Enterprise software development is entering a new era—where delivery speed is expected, but trust is everything. And most AI tools weren’t built for that.
Most AI coding tools are built for speed—not for scale. They lack context, governance, and the ability to operate across complex enterprise environments.
Tabnine is different. At NVIDIA GTC 2025, we showcased how Tabnine helps the world’s most advanced engineering teams scale AI across the SDLC—without compromising on quality, security, or governance.
Why Now: AI Has Hit the Enterprise Wall
AI adoption is exploding, but the returns aren’t. According to Google’s DORA report, every 25% increase in AI adoption correlates with a drop in delivery performance. At the same time, Gartner forecasts that 75% of enterprise developers will be using AI code assistants by 2028.
So what’s going wrong?
Engineering leaders tell us the same thing: they’re stuck balancing speed with control. Most AI tools simply don’t scale. They lack the context to enforce architectural consistency, the governance to comply with enterprise policies, and the flexibility to support multi-team, multi-region environments. Worse, they often create more technical debt than they eliminate.
To truly drive value, AI needs to be:
- Context-aware across your codebase, tickets, documentation, and architecture.
- Controllable with enforceable standards and fine-grained governance.
- Customizable to your infrastructure, policies, and languages.
That’s what Tabnine delivers.
Trusted AI That Aligns to Your Standards, Not Public Repos
At GTC, we showed how Tabnine transforms AI from an unpredictable assistant into an accountable engineering teammate—context-aware, policy-aligned, and infrastructure-ready.
A Context Engine That Reduces Review Time, Not Just Typing
Tabnine’s advanced context engine connects deeply with your development environment. It doesn’t just look at the current file—it understands the architectural patterns across your services, the standards in your PRs, the rules in your Jira workflows, and the language of your documentation.
With this deep organizational understanding, Tabnine is able to deliver AI assistance that’s not only fast—but accurate, relevant, and enterprise-aligned:
- Generate code that adheres to your existing service architecture and system design patterns, reducing architectural drift and rework.
- Suggest implementation patterns grounded in your team’s historical approaches, ensuring consistency across codebases and teams.
- Prevent rework and redundant reviews by aligning code output with your organization’s documented standards, naming conventions, and preferred frameworks.
Security and Compliance That Scale with You
Security teams at GTC were especially drawn to our provenance and attribution system—a built-in safety net that brings full transparency to AI-generated code. By flagging overlaps with public sources and surfacing license metadata in real-time, Tabnine helps teams mitigate open-source compliance risks before code ever makes it into production.
For highly regulated industries and security-sensitive teams, Tabnine delivers compliance and control at every level of the development lifecycle:
- License-aware generation that automatically filters and suppresses code suggestions based on disallowed license types (e.g., GPL), aligned to your internal policies.
- Policy-driven validation inside the IDE and pull requests to enforce compliance with your secure coding and architectural standards.
- Flexible, enterprise-grade deployment options including SaaS, VPC, on-premises, and fully air-gapped environments—giving you complete control over your AI footprint.
This isn’t a nice-to-have. For enterprise-grade software development, AI governance is non-negotiable.
Turn Your Best Engineers Into On-Demand Mentors
With Tabnine’s Coaching and Code Review Agent, organizations can capture and operationalize the judgment of their most experienced engineers—making it instantly available to every developer across the team.
This agent functions like your top reviewer on-demand—always available to coach, guide, and enforce excellence at scale. It enables you to:
- Define custom rulesets for architecture, readability, security, correctness, performance, and maintainability.
- Enforce them directly in the IDE, and as part of the PR process.
- Automatically flag violations and suggest improvements.
You’re no longer bottlenecked by reviewer availability or institutional knowledge. With Tabnine, excellence becomes standardized, repeatable, and on-demand.
Why Enterprises Choose Tabnine + Dell AI Factory
Enterprises want AI that’s fast, powerful, and private. That’s why Tabnine partnered with Dell Technologies to deliver a fully on-premises, GPU-accelerated AI coding assistant—designed specifically for enterprise-grade scale, control, and performance.
This isn’t theoretical. This is a turnkey solution, already in market. Tabnine integrates directly with Dell PowerEdge servers and NVIDIA GPUs to provide everything enterprise software teams need to deploy AI in secure, air-gapped environments—no cloud required. The result: maximum velocity without compromising IP, data privacy, or compliance.
With Tabnine on Dell AI Factory infrastructure, organizations can run the industry’s most contextually aware AI development agents entirely within their private environments. From local inference on Dell PowerEdge R760xa servers with NVIDIA L40S GPUs, to scaling across large environments with Dell XE9680 and H100 GPUs, this deployment model ensures teams get the performance and flexibility they need without sacrificing control.
This solution is optimized for every step of the SDLC—from planning to testing—and supports integration with your IDE, repos, Jira, and existing dev workflows. It’s fully customizable, scalable, and validated to perform with Dell’s enterprise hardware. No guesswork. Just a trusted path to secure, AI-powered software development.
This is the future of enterprise AI: on-prem, fully governed, and built for how your engineering team actually works.
Powered by NVIDIA: Innovation Without Compromise
As a member of the NVIDIA Inception program, Tabnine is working closely with NVIDIA to bring high-performance, low-latency AI to every phase of software development.
For NVIDIA customers, this partnership means their investment in GPU infrastructure now extends into secure, governed AI development workflows. Whether you’re training your own models or leveraging Tabnine’s proprietary ones, NVIDIA makes it performant—and Tabnine makes it useful.
How Tabnine Compares: Alignment Over Hype
Attendees at NVIDIA GTC—ranging from seasoned CIOs to hands-on software engineering leaders—were eager to understand how Tabnine’s enterprise-grade approach compares to the other tools in the market. Unlike generic AI solutions that focus narrowly on productivity, Tabnine is designed from the ground up to align with the standards, security posture, development processes, and infrastructure needs of sophisticated enterprise software teams.
Tabnine is not just another code assistant. It is a full-stack AI software development platform, built to operate with context, comply with policy, and scale across thousands of engineers—without introducing chaos or compromise. With our advanced context engine, multi-agent architecture, and governance capabilities, we’ve delivered a platform that acts more like an experienced engineering teammate than a tool.
Tabnine vs. GitHub Copilot
GitHub Copilot is a strong tool for individual productivity—but it wasn’t designed for enterprise rigor.
Tabnine outperformed Copilot across multiple use cases in Gartner’s Critical Capabilities Report, including code generation, debugging, and explanation—areas that directly impact delivery velocity and quality. While Copilot operates primarily with local file context and public data, Tabnine connects to GitHub, GitLab, Bitbucket, and Jira (both Cloud and Data Center), building a broader and more relevant understanding of your entire engineering environment.
Copilot is cloud-only. Tabnine gives you full deployment freedom—SaaS, VPC, on-prem, or fully air-gapped—with privacy-preserving architecture and IP indemnification.
Most importantly, while Copilot focuses on in-editor suggestions, Tabnine supports the entire SDLC. With dedicated AI agents for planning, coding, testing, documentation, and review, we’re not just speeding up keystrokes—we’re transforming workflows.
Tabnine vs. Cursor
Cursor takes an interesting swing—but it requires teams to adopt a new IDE, new workflows, and a limited ecosystem. For many enterprise organizations, that’s a high-friction, high-risk path.
Tabnine meets your developers where they already are—IntelliJ, VS Code, JetBrains, Eclipse—minimizing disruption while accelerating productivity.
Where Cursor offers local context, Tabnine’s advanced context engine reasons across entire repositories, issue trackers, documentation, and standards—delivering contextually relevant results—governed, high quality, and tuned to how your organization actually builds software.
And while many new tools rely on usage-based pricing, Tabnine provides predictable, flat seat-based pricing. No token anxiety. No scale surprises.
Bottom line: If you want a fast way to generate generic code, Copilot and Cursor may suffice. But if you need an enterprise-grade AI platform that aligns with your people, processes, policies, and infrastructure—Tabnine is the clear choice.
Model Sovereignty: Total Control, Total Flexibility
Tabnine is model-agnostic and enterprise-obsessed—built for organizations that demand architectural freedom and long-term optionality in their AI strategy.
Whether you’re experimenting with open models, operationalizing proprietary LLMs, or fine-tuning specialized models for regulated domains, Tabnine gives you the control to decide what runs, where, and how.
- Deploy in your environment: Run Tabnine entirely on your own infrastructure for maximum privacy, including on-prem, VPC, or air-gapped environments.
- Bring your own model: Integrate your fine-tuned or domain-specific models via private endpoints or through providers like Bedrock or Azure.
- Use Tabnine’s secure, IP-safe models: Leverage Tabnine’s proprietary models that are optimized for enterprise quality, safety, and reliability.
This is what true AI sovereignty looks like—total control over your models, your data, and your development future.
AI That Engineers Trust. A Platform You Can Own.
The future of software development isn’t generic. It’s governed. It’s contextual. It’s fast and secure and tailored to your business.
Tabnine is the AI platform that helps engineering leaders accelerate delivery—without increasing risk. We turn your standards into systems. Your best practices into agents. And your expertise into leverage.
AI is no longer just a tool. It’s your next great teammate—one that helps your developers ship faster, safer, and smarter than ever before.
And if you stopped by the Tabnine booth at GTC—thank you. It was a privilege to connect with so many forward-thinking engineering leaders. Congratulations to our giveaway winners—we hope you’re enjoying your gear and continuing the journey toward scalable, trustworthy AI in software development.
Explore how Tabnine can align with your enterprise AI strategy—securely, scalably, and on your infrastructure.
