Despite significant investments in AI, many organizations struggle to translate this potential into compelling business outcomes.
Only a third of AI practitioners feel equipped with the right tools and are deploying predictive AI applications. takes an average of seven months – eight for generative AI. Even then, trust in these solutions is often low, preventing organizations from realizing the full value of their AI investments.
By streamlining deployment and empowering teams, the right AI applications and agents can help businesses deliver. predictive And Generative AI use cases faster and with better results.
What’s slowing down your success with AI applications?
Data science and AI teams often face long cycles, integration hurdles, and inefficient tools, making it difficult to deliver advanced use cases or integrate them into enterprise systems. business.
Custom patches can offer a quick workaround, but they often lack scalability, preventing businesses from fully unlocking the potential of AI. The result? Missed opportunities, fragmented systems and growing frustration.
To meet these challenges, DataRobot AI applications and agents help streamline deployment, accelerate timelines, and simplify delivery of advanced use cases, without the complexity of building from scratch.
AI applications and agents
Creating impactful AI use cases can be faster and more effective with custom AI solutions. More specifically, DataRobot’s new features offer:
- Streamlined deployment by reducing the need for extensive code rewrites.
- Pre-built templates for business logic, governance, and user experience to accelerate timelines.
- The ability to tailor approaches to meet your unique organizational needs, ensuring meaningful results.
![AI applications and agents](https://www.datarobot.com/wp-content/uploads/2024/12/AI-apps-and-agents--1024x639.png)
Collaborative AI Application Library
Disconnected workflows and scattered resources can slow AI deployment and stall progress. DataRobot’s customizable frameworks, hosted on GitHub, help teams establish a shared library of AI applications for:
- Start with a basic framework.
- Adapt it to the organization’s requirements.
- Share it across data science, application development, and business teams.
These organization-specific customizations enable teams to deploy faster, improve security, and drive seamless collaboration across the organization.
![Collaborative AI Application Library](https://www.datarobot.com/wp-content/uploads/2024/12/Collaborative-AI-application-library-1024x555.png)
How to Streamline Fragmented Workflows for Scalable AI
Creating user-friendly AI interfaces that seamlessly integrate with business workflows is often a slow and complex process. Custom development and integration challenges force teams to start from scratch, leading to inefficiencies and delays. Simplifying application development, hosting, and prototyping can accelerate delivery and enable faster integration into business workflows.
AI Applications Workshop
Setting up local environments and building Docker images often creates bottlenecks. Managing dependencies, configuring settings, and ensuring compatibility between systems are time-consuming manual tasks that are prone to errors and delays.
DataRobot Codespaces now allow you to create code-driven AI applications for your models using frameworks like Streamlit and Flask, simplifying development and enabling rapid creation and deployment of Personalized Generative AI application interfaces.
Codespace’s new built-in support improves this process by allowing you to easily develop, upload, test, and organize interfaces within a streamlined file system, eliminating common configuration issues.
![AI Applications Workshop](https://www.datarobot.com/wp-content/uploads/2024/12/AI-App-Workshop-1024x631.png)
Questions and answers app
Another new feature of DataRobot allows you to quickly create chat applications to prototype, test and equip generative AI models. With a simple, pre-built GUI, you can evaluate model performance, efficiently gather feedback, and collaborate with business stakeholders to refine your approach.
This streamlined approach accelerates early development and validation, while its flexibility allows you to customize or replace components as priorities change.
Adding custom metrics and performing stress testing ensures the application meets the organization’s needs, builds confidence in its responses, and is ready for seamless production deployment.
![Quality Assurance Application](https://www.datarobot.com/wp-content/uploads/2024/12/QA-App_-1024x549.png)
What’s holding back scalable AI applications?
Delivering scalable and reliable AI applications requires cohesion across workflows, tools and teams. Without streamlined sourcing, standardization and integration, delays and inefficiencies hinder progress and stifle innovation.
However, the right tools unify processes, reduce errors, and align results with business needs.
Declarative API Framework
DataRobot’s declarative API framework simplifies the development of scalable, repeatable AI applications for generative and predictive use cases, enabling teams to replicate work, save pipelines, and deliver solutions faster.
![Declarative API](https://www.datarobot.com/wp-content/uploads/2024/12/Declarative-API-1024x573.png)
SAP ecosystem integration in one click
Integrating AI models into existing ecosystems presents many challenges, including compatibility issues, siled data, and complex configurations. DataRobot’s one-click integration with SAP Data Sphere and AI Core simplifies this process by allowing you to:
- Connect seamlessly with minimal effort.
- Specify SAP credentials and compute resources.
- Bring models closer to your data for faster, more efficient scoring.
- Monitor deployments directly in DataRobot.
This integration minimizes latency, streamlines workflows, and improves scalability, allowing your AI solutions to operate seamlessly across the enterprise.
![SAP ecosystem integration in one click](https://www.datarobot.com/wp-content/uploads/2024/12/One-click-SAP-ecosystem-embedding-1024x641.png)
Transform your workflows with adaptable AI
AI integration should not disrupt your workflows, but rather improve them.
Imagine AI that adapts to your business: flexible, customizable and seamlessly deployable. With the right tools, you can overcome challenges, deliver value faster, and ensure AI becomes an enabler, not an obstacle.
When evaluating AI for your organization, the right AI applications and agents can help you focus on what really matters. Find out what’s possible with AI applications that help you realize enterprise AI at scale.
About the author
![Vika Smilanski](https://www.datarobot.com/wp-content/uploads/2024/10/vikasmilansky_headshot-300x300.jpg)