. Match these requirements to platform capabilities. 
• Budget Constraints: Every business has to keep up with a cost structure. Check the upfront investment, subscription fees, scaling expenses, and other related costs to determine if the solution fits within your budget. Do not forget to factor in hidden costs like API calls and premium features.
• Integration Compatibility: Ensure the platform works well with your existing systems and communication channels. There is no point in paying for something that adds friction to your operations or worse. 
• Technical Expertise: Assess your team's skills. Some platforms need coding knowledge while others offer no-code interfaces. Rasa requires Python skills; Dialogflow works with minimal technical background.
• Vendor Support and Reliability: Review customer feedback, response times, and update frequency to avoid disruptions. Also, evaluate available documentation, learning resources, and technical support. Some companies offer extensive training, while others may provide more personalized support.

Is a Conversational AI Platform Worth the Cost?

It is common for businesses to question the cost of conversational AI platforms when planning their customer service investments. These systems offer several advantages on the backs of automated workflows, but require upfront spending and ongoing maintenance fees. For many businesses, especially enterprises, the investment proves worthwhile.

For example, a financial services firm can potentially cut its call center staffing after adding AI-driven chat services. Another example can be a retail outlet implementing chatbots to reduce support ticket volumes. 

There are plenty of examples that show how conversational AI solutions cut down operational expenses to let you save more and boost your ROI in the first year alone. This, however, does depend on your business goals. 

Every company cannot expect to see the same percentage of savings in the first year. You have to measure your conversational AI solutions against your business goals to see a clearer ROI picture. The strongest ROI cases combine multiple value sources rather than focusing solely on staff reduction.

Long-term benefits show up in other places as well to further confirm that conversational AI is worth every penny. Beyond direct savings, businesses see improved customer satisfaction scores, increased online sales, and better data collection for product improvements. 

The bottom line is that for businesses focused on efficiency and customer experience, the benefits often outweigh the initial investment.

Which Businesses Benefit Most From Conversational AI?

Conversational AI proves especially useful for enterprises or companies with over 1,000 employees that deal with high volumes of customer interactions. Deploying a single chatbot here can reduce call center costs by a significant margin. That said, mid-sized businesses with limited support teams can also benefit from AI solutions. However, when looking at the big picture, the ROI of conversational AI is pretty overwhelming in an enterprise-level setup and overshadows the improved efficiency and availability of a small business.  

Coming to industries with high value, here are all the sectors that are most suited to adopt conversational AI in 2025:

• Financial Services: Banks and insurance companies use chatbots to handle account inquiries and claims processing. 
• Healthcare: Medical practices reduce no-shows with appointment reminders and collect patient information before visits.
• Retail: E-commerce businesses answer product questions and process returns 24/7. 
• Travel & Hospitality: Hotels and airlines manage reservations and provide travel updates automatically. 

Reasons to Choose Mosaicx as Your Conversational AI Partner

Mosaicx is not just another name in the crowded AI market. We have a storied history of empowering enterprises through practical AI solutions. 

Our advanced conversational AI system, Mosaicx Engage, handles complex customer interactions without the robotic feel of typical chatbots. Your customers will feel like speaking with a live human agent. The difference being that our IVAs are better, faster, more accurate, and available 24/7. 

Choosing Mosaicx means partnering with a company that understands what businesses need from conversational AI. Whether it's cutting response times or providing reliable answers every time, our conversational AI platform delivers the results you are paying for.

Ready to revolutionize your customer experience? Schedule a demo today.