After speaking with hundreds of AI teams across the globe, one thing is clear: the only certainty is uncertainty.
From Boston to Dubai, I hear the same stories: AI teams feel stuck.
Leaders are forced into two bad options—build AI from scratch or buy a point solution that doesn’t quite fit.
The trust in AI simply isn’t there yet; it’s not reliable enough for most businesses to fully depend on.
And across the board, many teams lack the complete set of skills or expertise needed to truly deliver on AI’s promise.
At DataRobot, we understand the stakes. Since our inception, we’ve focused on AI that drives meaningful impact and tackles tough AI problems, which is why I am excited to announce the DataRobot Enterprise AI Suite.
Introducing the DataRobot Enterprise AI Suite
Our commitment to helping organizations achieve meaningful outcomes with AI led us to create the enterprise AI suite—a comprehensive solution made up of customizable AI applications built on a flexible platform.
This suite is designed to give you everything you need to infuse AI into your business, secure your AI outcomes, and empower your AI teams.
AI that works where and how your business teams want.
We intimately understand the complex, multifaceted challenges AI teams wrestle with when trying to ensure AI fits seamlessly into stakeholder workflows, tools of choice, and exact business requirements.
That’s why we built a fully customizable suite of AI apps to address your unique business needs, making it easy to embed AI wherever your users work—whether in a standalone app, SAP applications, or tools like Slack and Microsoft Teams.
Multiple AI techniques at your fingertips.
We also appreciate that your organization’s needs aren’t one-size-fits-all. You need different AI techniques to create outcomes that make sense for your business.
Our suite gives you and your team the flexibility to apply the AI techniques that align with your business goals—whether it’s agentic flows, predictive insights, or retrieval-augmented generation (RAG)—enabling you to tackle multiple use cases with confidence.
Streamline collaboration.
One thing we hear often is how challenging it is for teams to collaborate effectively when developing, deploying, and governing AI outcomes. Pipelines are often brittle and complex, and handing off projects from one team to another can feel like an uphill battle, making it difficult to get AI solutions into production efficiently.
To help ease this burden, we designed our AI app development platform with bespoke tools that equip each team member with what they need—without the hassle of stitching together multiple tools.
You have the flexibility and control to integrate and work with the tools you prefer, accessing the most popular LLMs and models, or bringing your own.
And to accelerate development and delivery even further, our platform automates the most labor-intensive steps, from data prep and testing to CI/CD pipelines and governance.
Think of the efficiency, collaboration, reliability, transparency, and quality assurance DevOps has provided for software developers.
That’s what we’re doing for AI.
By giving everyone on your AI team the exact tooling and techniques to work how and where they want, while ensuring seamless collaboration between project hand-offs, we’re ensuring your AI model integrity is maintained from end-to-end.
The combination of our AI app-building platform, diverse AI techniques, and fully customizable apps that integrate seamlessly into business workflows is why leading Fortune 500 companies turn to DataRobot. We’re able to help them augment their hyperscaler investments and scale AI, delivering 10x the number of use cases.
As part of our enterprise AI suite, we’ve also launched over 30 new, industry-leading features.
You’ll gain deeper insights into what these are in future blog posts but, because there are ones I believe will be massively impactful I want to highlight a few that I’m most excited about.
Infuse AI into your business
Despite billions invested in AI, only a third of AI teams feel equipped with the tools needed to meet their business objectives. Generative AI app experience and implementing AI into the business were two of the primary unmet needs facing teams.
Two new features are designed to address these specific challenges.
Customizable AI apps and agents
We’ve codified the most common technology patterns in AI use cases into fully customizable templates, drawing from a decade of applied AI experience and thousands of diverse deployments.
This gives you and your team complete control over business logic, app logic, security, governance, and UX, allowing you to focus on outcomes instead of piecing together pipelines.
Once built, apps can be shared as templates or added to our AI App Gallery for others to use and build upon.
One-click embedding of AI into popular business applications
Because AI isn’t always used in standalone apps, we’ve added one-click embedding for Slack, Microsoft Teams, and SAP.
As SAP’s only AI partner of choice, we’ve made it effortless to embed your applications and monitoring agents into the SAP ecosystem. With direct access to SAP Datasphere and AI Core, your models are closer to your data, which means faster, more efficient scoring.
Secure your AI outcomes
For over a decade, we’ve worked with AI leaders in highly regulated industries like finance, healthcare, and government, making AI security and governance a central focus.
This experience has shaped our approach to managing regulatory, security, and operational risks, and sharpened our understanding that as you scale, your risk exponentially grows with your AI surface area.
Now, as generative AI and agentic workflows add new layers of complexity, we’re applying our experiences to help you keep your AI solutions secure and compliant in production.
Our new industry-first tools help you ensure consistent, reliable oversight as you expand:
Regulation-ready AI and one-click generative AI compliance reports
With regulations like the EU AI Act, NYC Law No. 144, and California Law AB-2013 on the rise, compliance can be complex and time-consuming.
Our one-click generative AI compliance reports simplify this process by mapping key requirements directly to your documentation, streamlining model risk management (MRM) processes and regulatory adherence.
And because we know that achieving compliance is only the first step, we’ve introduced governance testing and alerts to help you maintain compliance, adapt to evolving standards, and reduce manual review time.
We’ve provided compliance documentation for predictive AI for years and have seen firsthand how it speeds up MRM processes, scales operations, and increases AI solutions in production tenfold. Extending this capability to generative AI was a natural next step.
AI red-team testing and add-on observability shield
Brand reputation and risk management are top of mind for AI leaders implementing generative AI, and manual security checks can’t always keep pace.
To address this, our new red-team testing flags vulnerabilities like PII leaks, prompt injections, toxicity, and bias, so you can maintain safety and compliance with less effort.
In addition, our new add-on observability offers real-time monitoring for any generative AI application built off the DataRobot platform. With just a single line of code, you can:
- Create an AI firewall that delivers observability, intervention, and moderation across all your agentic and generative AI solutions.
- Apply enterprise governance, real-time oversight, and moderation to components like LLMs, vector databases, and RAG flows.
Empower your AI teams
Unlocking AI’s full potential requires overcoming technical hurdles that can stretch model development to an average of seven months. And with most AI projects passing through five different teams, using an average of seven different tools and twelve coding languages, the process is often fragmented and complex.
This fractured approach leaves teams tangled in tooling rather than driving results and expanding their skills.
We’ve always prioritized giving teams the flexibility to work in the environments they prefer, with smooth transitions between code and GUI, predictive and generative.
That’s why we’ve prioritized giving teams flexibility to work in their preferred environments, ensuring smooth transitions between code and GUI, predictive and generative models.
Our latest release goes even further, with new building blocks that simplify the development process from start to finish.
- Coding blocks: These highly scalable coding blocks eliminate code complexity, streamline collaboration, accelerate production, and simplify maintenance over time—creating a seamless path for building end-to-end AI applications.
- Automated data preparation: We’ve minimized the manual and complex work needed to make data AI-ready for both predictive and generative applications. Enhanced functionality, including automated data healing, insights visualization, and feature detection help you move from raw data to feature engineering and modeling in minutes instead of hours.
- Multimodal incremental learning and unstructured data processing: With our new incremental learning across different data types, your teams can finally unlock the full potential of your organization’s data. This unique approach empowers teams to tackle a wide range of AI use cases without limitations on data size or type, process data efficiently, prevent overfitting, improve accuracy, and control compute costs.
In addition, built-in optical character recognition (OCR) transforms unstructured documents into generative AI-ready data, accelerating model training and enhancing outcomes.
AI that works for your business
The future of AI is about more than just technology — it’s about solving real business challenges in a way that makes sense for your organization.
Imagine AI seamlessly integrated into your workflows, evolving with your needs, and empowering your teams to make smarter decisions faster.
This is just the beginning. With the right tools and techniques, you can unlock new potential, streamline processes, and drive real value.
The path forward is full of possibilities, and the next step is yours to take.
To learn more, check out DataRobot’s full suite of products.
About the author
As Chief Product Officer at DataRobot, Venky Veeraraghavan drives the definition and delivery of the DataRobot Enterprise AI Suite. Venky has twenty-five years of experience focusing on big data and AI as a product leader and technical consultant at top technology companies (Microsoft) and early-stage startups (Trilogy).