Build or buy enterprise AI search? Many companies seek clarity on this question when they decide to leverage a search solution. Their goal is to deliver relevant information to their users and enhance the self-service experience.
Yes, this dilemma is real. A misstep in choosing the right search solution can lead to inefficiencies, increased support costs, and frustrated customers—ultimately impacting both revenue and retention.
But no worries! This blog will guide you through decision-making, explaining key considerations for buying or building an enterprise search engine.
Let’s dive in!
Build vs Buy Enterprise AI Search: Key Consideration
Here are some key considerations you shouldn’t overlook before moving ahead with building or buying an enterprise AI search decision.
| Factors | Building enterprise search engine | Buying enterprise search |
| Cost-effectiveness | Higher investment | Lower expenses |
| Time to Market | Slow development | Rapid deployment |
| Scalability | Limited growth | Seamless scaling |
| Features | Custom-built tools | Pre-built solutions |
| Compliance | Complex process | Built-in security |
| Support | Internal handling | Vendor support |
Cost-effectiveness
Cost plays a crucial role in decision-making regarding building or buying. Building an enterprise search engine is complex and demands a significant investment. Depending on scope and complexity, initial development costs can vary from tens of thousands to millions of dollars, with ongoing maintenance adding further expenses.
The real question is, should organizations make such a large investment in developing an enterprise AI search solution? If a ready-made solution can deliver the same or better results, wouldn’t it be the smarter choice?
Even for organizations with ample resources, developing an AI-powered enterprise search from scratch requires specialized expertise and robust infrastructure.
On the other hand, buying an enterprise search engine is a more efficient and cost-effective option. It comes with lower upfront costs and predictable subscription pricing. Various enterprise search vendors offer scalable solutions, including maintenance, updates, and security. This eliminates the need for additional development, hiring expertise, maintenance, and infrastructure.
Above all, it allows organizations to reallocate resources toward innovation and business expansion rather than managing search infrastructure and support costs.
Time to Market
Building an enterprise AI search can take months or even years. The reason? Developing a solution is complex and requires extensive research, meticulous design, rigorous development, testing, and continuous optimization. If it gets delayed at any stage, it will extend the development process and postpone tangible business impact.
However, buying pre-built enterprise search software enables organizations to implement it quickly. Since the development, testing, and software optimization have already been completed, it becomes easy to integrate it into their existing system with minimal setup time. Additionally, it accelerates ROI and expedites seeing measurable business outcomes.
So here is a question for you:
As a decision maker, would you like to wait years or deploy enterprise AI search now to start seeing results immediately?
Scalability
Scalability plays a crucial role when choosing build vs. buy. Developing an enterprise search solution comes with significant scalability challenges.
Organizations require continuous resources, time, and infrastructure investment to scale a solution to cater to growing users, data, or new features. Without dedicated efforts, scaling can become more complex, leading to performance bottlenecks.
In contrast, out-of-the-box AI search solutions are designed to accommodate your growing business needs. Cloud-based and enterprise-level solutions seamlessly manage more workloads, bigger data sets, and more users without needing extensive infrastructure upgrades or extra manual labor.
Therefore, buying enterprise search solutions is the smarter and more efficient choice for scalability.
Features
Another crucial factor that helps in the decision-making process is feature flexibility. Building an enterprise AI search solution offers you the flexibility to develop features that suit your business needs. However, you require expertise, resources, and significant time to build, test, and optimize those features with evolving demands.
In contrast, pre-built search solutions have comprehensive pre-configured features like NLP capabilities, analytics, AI-powered ranking, and integrations. These features are thoroughly tested, continuously optimized, and ready for deployment without hefty development efforts.
Compliance
For support leaders, ensuring compliance when deciding whether to build or buy an AI-powered enterprise searchis crucial.
Developing your search solution means taking responsibility for complying with various industry standards, including GDPR, SOC 2, or HIPAA, to ensure data privacy and security. Achieving and maintaining compliance is a continuous, resource-intensive process. Implementing data encryption, access controls, auditing, legal compliance measures, and regular updates requires extensive effort as regulations evolve.
However, purchasing an enterprise AI search solution usually comes with pre-configured security and compliance capabilities. With built-in compliance, enterprise search providers handle data protection, encryption, and role-based access—reducing the workload for your IT and legal departments.
Support
Developing enterprise AI search often adds operational strain. It requires ongoing support from internal teams to manage maintenance, updates, and troubleshooting, which can be intensive and challenging.
However, a purchased solution has enterprise search vendor assistance, ensuring you’ll receive timely updates and expert help for issue-solving without putting much of a load on internal teams.
Conclusion
To navigate the build-vs-buy dilemma, choose the option that best aligns with your business requirements. If you want to deploy enterprise AI search quickly and have specific requirements, a hybrid approach—combining buying and building — would be the best for you.
Organizations can purchase a pre-built enterprise search engine as a starting point and then customize it with particular business requirements. This way, you can have the best of both worlds regarding effort, cost, control, scalability, and other factors mentioned above.
