Build or Buy? Top 10 Considerations for GenAI Search & Chat

In the dynamic and rapidly evolving world of GenAI with search and chat emerging as the leading business adoption use cases, there are a myriad of components and options to piece together effective systems. There is no single definitive approach to creating these solutions; each path has its own set of challenges and benefits.

As the technology landscape evolves swiftly, businesses are keen to capitalize on early adopter advantages rather than waiting for the market to mature. So, how can organizations embark on this journey while ensuring robust business governance, data security, scalability, and adaptability for future tech changes?

Here are the top ten considerations to guide the build or buy decision:

1. Effort

Buy: Out-of-the-box functionality in vendor solutions significantly reduces development time, allowing businesses to quickly deploy systems and capture market trends without delay. Some vendors do have specialized use cases templates that closely resemble an inhouse build fit-for-purpose use case.

Build: Building in-house provides complete control over design and features, but this process is time-consuming and requires a substantial effort, delaying market entry. Management would need to have patience and tolerance for trial and error.

2. Expertise and Experience

Buy: Vendors bring extensive experience and specialized knowledge, minimizing the learning curve and reducing implementation risks. This expertise ensures that the solution is robust and well-tested in the market by similar organizations.

Build: Developing in-house expertise can lead to solutions that are finely tuned to specific business needs and at the same time build up an internal expertise in the technology. However, building this expertise takes considerable time and investment, which may not be feasible for organizations where AI technology is not their primary business and there isn’t an existing team able to undertake this project.

3. Comprehensive Information Retrieval (IR) Stack

Buy: Pre-built solutions often come with comprehensive IR stacks that can integrate various data types and sources seamlessly, offering immediate benefits and operational efficiency.

Build: Custom-built IR stacks can be designed to cater to the unique data types and sources of an organization, and the IP is owned by the organization but this requires specialized skills and prolonged development time.

4. Advanced AI Capabilities

Buy: Vendors typically offer advanced AI features, such as natural language processing, search relevancy, machine learning models, recommendation engines, and predictive analytics, as part of their solutions. These features are built on extensive research and real-world applications.

Build: Custom solutions can incorporate bespoke AI and machine learning capabilities tailored to an organization's specific needs. However, developing these capabilities from scratch is resource-intensive and requires significant AI expertise.

5. Scalability

Buy: Vendor solutions are designed to scale easily, accommodating growing data volumes and user demands with minimal additional effort. This scalability is often a core feature of commercial offerings.

Build: While custom-built solutions can be designed with scalability in mind, ensuring they can handle future growth requires careful planning and substantial resources.

6. Integration

Buy: Vendor solutions often offer seamless integration with a wide range of third-party applications and data sources, speeding up implementation and reducing compatibility issues.

Build: Custom solutions can be tailored for seamless integration with existing systems, but this requires significant development effort and extensive testing to ensure compatibility.

7. Data Security and Compliance

Buy: Vendors adhere to stringent data security standards and regulatory requirements, providing peace of mind and reducing the compliance burden on the business.

Build: In-house teams have full control over data security measures and compliance, but this can be resource-intensive and require ongoing vigilance to maintain standards.

8. Training and Support

Buy: Vendors typically provide free online training, dedicated training and support, ensuring that businesses can maximize the platform’s benefits and troubleshoot issues effectively.

Build: In-house teams may need to develop their own training and support structures, which can be time-consuming and costly.

9. Maintenance and Updates

Buy: Vendors handle regular updates, bug fixes, and improvements, reducing the maintenance burden on the business and ensuring the solution remains up-to-date with the latest advancements.

Build: Ongoing maintenance and updates for custom-built solutions require significant in-house resources and a long-term commitment to continuous improvement.

10. Cost-Efficiency

Buy: Vendor solutions can be more cost-effective upfront due to economies of scale and pre-developed features. They offer predictable pricing models that include support and updates.

Build: While the initial costs for custom-built solutions may be higher, they can offer better long-term ROI if the solution is perfectly aligned with business needs. However, this requires careful financial planning and risk assessment.

Final Thoughts

The decision to build or buy GenAI search and chat solutions depends on various factors, including effort, expertise, integration, and cost-efficiency. While building offers unparalleled customization and control, it demands significant investment in time, resources, and specialized skills. For businesses that AI is not their core business, the path of building a solution in-house can pose substantial challenges, including the need to assemble a highly skilled team in a competitive market and the risk of errors that could hinder early adopter advantages.

Conversely, buying a solution from a reputable vendor provides immediate access to advanced features, scalability, and robust support, allowing businesses to quickly implement effective solutions and stay ahead in the competitive landscape. For most businesses, particularly those outside the AI tech industry, purchasing a pre-built solution is a pragmatic choice that balances innovation with practicality, ensuring a secure, scalable, and future-proof investment.

If you are at this crossroad, drop us an email for a chat info@bioquestsg.com