AI Builder vs. In-House Team - Which One Should You Choose?

Paul Omenaca

Paul Omenaca

@houmland
AI Builder vs. In-House Team - Which One Should You Choose?

LLMs hold an incredible transformative value, from knowledge management (searching through your data bases) to back office automation (drafting reports or reviewing contracts).

We believe this technology should be as accessible as possible to those who are closest to the challenges, to the ones that understand their unique business contexts.

That’s why Stack AI has become the development partner for over 50,000 builders worldwide, from operations, marketing, and data science teams, to CIOs and executives. Stack AI simplifies the lives of problem-solvers, being the Pioneer in AI No-Code Building.

What’s an AI Builder?

An AI builder is a platform or tool designed to simplify the process of creating, deploying, and managing AI applications. It features a user-friendly interface that enables individuals to design AI applications without needing technical skills.

There’s different levels of complexity for AI builders. From full no-code to low-code to model hosting platforms. At Stack AI, we focus on empowering those without technical expertise in coding or AI through a user-friendly drag-and-drop interface. This allows users to build AI applications by simply connecting functional blocks.

AI builders are characterized by:

  • Integration with other services: AI models, data sources, SaaS services available.
  • Customization options for both the logic of the AI application (i.e., backend) and the available user interface (i.e., how you are displaying your app to your end users)
  • Deployment options to various environments (e.g., cloud, on-premise) and scalability as needed.
  • Monitoring and management tools for performance, version control, user management, etc.

Comparison

AI BuilderIn-house Team
Cost✅ (Lower)❌ (Higher)
Time to Deployment✅ (Faster - weeks)❌ (Slower - months/years)
Scalability✅ (Easily scalable)❌ (Requires hiring)
Customization☑️ (Depends, high with StackAI) ☑️ (Depends on expertise)
Expertise Requirement✅ (Lower)❌ (Higher)
Updates✅ (Easy to switch models)❌ (Required development)
AI Expertise Spread✅ (Easily spread across the company)❌ (Siloed in Eng. and Prod. teams)
Learning Curve✅ (When user-friendly, less steep)❌ (Extensive training)
Regulatory Compliance and Security☑️ (Depends on certifications like SOC 2 & HIPAA) ☑️ (Depends on internal security investments)
Control Over Data☑️ (Depends on transparency and control features)✅ (Full control)

What Makes Stack AI So Advantageous?

Here are some features that make us incredibly easy to use and effective for building AI solutions:


user
experience

User Experience: Our platform is designed to be user-friendly, enabling anyone to build AI applications without needing technical expertise.



Customization

Customization: We offer a pre-built interface that you can customize to reflect your company’s look and feel. Add your custom domain and use Stack AI simply to power your application.



Models

AI Models: We offer leading AI models, from closed to open source, updating them as new versions are released. This allows you to easily switch models with a simple click, ensuring optimal performance.



Knowledge
bases

Knowledge Bases: We integrate with the most common data sources in the market, enabling you to connect your data securely to your AI models.



Certifications

Security: We are SOC 2 Type II, HIPAA, and GDPR compliant. Data security is our top priority, particularly for companies in sensitive industries such as healthcare and finance.



Credentials

Performance: Our algorithms, crafted by engineers from MIT, Ubuntu, NASA, and other top firms, focus on optimizing your AI application's performance. This ensures precise data handling and minimizes errors, enhancing reliability. Stack AI has one of the leading RAG (Retrieval Augmented Generation) systems in the market.

In a nutshell, our mission is to make your life easier so you can solve your business problems quickly and reliably.

Deep-dive: Cost Analysis of an AI Team

Determining the budget for an in-house AI team is challenging. Many of our customers approach us with this uncertainty. Below, we provide a high-level estimation of the main cost components considering a U.S. based company developing five AI solutions annually. Costs can vary depending on your company’s specific needs, but these figures offer a useful overview.


Budget

Given our economies of scale (with 55,000+ users developing applications), our costs for infrastructure, development, and support are significantly lower than those associated with hiring an in-house development team. Given our scale (i.e., we make thousands of daily API calls to OpenAI, Anthropic, etc.), we get better rates and rate limits. On average, our clients save 70-80% of their budget by partnering with us.

Moreover, teams demonstrate results in less than a month, with production-ready solutions rolled out in less than six months versus what would take at least one year.

What’s Next?

Once you try an AI builder there is no way back! We are confident in the value our platform offers and are excited to initiate a pilot program with you. If you're not completely satisfied, we offer a full money-back guarantee.

Schedule a call with us so we can understand your AI journey and draft a plan to make it happen!